Note: Descriptions are shown in the official language in which they were submitted.
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SYSTEMS AND METHODS FOR INSPECTING A RAILROAD
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of and priority to U.S.
Provisional Application
No. 62/799,033, filed on January 30, 2019, which is hereby incorporated by
reference herein
in its entirety.
TECHNICAL FIELD
[0002] The present disclosure relates generally to inspection systems,
and more
particularly, to systems and methods for inspecting a railroad or a roadway.
BACKGROUND
[0003] Transportation pathways such as railroads and roadways are often
inspected to
identify various conditions (e.g., defects) that may require maintenance or
repair. Inspection
systems often utilize a camera located on a moving transport device that
captures images of a
given length of the railroad or roadway (e.g., several miles). However,
reviewing each of the
captured images to identify the various conditions can be extremely time
consuming and
inefficient. Similarly, it is impracticable or difficult to transmit each of
the captured images
from the transport device to a remote device for analysis and/or viewing in
substantially real-
time. The present disclosure is directed to solving these and other problems.
SUMMARY
[0004] According to some implementations of the present disclosure, a
method for
analyzing one or more conditions of a transportation pathway includes
obtaining, using an
imaging device of an inspection system, image data reproducible as a plurality
of images of the
transportation pathway, each of the plurality of images being reproducible as
an image of a
portion of the transportation pathway, each portion of the transportation
pathway having an
associated location along a length of the transportation pathway, analyzing,
using one or more
processors of the inspection system, the image data to determine a first
plurality of metrics
indicative of a condition of the transportation pathway at each of the
associated locations, and
generating a first graph, using the determined first plurality of metrics,
that is indicative of the
condition of the transportation pathway at each of the associated locations.
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[0005] According to some implementations of the present disclosure, a
method for
analyzing ballast of a railroad includes obtaining, using an imaging device of
an inspection
system, image data reproducible as a plurality of images of the railroad, each
of the plurality
of images being reproducible as an image of a portion of the railroad, each
portion of the
railroad having an associated location along a length of the railroad,
determining a plurality of
metrics by analyzing, using one or more processors of the inspection system,
the image data,
the plurality of metrics being indicative of a condition of the ballast of the
railroad at each of
the associated locations; and generating a graph using at least a portion of
the determined
plurality of metrics for visually illustrating the condition of the ballast of
the railroad for at
least a portion of the associated locations.
[0006] According to some implementations of the present disclosure, a
method for
analyzing cross-ties of a railroad includes obtaining, using an imaging device
of an inspection
system, image data reproducible as a plurality of images of the railroad, each
of the plurality
of images being reproducible as an image of a portion the railroad, each
portion of the railroad
having an associated location along a length of the railroad, determining a
plurality of metrics
by analyzing, using one or more processors of the inspection system, the image
data, the
plurality of metrics being indicative of a condition of the cross-ties of the
railroad at each of
the associated locations, and generating a graph using at least a portion of
the determined
plurality of metrics for visually illustrating the condition of the cross-ties
of the railroad for at
least a portion of the associated locations.
[0007] According to some implementations of the present disclosure,
amethod for
analyzing the presence or absence of one or more components of a railroad
includes obtaining,
using an imaging device of an inspection system, image data reproducible as a
plurality of
images of the railroad, each of the plurality of images being reproducible as
an image of a
portion the railroad, each portion of the railroad having an associated
location along a length
of the railroad, determining a plurality of metrics by analyzing, using one or
more processors
of the inspection system, the image data, the plurality of metrics being
indicative of the
presence or absence of a component of the railroad at each of the associated
locations, and
generating a graph using at least a portion of the determined plurality of
metrics for visually
illustrating the presence or absence of the component of the railroad at each
of the associated
locations.
[0008] According to some implementations of the present disclosure, a
method for
analyzing a conductive rail cover for one or more conductor rails of a
railroad includes
obtaining, using an imaging device of an inspection system, image data
reproducible as a
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plurality of images of the railroad, each of the plurality of images being
reproducible as an
image of a portion the railroad, each portion of the railroad having an
associated location along
a length of the railroad, determining a plurality of metrics by analyzing,
using one or more
processors of the inspection system, the image data, the plurality of metrics
being indicative of
a distance between a surface of the one or more conductor rails and the
conductor rail cover at
each of the associated locations, and generating a graph using at least a
portion of the
determined plurality of metrics for visually illustrating the distance at each
of the associated
locations.
[0009] According to some implementations of the present disclosure, a
method for
analyzing drainage of a railroad track includes obtaining, using an imaging
device of an
inspection system, image data reproducible as a plurality of images of the
railroad track, each
of the plurality of images being reproducible as an image of a portion the
railroad track, each
portion of the railroad having an associated location along a length of the
railroad track,
determining a plurality of metrics by analyzing, using one or more processors
of the inspection
system, the image data, the plurality of metrics being indicative of a
drainage condition of the
railroad track, and generating a graph using at least a portion of the
determined plurality of
metrics for visually illustrating the drainage condition at each of the
associated locations.
[0010] According to some implementations of the present disclosure, a
method for
analyzing vegetation within a right-of-way of a railroad includes obtaining,
using an imaging
device of an inspection system, image data reproducible as a plurality of
images of the railroad,
each of the plurality of images being reproducible as an image of a portion
the railroad, each
portion of the railroad having an associated location along a length of the
railroad, determining
a plurality of metrics by analyzing, using one or more processors of the
inspection system, the
image data, the plurality of metrics being indicative of a condition of
vegetation within the
right-of-way of the railroad at each of the associated locations, and
generating a graph using at
least a portion of the determined plurality of metrics for visually
illustrating the condition of
the vegetation within the right-of-way of the railroad at each of the
associated locations.
[0011] According to some implementations of the present disclosure, a
method for
analyzing one or more conditions of a transportation pathway includes
obtaining, during a first
inspection of the transportation pathway at a first time image data
reproducible as a plurality
of images of the transportation pathway, each of the plurality of images being
reproducible as
an image of a portion of the transportation pathway, each portion of the
transportation pathway
having an associated location along a length of the transportation pathway,
determining a first
plurality of metrics by analyzing the image data, the first plurality of
metrics being indicative
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of a first condition of the transportation pathway at each of the associated
locations at the first
time, displaying a first graph, using at least a portion of the determined
first plurality of metrics,
to visually illustrate the first condition of the transportation pathway at
each of the associated
locations at the first time; and displaying a second graph, using at least a
portion of a second
plurality of metrics, to visually illustrate the first condition of the
transportation pathway at
each of the associated locations at a second time that is different from the
first time.
[0012] According to some implementations of the present disclosure, a
method for
analyzing one or more conditions of a railroad including obtaining, using an
imaging device,
image data reproducible as a plurality of images of the railroad, each of the
plurality of images
being reproducible as an image of a portion of the railroad, each portion of
the railroad having
an associated location along a length of the railroad; analyzing, using one or
more processors,
the image data to determine (i) a first plurality of metrics indicative of a
first condition of the
railroad at each of the associated locations and (ii) a second plurality of
metrics indicative of a
second condition of the railroad at each of the associated locations;
displaying, on a display
device, a first graph, using at least a portion of the first plurality of
metrics, to visually illustrate
the first condition of the railroad; and displaying, on the display device, a
second graph, using
at least a portion of the second plurality of metrics, to visually illustrate
the second condition
of the railroad, the second graph being displayed adjacent to the first graph
on the display
device at the same time.
[0013] According to some implementations of the present disclosure, a
system for
inspecting a transportation pathway includes an imaging device; and a memory
device storing
machine readable instructions configured to be executed by one or more
processors to cause
the system to: cause the imaging device to generate first image data
reproducible as a first
image of a first portion of the transportation pathway at a first location;
analyze the first image
data to determine a first metric indicative of a condition for the first
portion of the transportation
pathway; cause the imaging device to generate second image data reproducible
as a second
image of a second portion of the transportation pathway at a second location
that is a
predetermined distance from the first location; analyze the second image data
to determine a
second metric indicative of the condition for the second portion of the
transportation pathway;
and generate a graph, using the first metric and the second metric, that is
indicative of the
condition at the first location and the second location.
[0014] The above summary is not intended to represent each embodiment or
every aspect
of the present invention. Additional features and benefits of the present
invention are apparent
from the detailed description and figures set forth below.
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BRIEF DESCRIPTION OF THE DRAWINGS
[0015] FIG. 1 is a functional block diagram of an inspection system,
according to some
implementations of the present disclosure;
[0016] FIG. 2 is an image of a portion of a railroad including running
rails, cross-ties, and
ballast, according to some implementations of the present disclosure;
[0017] FIG. 3 is an image of a portion of the railroad including a
conductive rail and a
conductive rail cover, according to some implementations of the present
disclosure;
[0018] FIG. 4 is an image of a portion of a railroad including running
rails, cross-ties, and
vegetation, according to some implementations of the present disclosure;
[0019] FIG. 5 is a process flow diagram for a method for analyzing one or
more conditions
of a railroad track, according to some implementations of the present
disclosure;
[0020] FIG. 6 illustrates a plurality of graphs indicative of conditions
of a railroad,
according to some implementations of the present disclosure; and
[0021] FIG. 7 illustrates a plurality of graphs indicative of a rail
corrugation condition of a
railroad, according to some implementations of the present disclosure.
[0022] While the disclosure is susceptible to various modifications and
alternative forms,
specific embodiments thereof have been shown by way of example in the drawings
and will
herein be described in detail. It should be understood, however, that it is
not intended to limit
the invention to the particular forms disclosed, but on the contrary, the
intention is to cover all
modifications, equivalents, and alternatives falling within the spirit and
scope of the invention
as defined by the appended claims.
DETAILED DESCRIPTION
[0023] Referring to FIG. 1, an inspection system 10 includes one or more
processors 12
(hereinafter, "processor"), one or more memory devices 14 (hereinafter,
"memory device"),
one or more imaging devices 16, one or more sensors 18, a GPS module 20, and a
communication module 22. The inspection system 10 is coupled to a transport
device 30 and
is generally used to inspect a transportation pathway (e.g., a railroad or a
roadway), determine
metric indicative of one or more conditions of the transportation pathway,
generate one or more
graphs indicative of the one or more conditions, and transmit the graph(s) to
a remote system
40 so that they can be displayed and viewed/analyzed by a user.
[0024] The transport device 30 is moveable along the transportation
pathway. In some
implementations, the transport device 30 is autonomous, meaning that it can be
operated with
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little or no human intervention. In other implementations, the transport
device 30 is manually
operated by a user that is located on the transport device 30 or remotely
controlled by a user
that is not located on the transport device 30. In the case of a railroad, the
transport device 30
can be a locomotive, a railcar, a passenger car, a freight car, a tram, a
subway car, a railroad
vehicle, a road vehicle (e.g., a vehicle configured to operate on both a
railroad and a roadway,
etc.) In the case of a roadway, the transport device 30 can be a car, a truck,
a bus, a motorcycle,
an autonomous vehicle, or the like. Further, in some implementation, the
transport device 30
can be an aerial vehicle (e.g., an unmanned aerial vehicle) configured to fly
over the
transportation pathway (e.g., railroad or roadway) at a predetermined
altitude.
[0025] The processor 12 of the inspection system 10 is communicatively
coupled to the
memory device 14, the camera 16, the sensors 18, the GPS module 20, and the
communication
module 22, and is generally used to control the operation of these components
of the system
and implement the methods described herein. The memory device 14 is generally
used to
store machine readable instructions that are executable by the processor 12.
Generally, the
memory device 14 can be any suitable computer readable storage device or
media, such as, for
example, a random or serial access memory device, a hard drive, a solid state
drive, a flash
memory device, etc.
[0026] The imaging device(s) 16 are generally used to generate image data
reproducible as
one or more images of the transportation pathway. That is, as the transport
device 30 moves
along the transportation pathway (e.g., railroad or roadway), the imaging
device(s) 16
continuously generate image data. In some implementations, the imaging
device(s) 16 are
configured to only generate image data responsive to movement of the transport
device 30 and
are configured to cease generating image data when the transport device 30
stops moving. In
some implementations, the imaging device(s) 16 also include one or more light
sources to
illuminate the transportation pathway (e.g., in a tunnel) and aid in
generating image data (e.g.,
fluorescent bulbs, incandescent bulbs, light emitting diodes (LEDs), arc
lamps, flashtubes,
etc.).
[0027] The imaging device(s) 16 can be coupled at various locations on
the transport device
30 to capture image data of different portions of the transportation pathway.
In some
implementations, the imaging device(s) 16 are coupled to an underside of the
transport device
30 such that the captured image data is reproducible as a plurality of images
showing a plan or
top view of the transportation pathway. For example, referring to FIG. 2, in
such
implementations, the imaging device(s) 16 can capture images of a railroad 200
including a
first running rail 210A, a second running rail 210B, a first cross-tie 212A, a
second cross-tie
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212B, and ballast 214. As described in further detail herein, the imaging
device(s) 16 can
capture a plurality of such images of the railroad 200 like the one shown in
FIG. 2, each of
which is associated with a location along the railroad 200 and analyzed to
determine a metric
indicative of a condition of the railroad 200 (e.g., a condition of the
ballast 214, a condition of
the running rail 210A, a second of the running rail 210B, a condition of the
first cross-tie 212A,
a condition of the second cross-tie 212B, or any combination thereof).
[0028] In some implementations, the imaging device(s) 16 can be coupled
to the transport
device 30 such that a field of view of the imaging device(s) is generally
perpendicular to the
direction of travel of the transport device 30. For example, referring to FIG.
3, in such
implementations, the imaging device(s) 16 can capture images of a railroad
includes a
conductive rail 310 (a/k/a power rail or third rail) and a conductive rail
cover 316. The
conductive rail 310 is an electrified rail (e.g., to provide power to a subway
car) that is
positioned on top of an insulator 312. Brackets 314 position cover 316 such
that it at least
partially overlies an upper surface of the conductor rail 310, aiding in
protecting the conductor
rail 310 from damage (e.g., rain, sun, debris, etc.) and inadvertent contact.
As described in
further detail herein, the imaging device(s) 16 can capture images like the
one shown in FIG.
3, each of which is associated with a location along the railroad and analyzed
to determine a
metric indicative of a condition of the railroad (e.g., a distance d between
the conductive rail
cover 316 and a surface of the conductive rail 310).
[0029] In other implementations, one or more of the imaging device(s) 16
can be coupled
to a front or leading portion of the transport device 30 such that a field of
view of the imaging
device(s) 16 is directed in the same direction as the direction of travel of
the transport device
30. That is, the imaging device(s) 16 can capture images of a right-of-way of
the railroad.
State another way, the imaging device(s) 16 capture images of what a railroad
engineer would
see if operating the transport device 30. The right-of-way generally includes
the railroad track,
including its rails, cross-ties (a/k/a ties or sleepers), and ballast, and an
area on either side of
the rails (e.g., 2 feet, 5 feet, ten feet, etc.) For example, referring to
FIG. 4, in such
implementations, the imaging device(s) 16 can capture images of a railroad 400
including a
first running rail 410A, a second running rail 410B, cross-ties 412, ballast
414, and vegetation
416. As described in further detail herein, the imaging device(s) 16 can
capture images of the
railroad 400 like the one shown in FIG. 4, each of which is associated with a
location along the
railroad 400 and analyzed to determine a metric indicative of a condition of
the railroad 400
(e.g., a vegetation condition).
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[0030] The imaging device(s) 16 of the inspection system 10 (FIG. 1)
described herein can
include a visual imaging device (e.g., digital cameras, line-scan cameras,
frame cameras,
photodiodes, photomultiplier tube arrays, charge-coupled devices (CCDs)), a
thermal imaging
device (e.g., a thermographic camera configured to detect infrared radiation),
or both. The
visual imaging device is configured to generate visual image data (e.g., still
images, video
images, or both) that is reproducible as one or more visual images of the
transportation
pathway. Thermal imaging devices are configured to generate thermal image data
reproducible
as one or more thermal images of the transportation pathway. The amount of
infrared radiation
emitted from an object or surface increases with temperature, thus, the
detected infrared
radiation is indicative of a temperature. The thermal imaging device can
detect temperatures
ranging between, for example, about -50 C and about 2,000 C, 0 C to about
1,000 C, 20 C
to about 50 C, etc. In some implementations, a user can select the range of
temperatures that
are detected by the thermal imaging device. The thermal data obtained by the
thermal imaging
device is reproducible as one or more thermal images comprising a range of
colors, where each
color is indicative of a temperature and/or a range of temperatures. For
example, violet (which
has the lowest wavelength on the visible light spectrum) can be indicative of
the coldest
temperature in the temperature image and red (which has the highest wavelength
on the visible
light spectrum) can be indicative of the hottest temperature within the
thermal image, with
shades of violet, blue, green, yellow, orange, and red being indicative of
temperatures
therebetween. Generally, a user can select the range of colors and/or range of
temperatures
(e.g., the maximum and minimum temperatures) to make temperature differences
within the
thermal image more distinctive and readily apparent.
[0031] The sensors 18 of the inspection system 10 can include a variety
of sensors, such
as, for example, an optical sensor, a radar-based sensor, an RFID reader, or
any combination
thereof. The optical sensor is configured to detect movement of the transport
device 30 along
the transportation pathway and can include an optical encoder that detects
rotational position
changes and converts the angular position or motion to analog or digital
signal outputs. The
optical sensor can also determine a distance traveled by the transport device
30 from an initial
position. In some implementations, the processor 12 automatically actuates the
camera(s) 16
responsive to receiving signals or data from the optical sensor indicating
that the transport
device 30 is moving. The radar-based sensor can be a light detection and
ranging ("LIDAR")
sensor, a simultaneous localization and mapping ("SLAM") sensor, or both. The
LIDAR
sensor and/or SLAM sensor can be used to generate a three-dimensional
representation of the
transportation pathway and its surroundings, which can be stored in the memory
device 14
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and/or transmitted to a remote device via the communication module 22. The
RFID reader is
configured to automatically receive location information (e.g., in terms of
GPS coordinates, a
milepost or mile marker, landmarks, etc.) from RFID tags positioned on or
adjacent to the
transportation pathway (e.g., RFID tags coupled to a running rail of the
railroad). Thus, the
RFID reader can aid in determining the location of the transport device 30 if
the location cannot
be determined from the GPS module 20.
[0032] The GPS module 20 (e.g., sensor) of the inspection system 10 is
configured to
receive GPS signals for determining a location (e.g., latitude and longitude,
or other
coordinates) of the transport device 30. The current location of the transport
device 30 can be
expressed in terms of a distance along the railroad. For example, using the
GPS module 20, it
can be determined that the transport device 30 is located at meter 400 of the
transportation
pathway. Alternatively, the current location of the transport device 30 can be
expressed in
terms of a distance traveled from an initial position, as determined by the
GPS module 20.
[0033] The communication module 22 of the inspection system 10 is
configured to
communication with a communication module 42 of the remote system 40. Examples
of
communication interfaces for the communication module 22 include a wired
network interface
or a wireless network interface. As described herein, the communication module
22 can
transmit certain data in substantially real-time to the communication module
42 of the remote
system 40. The communication module 22 can include, for example, an antenna, a
receiver, a
transmitter, a transceiver, or any combination thereof
[0034] While the inspection system 10 is shown in FIG. 1 as including
all of the
components described herein, more or fewer components can be included in a
system. For
example, an alternative system (not shown) includes the processor 12, the
memory device 14,
the imaging device 16, the GPS module 20, and the communication module 22.
Thus, various
inspection systems can be formed using any portion of the components described
herein.
[0035] As shown in FIG. 1, unlike the inspection system 10, the remote
system 40 is not
coupled to the transport device 30. That is, the remote system 40 is not
physically located on
(e.g., coupled to) the transport device 30. The remote system 40 can be a
computer, a laptop,
a tablet, a smartphone, a server, or the like. Thus, a user can view the
information displayed
on the display device 44 without being physically located on the transport
device 30.
[0036] The display device 44 of the remote system 40 is a human-machine
interface (HMI)
including a graphical user interface (GUI) that can display images (e.g.,
still images, video
images, or both). As described in detail herein, the display device 44 can
display, for example,
graphs indicative of determined metrics. The display device 44 can be, for
example, a general
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or special purpose desktop computer, laptop computer, tablet computer,
smartphone, display
monitor, television, LED display, LCD display, or the like, or any combination
thereof. The
display device 44 can also include an input interface such as, for example, a
touchscreen or
touch-sensitive substrate, a mouse, a keyboard, or any sensor system
configured to sense inputs
made by a human user interacting with the display device 44. In some
implementations, the
inspection system 10 also includes a display device that is the same as, or
similar to, the display
device 44 described herein.
[0037] In addition to or in the alternative to the inspection system 10,
other inspection
systems can be coupled to the transport device 30 and used to implement the
methods described
herein. Exemplary alternative inspection systems are described in commonly
owned
International Patent Application Publication No. WO 2019/023658 entitled
"Systems and
Methods for Visualizing and Analyzing a Rail Surface," co-pending U.S. Patent
Application
No. 16/584,946 entitled "Systems and Methods for Analyzing Thermal Properties
of Railroad,"
and co-pending U.S. Patent Application No. 16/705,137 entitled "Systems and
Methods for
Analyzing a Rail, each which is hereby incorporated by reference herein in its
entirety. Each
of the elements or aspects of the inspection system 10 can be substituted or
modified with any
of the elements and/or functions described in these applications.
[0038] Further, in some implementations, the methods described herein can
be
implemented using two or more different inspection systems located on the same
transport
device. For example, in some implementations, a field of view of an imaging
device of a first
inspection system coupled to the transport device can be directed downwards
towards a top
surface of railroad (e.g., as shown in FIG. 2) and a field of view of an
imaging device of a
second inspection system can be directed forward or backwards relative to the
direction of
travel of the transport device (e.g., as shown in FIG. 4).
[0039] Referring to FIG. 5, a method 500 for analyzing one or more
conditions of a railroad
is illustrated. The railroad (e.g., subway, elevated train, high speed rail,
monorail, tram, etc.)
can include one or more running rails, one or more conductor rails, a
conductor rail cove, cross-
ties (a/k/a ties or sleepers), tie plates, ballast, fasteners, joint bars,
welds, switches, overhead
power lines, signs (e.g., mileposts, whistle boards, etc.), signals, or any
combination thereof.
The method 500 can be implemented using the system 10 (FIG. 1) described
herein and/or any
of the alternative inspection systems referenced herein.
[0040] Step 501 of the method 500 includes obtaining, using an imaging
device (e.g.,
imaging device(s) 16 of the inspection system 10 described herein) image data
reproducible as
a plurality of images of a portion of the railroad. Each of the plurality of
images are
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reproducible as an image of a portion of the railroad. The portion of the
railroad in each of the
images depends on the direction of the field of view of the imaging device(s)
of the inspection
system, as shown in FIGS. 2-4, for example.
[0041] During step 501, each of successive image is obtained at a
predetermined interval
from the prior image as the transport device 30 moves along the railroad. For
example, the
predetermined interval can be between about 6 inches and about 10 feet,
between about 1 foot
and about 5 feet, between about 2 feet and 3 feet, every foot, etc. That is,
the associated location
of each of the plurality of images obtained by the imaging device(s) 16 will
be spaced from the
associated locations of the prior and subsequently obtained images by the
predetermined
interval. The speed at which the imaging device(s) 16 obtain the plurality of
images of the
railroad can be adjusted based on the current speed of the transport device 30
(e.g., as
determined by the sensor(s) 18) such that images are obtained at the
predetermined interval
despite changes in the speed of the transport device 30.
[0042] Step 502 of the method 500 includes associating each of the images
obtained during
501 with a location. Locations on a railroad are often expressed in terms of a
distance rather
than absolute GPS coordinates. For example, locations can be defined by a
distance from the
beginning of the railroad (e.g., mile 1, mile 5.5, foot 1, foot 330, etc.) In
some implementations,
the GPS module 20 determines the GPS coordinates (e.g., latitude and
longitude) of the
transport device 30 when each image is obtained during step 501. These GPS
coordinates can
then be compared to a look-up table (e.g., stored in the memory device 14) to
determine the
location of the transport device 30 in terms of a distance as described above.
Alternatively,
once the location of a first image is determined, the locations of subsequent
images can be
determined based on the predetermined interval described above. Once
determined, each
image is associated with the location of the transport device 30 when the
image was obtained.
Thus, a first image will be associated with a first location and a second
image will be associated
with a second location that is spaced from the first location by the
predetermined interval.
[0043] Step 502 of the method 500 can occur simultaneously or nearly
simultaneously with
step 501. That is, each image obtained during step 501 can be associated with
the location of
transport device in substantially real-time (e.g., within 0.1 seconds, 0.5
seconds, 1 second, five
seconds, etc. after the image is obtained).
[0044] In some implementations, the method 500 optionally includes step
503, which
includes identifying one or more regions of interest within each of the images
obtained during
step 501. For example, referring to FIG. 4, a first region of interest 450 is
identified in the
image of the railroad. While shown as generally rectangular in FIG. 4, the
region(s) of interest
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can have any suitable size and can be defined by a square boundary, a circular
boundary, a
triangular boundary, a polygonal boundary, or any combination thereof. In
some
implementations, the region(s) of interest can be identified by a human user
on a first image,
and that region of interest is then applied to each subsequent image obtained
during step 501.
In other implementations, the region(s) of interest can be automatically
identified within each
of the images. For example, if the desired region of interest is a running
rail, the system 10 can
be configured to automatically identify the running rail within each of the
images as the region
of interest.
[0045] In
some implementations, as shown in FIG. 4, the region of interest can be
positioned at a predetermined distance (e.g., 2 feet, 5 feet, 10 feet, 50
feet, 100 feet, etc.) ahead
of the current location of the transport device. In such implementations, step
502 is modified
to account for this different in position. As described above, step 502
includes associating each
of the images with a location based on the current location of the transport
device. In the case
where the region of interest is a predetermined distance ahead or behind the
current location of
the transport device, step 502 adds or subtracts the predetermined distance
such that the image
is associated with the actual location of the image (and not the location of
the transport device).
For example, if it is determined that the transport device is at "100 feet"
and the predetermined
distance for the region of interest is 10 feet, then the image will be
associated with "110 feet."
[0046]
Step 504 of the method 500 includes analyzing the image data to determine
metrics
associated with one or more conditions of the railroad. That is, the system
analyzes each of
the plurality of images obtained during step 501 and determines a metric
indicative of a
condition. Each metric is associated with the location that is associated with
that image during
step 502. In such implementations in which the method 500 includes step 503,
step 504
includes analyzing the region(s) of interest within each image rather than the
entire image.
Exemplary metrics and conditions of the railroad are described in further
detail below.
[0047] As
described in further detail below in reference to each of the exemplary
conditions, step 504 can include identifying certain features or components of
the railroad that
are used to determine the metric at each associated location. To do so,
trained algorithms can
be applied to each of the images to identify the features or components. These
trained
algorithms can be machine learning algorithms, neutral networks, regression
models, etc. that
are trained using reference image data. For example, an algorithm can be
trained to identify
vegetation growing on or adjacent to the railroad in each of the images using
reference images
of railroads with and without vegetation.
CA 3070280 2020-01-29
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[0048]
Additionally, as described in further detail below, step 504 can include
determining
distances within each of the plurality of images. In some implementations, in
order to improve
the accuracy of these distance determinations, the method 500 can include a
calibration step
(not shown) prior to steps 501-507. In such implementations, the calibration
step includes
positioning a reference object within the field of view of the imaging device
and obtaining an
image containing the reference object. The reference object has one or more
known dimensions
(e.g., length, width, height). For example, the reference object can be
precisely machined to
further refine the known dimensions. The calibration step includes analyzing
the image to
determine a number of pixels corresponding to each known dimension of the
reference object.
Based on the known dimension(s) of the reference object and the number of
pixels, each pixel
within the image can be assigned a distance. For example, if a known distance
of 10 inches
corresponds to 1,000 pixels, each pixel can be assigned a distance of 0.01
inches. The distance
of each of pixel can then be used to determined unknown distances within the
image by
counting the number of pixels along the unknown distance and multiplying the
by distance
assigned to each pixel during the calibration step. Thus, unknown distances
can be determined
in subsequently obtained images from the same imaging device using the
information obtained
during the calibration step.
[0049]
Step 505 of the method 500 includes generating a graph indicative of the
condition
at each of the associated locations. Exemplary graphs are illustrated in FIG.
6 and are described
in further detail herein. Generally, each graph can be in the form of a one-
dimensional strip
chart and plots the determined metrics against the associated locations. That
is, a first axis
(e.g., x-axis) of the graph is indicative of each of the associated locations
along the railroad and
a second axis (e.g., y-axis) of the graph is indicative of a value of the
determined metrics.
[0050]
Step 506 of the method 500 includes transmitting the graph(s) generated during
step
506 from the transport device to a remote device or system. For example, as
shown in FIG. 1,
the inspection system 10 is located on the transport device 30. Thus, steps
501-504 can be
performed by the processor 12 and memory device 14 of the system 10 that are
located on the
transport device 30.
Step 506 includes transmitting the generated graph(s) via the
communication module 22 to the communication module 42 of the remote device
40.
[0051] By
transmitting data or information describing the graph(s) generated during step
505 (i.e., just that the graph can be reproduced and displayed on the display
device 44) instead
of all of the image data obtained during step 501, the transferred file size
can be greatly reduced
(e.g., several MB versus several GB). This allows for substantially real-time
transfer of data
CA 3070280 2020-01-29
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from the inspection system located on the transport device to a remote device
where it can be
viewed and analyzed in substantially real-time by a user.
[0052] Step 507 of the method 500 includes displaying the graph(s) on a
display device
(e.g., the display device 44 of the remote device 40) for viewing by a human
user. A user can
adjust the scale of the displayed first axis of the graph(s) to show, for
example, all of the
associated location (i.e., the entire length of the railroad that was
inspected) or a particular
range of locations (e.g., a particular 10-foot length, a particular 100-foot
length, etc.) Likewise,
a user can adjust the scale of the displayed second axis of the graph(s) to
show differences in
the values of the metrics at different locations with increasing or decreasing
granularity. A
user can also select individual points on the graph(s) (e.g., by clicking or
hovering over a
particular location) to display the value of the metric and associated
location for that point on
the graph.
[0053] In some implementations, the display device can further display
one or more
movable visual markers. For example, if a plurality of graphs is displayed
simultaneously (e.g.,
as shown in FIG. 6), a vertical marker can be overlaid on some or all of the
plurality of graphs
to allow a user to more easily compare the metric indicative of a first
condition at a first location
on a first graph with the metric indicative of a second condition the first
location on a second
graph.
Ballast Condition
[0054] In some implementations, the condition of the railroad is a
ballast condition. Ballast
typically comprises crushed stone and is generally used to keep the railroad
track in place, aid
in reducing or absorbing vibrations caused by railroad vehicles, aid in
draining water away
from the track, and aid in inhibiting or reducing vegetation growth. Referring
to FIG. 2, for
example, the ballast 214 typically has irregular shapes and sharp edges to aid
in securing the
cross-ties 212A and 212B.
[0055] Over time, railroad ballast may become "fouled" or degraded. This
can occur due
to the ballast being crushed from repeated loading, wear and tear, and other
disturbances. Mud
or other debris can also clog the ballast, reducing its ability to drain water
away from the track.
Fouled ballast also has a reduced ability to secure the cross-ties and prevent
lateral movement
due to its change in shape. As an example of the kind of differences between
fresh ballast and
fouled ballast, referring to FIG. 2, an area 216A of fresh ballast is shown
and an area 216B of
fouled ballast is shown. The fresh ballast area 216A has stones with irregular
shapes that are
CA 3070280 2020-01-29
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closely packed together, whereas the fouled ballast area 216B has stones with
more rounded
shapes and mud between some of the stones.
[0056] In some implementations, step 504 includes analyzing the plurality
of images
obtained during step 501 to determine a plurality of metrics indicative of a
ballast condition at
each of the associated locations. In such implementations, the metrics
determined in step 504
are based on a determined texture of the ballast in each image, a determined
color of the ballast
in each image, or both. As described above, rounder ballast stones are
indicative of fouled
ballast, whereas irregularly shaped stones with sharp edges are indicative of
fresh ballast.
Similarly, darker colors are indicative of mud or debris (i.e., fouled
ballast) whereas lighter
colors (e.g., gray) are indicative of fresh ballast. As described above, an
algorithm can be
trained using reference data to identify the texture and/or color of the
ballast to determine the
metric at each of the associated locations.
[0057] In some implementations, the metric indicative of the condition of
the ballast at
each location can be expressed as a number whose value is indicative of the
condition of the
ballast. For example, the number 0 can be used to indicate that there is no
fouled ballast at a
location and the number 1 can be used to indicate that there is heavily fouled
ballast at a
location, with numbers there between being indicative of levels of fouled
ballast between none
and heavily fouled.
[0058] During step 505 of the method, a graph indicative of the ballast
condition is
generated using the determined metrics from step 504. The graph is then
displayed during step
507 of the method. Referring to FIG. 6, graph 601 is an exemplary graph
indicative of the
condition of the ballast. As shown, each point along the x-axis is indicative
of the associated
location on the railroad and the value of the y-axis corresponds to the
determined metric at that
location. A user viewing graph 601 can easily and efficiently identify
locations or stretches of
the railroad where there is fouled ballast that requires maintenance (e.g.,
cleaning or
replacement of the ballast).
[0059] In other implementations, the determined metric indicative of the
condition of the
ballast can be binary. That is, the determined metric for each location can be
either a 1 or 0
based on the texture and/or color of the ballast. For example, if the texture
and/or color of the
ballast satisfy a certain threshold indicative of fouled ballast that is need
of
maintenance/replacement, the metric for that location is a 1 (fouled ballast),
whereas if the
texture and/or color do not satisfy that threshold are assigned a 0. In such
implementations,
the graph 601 will clearly show points where there is fouled ballast (i.e.,
where the determined
metric is a 1) and points where there is no fouled ballast (i.e., where the
determined metric is a
CA 3070280 2020-01-29
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0) to aid a user in quickly and efficiently identifying locations where
maintenance/repair is
suggested or required.
[0060] The method 500 described herein can be repeated one or more times
for the same
locations along the railroad. For example, the method 500 can be performed a
first time for a
segment of the railroad and then again at a second, later time for the same
segment of the
railroad. Both times, a graph indicative of a condition of the railroad is
generated. After the
method has been completed the second time, these two graphs can be displayed
simultaneously,
allowing a user to compare the graphs and identify any changes since the first
time the railroad
was inspected. In this manner, a plurality of graphs indicative of the same
condition at the
same locations can be displayed simultaneously (e.g., a first graph can be
displayed with a
second graph that was generated 6 months after the first graph and a third
graph that was
generated 3 months after the second graph was generated).
[0061] For example, if a user viewing the first graph determines that a
particular location
may need repair based on the determined metric at that location, and that
location is not repaired
prior to the generation of the second graph, the user can examine the second
graph to see
whether the condition at that location has worsened or improved. Similarly, in
another
example, if the user determined based on the first graph that a particular
location is in need of
repair and sent a maintenance crew only to find that there was actually no
need for a repair,
viewing the first and second graphs simultaneously can aid the user in
identifying this false
positive on the second graph and avoid repeating the same process. In this
manner, the user
can more efficiently allocate resources for the repair/maintenance of the
railroad.
[0062] In some implementations, a symbol (e.g., a shape, a letter, a
number, etc.) can be
overlaid on the displayed graph at locations where it is determined that the
associated metric
exceeds or falls below a predetermined threshold. This can aid a user
identifying location(s)
along the railroad track where attention is required.
Cross-tie Conditions
[0063] In some implementations, the condition of the railroad is a
condition of the cross-
ties of the railroad. As set forth below, different types of metrics that are
indicative of the
condition of the cross-ties can be determined.
[0064] First, the determined metrics can be a cross-tie grade. Cross-tie
grades are used by
railroads to indicate damage to individual cross-ties. For example, railroads
often use cross-
tie grades between 1-5, where a grade of 1 is indicative of a substantially
undamaged or quality
cross-tie, a grade of 5 is indicative of a heavily damage cross-tie, and
grades 2-4 are indicative
CA 3070280 2020-01-29
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of cross-ties having conditions between substantially undamaged and heavily
damaged. Many
railroads manually inspect each individual cross-tie to assign these grades.
In such
implementations, the metrics determined during step 504 are based on a
determined crack
density of the cross-tie at each associated location. Cracking on the cross-
tie is indicative of
the cross-tie grade: little or no cracking is indicative of a grade of 1,
whereas significant
cracking is indicative of a graph of 5. For example, referring to FIG. 2,
cross-tie 212C includes
cracks 220. These cracks 220 can be identified in each of the images obtained
during step 501
using the trained algorithms described herein.
[0065] The crack density can be determined based on the crack density of
one or more
regions of a cross-tie, such as, for example, a region that is generally in
the center of the cross-
tie (between the running rails) or a region that is directly adjacent to the
tie plate (described
further below). These regions can be identified as a region of interest during
step 503 described
above. The crack density within a region is defined as the area of all cracks
identified in the
region divided by the area of the region. Thus, during step 504, all cracks
are identified within
each region, the area of each crack is determined and then added together. By
then taking the
ratio of the total crack area to the total area of the region of the cracks,
the crack density of the
region is determined. The crack density metric can be a percentage between 0
and 100, or a
dimensionless value between 0 and 1.
[0066] Referring to FIG. 6, graph 602 is an exemplary graph that is
indicative of the cross-
tie grade metric. As shown, the graph 602 illustrates cross-tie grade
fluctuations and trends
along the length of the railroad (e.g., between grades of 1-5). Thus, a user
viewing the graph
602 can quickly and easily find locations where the cross-tie grade is
indicative of a damaged
cross-tie, and prioritize repair or replacement. In some implementations, only
grades above a
predetermined threshold are displayed on the graph 602. For example, a user
can choose to
display only grades that are 4 and above. This can aid a user identifying the
locations of cross-
ties that are in need of repair or replacement.
[0067] Second, the determined metrics can be a cross-tie plate-cutting
metric. Referring
to FIG. 2, each cross-tie 212 includes a pair of tie plates 230 that are
coupled to (e.g., via
fasteners) to the upper surface of the cross-tie. Each tie plate 230 has a
rail seat that aids in
securing the running rail to the cross-tie 212. Typically, the cross-ties 212
comprise wood and
the tie plates comprise metal (e.g., steel). As trains move along the track,
the train can cause
lateral movement of the running rails 210A and 210B, which is resisted by the
cross-tie 212
and cross-tie plate 230. Often, during such lateral movement, the cross-tie
212 (which is made
of metal) digs into the cross-tie 212, leaving an indentation, such as
indentation 232 shown in
CA 3070280 2020-01-29
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FIG. 2. This often referred to as "plate-cutting." This plate-cutting not only
damages the cross-
tie 212, but also serves an indicator of lateral movement of the rails that
may require remedial
action.
[0068] The plating-cutting metrics can be determined based on a distance
between an end
of the tie plate and the indentation in the cross-tie caused by movement of
the tie-plate. Larger
distances are indicative of larger indentations, which in turn are indicative
of damage to the
cross-tie and lateral movement of the rails. A distance of zero indicates that
there is no plate-
cutting. Thus, step 504 includes, for example, determining a distance between
the end of the
tie plate 230 and the indentation 232. As described above, a calibration step
can be initially
performed to aid in accurately determining this distance.
[0069] Referring to FIG. 6, graph 603 is an exemplary graph that is
indicative of a cross-
tie plate-cutting metric. As shown, the graph 603 illustrates plate-cutting
fluctuations and
trends along the length of the railroad. Thus, a user viewing the graph 603
can quickly and
easily find locations where there is significant plate-cutting requiring
repair or replacement.
[0070] Third, determined metrics can be a cross-tie spacing metric. Cross-
ties are typically
spaced from adjacent cross-ties by a predetermined distance. For example,
cross-ties are often
spaced apart from one another by 18 inches. In such implementations, the
determined metrics
are based ona determined distance between adjacent cross-ties. For example,
referring to FIG.
2, the distance between the first cross-tie 212A and the second cross-tie 212B
can be
determined by analyzing the image of the railroad.
[0071] Referring to FIG. 6, graph 604 is an exemplary graph that is
indicative of the cross-
tie spacing metrics at each of the associated locations. As shown, the graph
604 illustrates
fluctuations and trends in the spacing between cross-ties along the length of
the railroad. Thus,
a user viewing graph 604 can easily and efficiently identify locations where
the cross-tie
spacing does not conform to the railroad's predetermined spacing. To that end,
in some
implementation, only determined metrics that are predetermined threshold above
or below the
railroad's cross-tie spacing specification are displayed on the graph 604. For
example, if the
railroad specifies that the spacing between cross-ties should be 18 inches,
only determined
metrics that are 3 inches greater than or less than 18 inches are displayed
(i.e., cross-ties that
are too far apart or too close together). This aids a user in determining
location(s) of cross-ties
whose spacing may need to be readjusted to comply with the railroad standards
compared to
location(s) where the spacing is so close to the railroad's specification that
no action may be
required (or at least a lower priority can be assigned to those locations).
CA 3070280 2020-01-29
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[0072] Fourth, the determined metrics can be a cross-tie skew angle
metric. As shown in
FIG. 2 for example, the railroad running rails span parallel to one another
and the cross-ties
extend perpendicular to the running rails. It is desirable for each cross-tie
to be as close to
perpendicular to the running rails as possible. A large cross-tie skew angle
could also be
indicative of the fact that the cross-tie is not adequately secured to one or
more of the running
rails.
[0073] The cross-tie skew angle metric can be determined during stpe 504
by identifying
one or more of the running rails in each of the images (e.g., using the
trained algorithms
described herein). Once a path of one or both of the running rails is
identified, a reference line
perpendicular to that path can be generated. Next, the distance of each of the
cross-tie in the
image to the reference line can be determined. Then, the angle of the cross-
tie relative to the
reference line can be determined.
[0074] Referring to FIG. 6, graph 605 is an exemplary graph that is
indicative of the cross-
tie skew angle metrics at each of the associated locations. As shown, the
graph 605 illustrates
fluctuations and trends in the cross-tie skew angle along the length of the
railroad. Thus, a user
viewing graph 605 can easily and efficiently identify locations where the
cross-tie skew angle
is out of tolerance (e.g., more than +/- 5 degrees, more than +/- 10 degrees,
more than +/- 25
degrees, etc.) To that end, in some implementation, only determined metrics
that are
predetermined threshold above or below a skew angle of 0 are displayed on the
graph 605.
This aids a user in determining location(s) of cross-ties that may need
realignment to the rails.
Conductor Rail Cover Condition
[0075] In some implementations, the condition of the railroad is a
condition of the
conductor rail cover. As described above and referring to FIG. 3, a railroad
(e.g., subway or
elevated train) can include the conductor rail cover 316 to help protect the
electrified conductor
rail 310. The train receives power from the conductor rail 310 using a shoe
that contacts and
travels along the upper surface of the conductor rail 310. Thus, the distance
d between the
cover 316 and the rail 310 needs to be sufficient to allow the shoe to fit
between them.
[0076] In some implementations, step 504 includes analyzing the plurality
of images
obtained during step 501 to determine a plurality of metrics indicative of a
condition conductor
rail cover. The determined metric at each location can be determined, for
example, by
determining the distance d between the conductor rail 310 and the cover 316 at
each of the
associated locations.
CA 3070280 2020-01-29
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[0077] The determined metric can also be based on the railroad's
specified clearance
distance for the conductor rail and the cover. Thus, the metric can be
determined as a ratio of
the determined distance and the railroad's specified clearance, and expressed
as a percentage.
Alternatively, the metric can be binary, that is, a value of 1 indicates that
the determined
distance is less than the specified clearance and a value of 0 indicates that
the determined
distance is greater than the specified clearance.
[0078] During step 505 of the method, a graph indicative of the condition
of the cover is
generated using the determined metrics from step 504. The graph is then
displayed during step
507 of the method. Referring to FIG. 6, graph 606 is an exemplary graph
indicative of the
condition of the cover. As shown, each point along the x-axis is indicative of
the associated
location on the railroad and the value of the y-axis corresponds to the
determined metric at that
location. A user viewing graph 606 can easily and efficiently identify
locations or stretches of
the railroad where the distance between the cover and the conductor rail is
too close and may
need to be adjusted. In some implementations, the determined metric is only
displayed if it is
lower than a predefined threshold to aid a user in identifying locations where
repair may be
needed.
Drainage Condition
[0079] In some implementations, the condition of the railroad is a
drainage condition. The
presence of standing water on or adjacent to the railroad track can be
problematic for a number
of reasons. For example, standing water can damage the rails, cause the track
bed to sink, or
pose an electrocution risk in the case of an electrified conductor rail.
Standing water can also
freeze in cold conditions, damaging the track and/or causing a switch to seize
up. As described
herein, ballast is often used to aid in draining water away from the track.
However, some
railroads (e.g., subways) do not use ballast, and instead use what is often
referred to as a "slab
track" where the running rails are directly attached to a concrete slab. Slab
tracks often use
drains, which may become clogged over time. Thus, is it advantageous to
identify areas of
standing water to identify areas of the railroad where drainage problems can
be remediated.
[0080] In some implementations, step 504 includes analyzing the plurality
of images
obtained during step 501 to determine a plurality of metrics indicative of a
drainage condition.
The determined metric at each location can be determined, for example,
identifying areas of
standing water in which image or region(s) of interest. Areas of standing
water can be
identified using, for example, a trained algorithm or a thermal imaging
device. The thermal
imaging device can identify areas of standing water by identifying areas where
the temperature
CA 3070280 2020-01-29
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is lower than the surrounding areas and/or the ambient temperature, which is
indicative of
standing water. The determined metric at each location can be based on the
mere presence or
absence of standing water. That is, the metric is binary where a value of 1
means that standing
water is identified and a value of 0 means that no standing water was
identified. Alternatively,
the determined metric can be a ratio of the area of standing water versus the
total area of the
image or region of interest. This can aid a user in later identifying areas
where there is more
standing water than other areas and prioritize repairs.
[0081] During step 505 of the method, a graph indicative of the drainage
condition of the
railroad is generated using the determined metrics from step 504. The graph is
then displayed
during step 507 of the method. Referring to FIG. 6, graph 607 is an exemplary
graph indicative
of the drainage condition. As shown, each point along the x-axis is indicative
of the associated
location on the railroad and the value of the y-axis corresponds to the
determined metric at that
location. A user viewing graph 607 can easily and efficiently identify
locations or stretches of
the railroad where there is standing water.
Vegetation Condition
[0082] In some implementations, the condition of the railroad is a
vegetation condition.
The peripheries of a railroad are typically surrounded by vegetation (e.g.,
grass, weeds, brushes,
trees, etc.). Referring to FIG. 4, for example, vegetation 402 is present on
both sides of the
railroad track and some vegetation 402 is positioned directly adjacent to or
between the running
rails 210A and 210B. While the ballast generally aids in preventing vegetation
growth, as
shown, sometimes vegetation (e.g., weeds) can grow in the ballast.
[0083] The growth of this vegetation within the railroad right-of-way or
clearance envelope
of the train can be problematic. For one example, a tree branch growing onto
the right-of-way
could pose a safety hazard requiring trimming. Many railroads specify a
required distance
between the track and the surrounding vegetation and regularly trim the
vegetation to comply
with this distance.
[0084] In some implementations, step 504 includes analyzing the plurality
of images
obtained during step 501 to determine a plurality of metrics indicative of a
vegetation condition
at each of the associated locations. The vegetation metric at each location
can be determined,
for example, by identifying vegetation in each of the plurality of images
(e.g., using trained
algorithms) or regions(s) of interest within the images. A ratio of the total
area of vegetation
compared to the total area of the image or region(s) of interest can be
calculated to determine
the vegetation metric, which can be a percentage or dimensionless (between 0
and 1).
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[0085] Alternatively, step 504 can including analyzing the plurality of
images to determine
a distance between the ends of the cross-ties or the running rails and
vegetation growing on the
sides of the railroad. The vegetation metric can also be based on the
railroad's specified
clearance distance for the vegetation. Thus, the vegetation metric can be
determined as a ratio
of the determined distance and the railroad's specified clearance, and
expressed as a
percentage. This percentage is indicative of the relative compliance or non-
compliance of the
vegetation at a particular location is. For example, if the determined
distance is 200% of the
specified distance at location 1 and the determined distance is 105% of the
specified distance
at location, both are in compliance but location 2 is closer to being out of
compliance that
location 1. Alternatively, the vegetation metric can be binary, that is, a
value of 1 indicates
that the determined distance is greater than the specified clearance and a
value of 0 indicates
that the determined distance is less than the specified clearance.
[0086] During step 505 of the method, a graph indicative of the
vegetation condition is
generated using the determined metrics from step 504. The graph is then
displayed during step
507 of the method. Referring to FIG. 6, graph 608 is an exemplary graph
indicative of the
condition of the ballast. As shown, each point along the x-axis is indicative
of the associated
location on the railroad and the value of the y-axis corresponds to the
determined metric at that
location. A user viewing graph 608 can easily and efficiently identify
locations or stretches of
the railroad where there is vegetation that may need to be removed. In some
implementations,
the determined vegetation metric is only displayed if it exceeds a predefined
threshold to aid a
user in identifying locations where removal may be needed.
[0087] The systems and methods disclosed herein offer several advantages
compared to
prior inspection systems and methods. It would be extremely time consuming and
inefficient
for a user to view and analyze each of the plurality of obtained images (e.g.,
for several miles
of the railroad) to identify the various conditions described herein.
Similarly, given that these
obtained images often constitute a large data file (e.g., several gigabytes),
it is impractical or
difficult to transmit all of the images from the transport device to a remote
system or device
for analysis and/or viewing in real-time, especially in the case where the
transport device is an
autonomous vehicle. Indeed, transferring the obtained data is a critical
component in
implementing a fully autonomous inspection system. These prior systems also
suffer from
another drawback in that they typically only identify the presence or absence
of certain isolated
defects or features (e.g., cracks, missing track components, etc.) and do not
quantitatively
assess the types of conditions described herein and/or trends in the
conditions either at different
locations or different times for the same location.
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[0088] The systems and methods disclosed herein address these and other
problems by
analyzing the images in substantially real-time on the transport device to
determine metrics
that are indicative of various conditions, generating a graph that is
indicative of those various
conditions, and then transmitting the graph off of the transport device for
viewing or further
analysis by a human user. In other words, the graph(s) offer an intuitive
statistical summary
without the need for reprocessing all of the obtained image data.
[0089] As described herein, a user can adjust the scale of the displayed
graph to see
determined metrics for a desired length of the railroad track (e.g., a mile or
ten feet), bringing
the condition into focus as needed. This functionality allows a user to see,
for example, the
condition of individual cross-ties or a broader trend of the condition of
hundreds or thousands
of cross-ties. Further, a user can focus on the condition of the railroad at
specific locations
with precision.
[0090] While the system 10 and the method 500 have been generally
described herein in
reference to a railroad, it should be understood that any of the methods and
systems described
here can be implemented to analyze a roadway (e.g., highways, airport runways,
etc.) In such
implementations, a method that is the same as, or similar to, the method 500
(FIG. 5) can be
used to generate and display graphs indicative of various conditions of the
roadway that are the
same as, or similar to, the graphs and conditions of the railroad described
herein. For example,
the conditions can be a road surface condition where the determined metrics
are crack density
or missing portions of pavement. As another example, the condition can be a
thermal condition
of the roadway where the determined metrics include a maximum temperature, a
minimum
temperature, an average temperature, a temperature standard deviation, or any
combination
thereof. As yet another example, the condition can be a drainage condition
where the
determined metrics include the presence of standing water on the roadway.
Corrugation Condition
[0091] In some implementations, the condition of the railroad is a rail
corrugation
condition. Rail corrugation can develop over time from contact (e.g.,
friction) between the
rail(s) and the wheel set of the transport device 30. Wear caused by this
contact forms troughs
and crests in the rail, which may develop into rail corrugation. Rail
corrugation can be
represented in wavelength. Typically, heavily corrugated rails experience a
concave
deformation on surface of the rail at an interval (e.g., a 20 mm interval, a
200 mm interval,
etc.). Rail corrugation can decrease the service life of rails, and in some
cases require rail
replacement. Rail corrugation can also cause undesirable noise as the
transport device 30
moves along sections of the rail(s) with corrugation.
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[0092] In some implementations, step 504 includes analyzing the plurality
of images
obtained during step 501 to determine a plurality of metrics indicative of a
corrugation
condition at each of the associated locations along the railroad. The metric
at each location
can be determined, for example, by identifying corrugation in each of the
plurality of images
(e.g., using trained algorithms) or regions(s) of interest within the images.
In some
implementations, the metric indicative of the rail corrugation condition at
each location can be
expressed as a number or value that is indicative of the rail corrugation
condition. For example,
the number 0 can be used to indicate that there is no rail corrugation at a
first location and the
number 1 can be used to indicate that there is rail corrugation at a second
location.
[0093] In such implementations, during step 505 of the method, a graph
indicative of the
rail corrugation condition is generated using the determined metrics from step
504. The graph
is then displayed during step 507 of the method. Referring to FIG. 7, a first
graph 701 is an
exemplary graph indicative of the rail corrugation condition for a first rail
(e.g., the first running
rail 210A shown in FIG. 2) and a second graph 702 is an exemplary graph
indicate of the rail
corrugation condition for a second rail (e.g., the second running rail 210B
shown in FIG. 2).
As shown, each point along the x-axis is indicative of the associated location
on the railroad
and the value of the y-axis corresponds to the determined metric at that
location. A user
viewing graph 701 and/or graph 702 can easily and efficiently identify
locations or stretches
of the railroad where there is rail corrugation that may require rail
maintenance (e.g., rail
grinding) or replacement.
[0094] While the various distances described herein are expressed in
terms of miles, more
generally, any unit of distance (e.g., feet, meters, kilometers, etc.) or any
combination of units
of distance can be used in accordance with the systems and methods described
herein.
ALTERNATIVE IMPLEMENTATIONS
[0095] Alternative Implementation 1. A method for analyzing one or more
conditions
of a transportation pathway comprising: obtaining, using an imaging device of
an inspection
system, image data reproducible as a plurality of images of the transportation
pathway, each of
the plurality of images being reproducible as an image of a portion of the
transportation
pathway, each portion of the transportation pathway having an associated
location along a
length of the transportation pathway, analyzing, using one or more processors
of the inspection
system, the image data to determine a first plurality of metrics indicative of
a condition of the
transportation pathway at each of the associated locations, and generating a
first graph, using
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the determined first plurality of metrics, that is indicative of the condition
of the transportation
pathway at each of the associated locations.
[0096] Alternative Implementation 2. The
method according to alternative
implementation 1, wherein the analyzing includes identifying one or more
regions of interest
within each of the plurality of images.
[0097] Alternative Implementation 3. The
method according to alternative
implementation 2, wherein the analyzing includes analyzing the identified one
or more regions
of interest to determine the first plurality of metrics indicative of the
condition of the
transportation pathway at each of the associated locations.
[0098] Alternative Implementation 4. The
method according to alternative
implementation 2 or 3, wherein the region of interest is defined by a square
boundary, a circular
boundary, a triangular boundary, a polygonal boundary, or any combination
thereof.
[0099] Alternative Implementation 5. The method according to any one of
alternative
implementations 1-4, further comprising: analyzing, using at least one of the
one or more
processors, the image data to determine a second plurality of metrics
indicative of a second
condition of the transportation pathway at each of the associated locations;
and generating a
second graph, using the determined second plurality of metrics, that is
indicative of the second
condition of the transportation pathway at each of the associated locations.
[0100] Alternative Implementation 6. The
method according to alternative
implementation 5, further comprising displaying the first graph and the second
graph on a
display device at the same time.
[0101] Alternative Implementation 7. The method according to any one of
alternative
implementations 1-6, wherein the first graph includes a first axis indicative
of a value of the
determined first plurality of metrics and a second axis indicative of each of
the associated
locations along the transportation pathway.
[0102] Alternative Implementation 8. The method according to any one of
alternative
implementations 1-7, wherein the imaging device and the one or more processors
are coupled
to a transport device configured to move along the transportation pathway.
[0103] Alternative Implementation 9. The
method according to alternative
implementation 8, further comprising transmitting the generated first graph to
a remote device
that is not coupled to the transport device such that the first graph can be
displayed on the
remote device.
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[0104] Alternative Implementation 10. The method according to alternative
implementation 9, wherein the transmitting does not include transmitting the
image data to the
remote device.
[0105] Alternative Implementation 11. The method according to alternative
implementation 9, further comprising, subsequent to the transmitting, deleting
the image data.
[0106] Alternative Implementation 12. The method according any one of
alternative
implementations 1-11, wherein each of the associated locations along the
length of the
transportation pathway is a predetermined distance from a previous one of the
associated
locations along the transportation pathway.
[0107] Alternative Implementation 13. The method according to alternative
implementation 12, wherein the predetermined distance is between about 6
inches and about 3
feet.
[0108] Alternative Implementation 14. The method according to any one of
alternative
implementations 1-13, wherein the transportation pathway is a railroad
including one or more
running rails, one or more conductor rails, one or more conductor rail covers,
one or more
cross-ties, ballast, joints, welds, fasteners, one or more switches, or any
combination thereof.
[0109] Alternative Implementation 15. The method according to any one of
alternative
implementations 1-14, further comprising calibrating the inspection system
such that the one
or more processors are configured to determine one or more distances within
each of the
plurality of images.
[0110] Alternative Implementation 16. The method according to alternative
implementation 15, wherein the calibrating includes obtaining, from the
imaging device, a first
image including an object having a known length; analyzing the first image to
determine a
number of pixels associated with the known length of the object; and based on
the analyzing,
assigning a distance to each pixel in the first image.
[0111] Alternative Implementation 17. The method according to alternative
implementation 14, wherein the condition is a condition of the one or more
running rails, a
condition of the one or more conductor rails, a condition of the one or more
cross-ties, a
condition of the ballast, a condition of the joints, a condition of the welds,
a condition of the
fasteners, a condition of the one or more switches, or any combination
thereof.
[0112] Alternative Implementation 18. The method according to alternative
implementation 14, wherein the condition is a condition of the ballast and the
first plurality of
metrics is indicative of a texture of the ballast, a color of the ballast, or
both, at each of the
associated locations.
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[0113] Alternative Implementation 19. The method according to alternative
implementation 14, wherein the condition is a condition of the one or more
cross-ties and the
first plurality of metrics is indicative of a crack density of the one or more
cross-ties at each of
the associated locations.
[0114] Alternative Implementation 20. The method according to alternative
implementation 14, wherein the condition is a condition of the one or more
cross-ties and the
first plurality of metrics is indicative of a distance between adjacent ones
of the one or more
cross-ties at each of the associated locations.
[0115] Alternative Implementation 21. The method according to alternative
implementation 14, wherein the condition is a condition of the one or more
cross-ties and the
first plurality of metrics is indicative of a skew angle of the one or more
cross-ties at each of
the associated locations.
10116] Alternative Implementation 22. The method according to alternative
implementation 14, wherein the condition is a condition of the one or more
cross-ties and the
first plurality of metrics is indicative of a cross-tie plate-cutting at each
of the associated
locations.
[0117] Alternative Implementation 23. The method according to alternative
implementation 14, wherein the one or more conductor rail covers are
positioned adjacent to a
surface of the one or more conductor rails.
[0118] Alternative Implementation 24. The method according to alternative
implementation 23, wherein the condition is a condition of the one or more
conductor rail
covers and the first plurality of metrics is indicative of a distance between
the one or more
conductor rail covers and the surface of the one or more conductor rails at
each of the associated
locations.
[0119] Alternative Implementation 25. The method according to alternative
implementation 14, wherein the condition is a drainage condition of the
railroad and the first
plurality of metrics is indicative of the presence or absence of standing
water at each of the
associated locations.
[0120] Alternative Implementation 26. The method according to alternative
implementation 14, wherein the condition is a vegetation condition and the
first plurality of
metrics is indicative of a volume of vegetation within a right of way of the
railroad at each of
the associated locations.
[0121] Alternative Implementation 27. The method according to alternative
implementation 14, wherein the imaging device is a thermal imaging device and
the image data
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is thermal image data, and wherein the condition is a thermal condition of the
railroad and the
first plurality of metrics is indicative of a maximum temperature, a minimum
temperature, an
average temperature, a temperature standard deviation, or any combination
thereof at each of
the associated locations.
[0122] Alternative Implementation 28. The method according to any one of
alternative
implementations 1-27, wherein the transportation pathway is a roadway.
[0123] Alternative Implementation 29. , The method according to
alternative
implementation 28, wherein the condition is a surface condition of the
roadway, a drainage
condition of the roadway, a thermal condition of the roadway, or any
combination thereof.
[0124] Alternative Implementation 30. The method according to any one of
alternative
implementations 1-29, wherein the inspection system is coupled to a transport
device that is
configured to autonomously move along the transportation pathway.
[0125] Alternative Implementation 31. A method for analyzing ballast of a
railroad, the
method comprising: obtaining, using an imaging device of an inspection system,
image data
reproducible as a plurality of images of the railroad, each of the plurality
of images being
reproducible as an image of a portion of the railroad, each portion of the
railroad having an
associated location along a length of the railroad; determining a plurality of
metrics by
analyzing, using one or more processors of the inspection system, the image
data, the plurality
of metrics being indicative of a condition of the ballast of the railroad at
each of the associated
locations; and generating a graph using at least a portion of the determined
plurality of metrics
for visually illustrating the condition of the ballast of the railroad for at
least a portion of the
associated locations.
[0126] Alternative Implementation 32. The method according to alternative
implementation 31, wherein the determined plurality of metrics is based at
least in part on a
texture of the ballast, a color of the ballast, or both.
[0127] Alternative Implementation 33. The method according to any one of
alternative
implementations 31 or 32, wherein the graph is a two-dimensional line graph
and the method
further comprises displaying the two-dimensional line graph on a display
device.
[0128] Alternative Implementation 34. The method according to alternative
implementation 33, urther comprising, responsive to determining that a first
one of the plurality
of metrics at a first one of the associated locations is greater than a
predefined threshold,
overlaying a symbol on the two-dimensional line graph at a position
corresponding to the first
associated location.
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[0129] Alternative Implementation 35. The
method according to alternative
implementation 33, wherein the two-dimensional line graph visually illustrates
the condition
of the ballast at a first time, the method further comprising displaying a
second two-
dimensional line graph on the display device at the same time that the two-
dimensional line
graph is displayed on the display device, the second two-dimensional line
graph visually
illustrating the condition of the ballast at a second time that is different
than the first time.
[0130] Alternative Implementation 36. A method for analyzing cross-ties
of a railroad,
the method comprising: obtaining, using an imaging device of an inspection
system, image
data reproducible as a plurality of images of the railroad, each of the
plurality of images being
reproducible as an image of a portion the railroad, each portion of the
railroad having an
associated location along a length of the railroad; determining a plurality of
metrics by
analyzing, using one or more processors of the inspection system, the image
data, the plurality
of metrics being indicative of a condition of the cross-ties of the railroad
at each of the
associated locations; and generating a graph using at least a portion of the
determined plurality
of metrics for visually illustrating the condition of the cross-ties of the
railroad for at least a
portion of the associated locations.
[0131] Alternative Implementation 37. The method according to alternative
implementation 36, wherein the determined plurality of metrics is indicative
of a cross-tie grade
of each of the cross-ties.
[0132] Alternative Implementation 38. The method according alternative
implementation 37, wherein the analyzing includes determining a crack density
in one or more
portions of the cross-ties, and wherein the cross-tie grade is based on the
determined crack
density.
[0133] Alternative Implementation 39. The method according to alternative
implementation 38, wherein the one or more portions of each of the cross-ties
include a rail
seat portion of the cross-ties, a center portion of the cross-ties, or both.
[0134] Alternative Implementation 40. The method according to any one of
alternative
implementations 36-39, wherein the determined plurality of metrics is
indicative of a distance
between adjacent ones of the cross-ties at each of the associated locations.
[0135] Alternative Implementation 41. The method according to any one of
alternative
implementations 36-40, wherein the determined plurality of metrics is
indicative of a skew
angle of the cross-ties at each of the associated locations.
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[0136] Alternative Implementation 42. The method according to any one of
alternative
implementations 36-41, wherein the determined plurality of metrics is
indicative of a cross-tie
plate-cutting at each of the associated locations.
[0137] Alternative Implementation 43. A method for analyzing the presence
or absence
of one or more components of a railroad, the method comprising: obtaining,
using an imaging
device of an inspection system, image data reproducible as a plurality of
images of the railroad,
each of the plurality of images being reproducible as an image of a portion
the railroad, each
portion of the railroad having an associated location along a length of the
railroad; determining
a plurality of metrics by analyzing, using one or more processors of the
inspection system, the
image data, the plurality of metrics being indicative of the presence or
absence of a component
of the railroad at each of the associated locations; and generating a graph
using at least a portion
of the determined plurality of metrics for visually illustrating the presence
or absence of the
component of the railroad at each of the associated locations.
[0138] Alternative Implementation 44. The method according to alternative
implementation 43, wherein the component of the railroad is a joint, a weld, a
switch, or any
combination thereof.
[0139] Alternative Implementation 45. The method according to alternative
implementation 43 or 44, further comprising transmitting the generated graph
to a remote
device and displaying the graph on a display device of the remote device.
[0140] Alternative Implementation 46. The method according to alternative
implementation 45, wherein the graph includes a symbol for each of the
associated locations
where the corresponding one of the plurality of metrics is indicative of the
absence of the
railroad component.
[0141] Alternative Implementation 47. The
method according to alternative
implementation 45, wherein the graph includes a symbol for each of the
associated locations
where the corresponding one of the plurality of metrics is indicative of the
presence of the
railroad component.
[0142] Alternative Implementation 48. The method according to any one of
alternative
implementations 44-47, wherein the analyzing includes comparing each of the
plurality of
images to one or more reference images to identify the presence or absence of
the railroad
feature using one or more trained algorithms.
[0143] Alternative Implementation 49. A method for analyzing a conductive
rail cover
for one or more conductor rails of a railroad, the method comprising:
obtaining, using an
imaging device of an inspection system, image data reproducible as a plurality
of images of the
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railroad, each of the plurality of images being reproducible as an image of a
portion the railroad,
each portion of the railroad having an associated location along a length of
the railroad;
determining a plurality of metrics by analyzing, using one or more processors
of the inspection
system, the image data, the plurality of metrics being indicative of a
distance between a surface
of the one or more conductor rails and the conductor rail cover at each of the
associated
locations; and generating a graph using at least a portion of the determined
plurality of metrics
for visually illustrating the distance at each of the associated locations.
[0144] Alternative Implementation 50. The method according to alternative
implementation 49, wherein the surface of the one or more conductor rails is
an upper surface
of the one or more conductor rails.
[0145] Alternative Implementation 51. The
method according to alternative
implementation 49, wherein the surface of the one or more conductor rails is a
lower surface
of the one or more conductor rails.
[0146] Alternative Implementation 52. The method according to any one of
alternative
implementations 49-51, further comprising, responsive to determining that a
first one of the
plurality of metrics at a first one of the associated locations is greater
than a predefined
threshold, overlaying a symbol on the graph at a position corresponding to the
first associated
location.
[0147] Alternative Implementation 53. A method for analyzing drainage of
a railroad
track, the method comprising: obtaining, using an imaging device of an
inspection system,
image data reproducible as a plurality of images of the railroad track, each
of the plurality of
images being reproducible as an image of a portion the railroad track, each
portion of the
railroad having an associated location along a length of the railroad track;
determining a
plurality of metrics by analyzing, using one or more processors of the
inspection system, the
image data, the plurality of metrics being indicative of a drainage condition
of the railroad
track; and generating a graph using at least a portion of the determined
plurality of metrics for
visually illustrating the drainage condition at each of the associated
locations.
[0148] Alternative Implementation 54. The method according to alternative
implementation 53, wherein the analyzing includes identifying the presence or
absence of
standing water in each of the plurality of images of the railroad track.
[0149] Alternative Implementation 55. The method according to alternative
implementation 54, wherein the identifying includes determining an area of
standing water in
each of the plurality of images of the railroad track.
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[0150] Alternative Implementation 56. The method according to alternative
implementation 55, further comprising, responsive to identifying the presence
of standing
water at a first location of the associated locations, overlaying a symbol on
the graph at a
position corresponding to the first location.
[0151] Alternative Implementation 57. A method for analyzing vegetation
within a
right-of-way of a railroad, the method comprising: obtaining, using an imaging
device of an
inspection system, image data reproducible as a plurality of images of the
railroad, each of the
plurality of images being reproducible as an image of a portion the railroad,
each portion of the
railroad having an associated location along a length of the railroad;
determining a plurality of
metrics by analyzing, using one or more processors of the inspection system,
the image data,
the plurality of metrics being indicative of a condition of vegetation within
the right-of-way of
the railroad at each of the associated locations; and generating a graph using
at least a portion
of the determined plurality of metrics for visually illustrating the condition
of the vegetation
within the right-of-way of the railroad at each of the associated locations.
[0152] Alternative Implementation 58. The method according to alternative
implementation 57, wherein the analyzing includes identifying an area of
vegetation in each of
the plurality of images and the plurality of metrics is a percentage area of
vegetation within the
right-of-way at each of the associated location.
[0153] Alternative Implementation 59. The method according to alternative
implementation 58, wherein the identifying the area of vegetation in each of
the plurality of
images includes comparing each of the plurality of images to one or more
reference images
using one or more trained algorithms.
[0154] Alternative Implementation 60. The method according to alternative
implementation 59, wherein the one or more trained algorithms includes a
machine learning
algorithm.
[0155] Alternative Implementation 61. A method for analyzing one or more
conditions
of a transportation pathway, the method comprising: obtaining, during a first
inspection of the
transportation pathway at a first time image data reproducible as a plurality
of images of the
transportation pathway, each of the plurality of images being reproducible as
an image of a
portion of the transportation pathway, each portion of the transportation
pathway having an
associated location along a length of the transportation pathway; determining
a first plurality
of metrics by analyzing the image data, the first plurality of metrics being
indicative of a first
condition of the transportation pathway at each of the associated locations at
the first time;
displaying a first graph, using at least a portion of the determined first
plurality of metrics, to
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visually illustrate the first condition of the transportation pathway at each
of the associated
locations at the first time; and displaying a second graph, using at least a
portion of a second
plurality of metrics, to visually illustrate the first condition of the
transportation pathway at
each of the associated locations at a second time that is different from the
first time.
[0156] Alternative Implementation 62. A method for analyzing one or
more conditions
of a railroad, the method comprising: obtaining, using an imaging device,
image data
reproducible as a plurality of images of the railroad, each of the plurality
of images being
reproducible as an image of a portion of the railroad, each portion of the
railroad having an
associated location along a length of the railroad; analyzing, using one or
more processors, the
image data to determine (i) a first plurality of metrics indicative of a first
condition of the
railroad at each of the associated locations and (ii) a second plurality of
metrics indicative of a
second condition of the railroad at each of the associated locations;
displaying, on a display
= device, a first graph, using at least a portion of the first plurality of
metrics, to visually illustrate
the first condition of the railroad; and displaying, on the display device, a
second graph, using
at least a portion of the second plurality of metrics, to visually illustrate
the second condition
of the railroad, the second graph being displayed adjacent to the first graph
on the display
device at the same time.
[0157] Alternative Implementation 63. The method according to
alternative
implementation 62, wherein the imaging device and the one or more processors
are coupled to
a transport device configured to move along the railroad and the display
device is not coupled
to the transport device.
[0158] Alternative Implementation 64. The method according to
alternative
implementation 62, further comprising transmitting, using a communication
module coupled
to the transport device, information associated with the first graph and the
second graph to a
remote system.
[0159] Alternative Implementation 65. The method according to
alternative
implementation 64, wherein the transmitted information does not include the
image data.
[0160] Alternative Implementation 66. A system for inspecting a
transportation
pathway, the system comprising: an imaging device; and a memory device storing
machine
readable instructions configured to be executed by one or more processors to
cause the system
to: cause the imaging device to generate first image data reproducible as a
first image of a first
portion of the transportation pathway at a first location; analyze the first
image data; determine,
based on the analysis of the first image data, a first metric indicative of a
condition for the first
portion of the transportation pathway; cause the imaging device to generate
second image data
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reproducible as a second image of a second portion of the transportation
pathway at a second
location that is a predetermined distance from the first location; analyze the
second image data;
determine, based on the analysis of the second image data, a second metric
indicative of the
condition for the second portion of the transportation pathway; and generate a
graph, using the
determined first metric and the determined second metric, the generated graph
for visually
illustrating the condition at the first location and the second location.
[0161] Alternative Implementation 67. The system according to alternative
implementation 66, wherein the transportation pathway is a railroad including
a railroad track
having one or more rails, one or more cross-ties, ballast, joints, welds,
fasteners, a switch, or
any combination thereof.
[0162] Alternative Implementation 68. The
system according to alternative
implementation 67, wherein the condition is a condition of the ballast of the
railroad track.
[0163] Alternative Implementation 69. The
system according to alternative
implementation 68, wherein the first metric and second metric are indicative
of a texture of the
ballast, a color of the ballast, or both.
[0164] Alternative Implementation 70. The system according to alternative
implementation 67, wherein the condition is a condition of the one or more
cross-ties of the
railroad track.
[0165] Alternative Implementation 71. The system according to alternative
implementation 70, wherein the first metric and the second metric are
indicative of a cross-tie
grade.
[0166] Alternative Implementation 72. The system according to alternative
implementation 71, wherein the first metric and the second metric indicative
of the cross-tie
grade are determined based on a crack density of one or more portions of a
cross-tie.
[0167] Alternative Implementation 73. The system according to alternative
implementation 72, wherein the one or more portions of the cross-tie include a
first portion that
is generally adjacent to a rail seat, a second portion that is generally
equidistance between a
first rail and a second rail, or both.
[0168] Alternative Implementation 74. The system according to
implementation 67,
wherein the first metric and the second metric are indicative of cross-tie
plate-cutting.
[0169] Alternative Implementation 75. The
system according to alternative
implementation 74, wherein the first metric and the second metric indicative
of the cross-tie
plate-cutting are determined based on a width of an indentation in the one or
more cross-ties.
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[0170] Alternative Implementation 76. The
system according to alternative
implementation 67, wherein the first metric and the second metric are
indicative of a cross-tie
spacing distance.
[0171] Alternative Implementation 77. The
system according to alternative
implementation 67, wherein the first metric and the second metric are
indicative of a cross-tie
skew angle.
[0172] Alternative Implementation 78. The system according to alternative
implementation 67, wherein the condition is a condition of the joints and
welds of the railroad
track.
[0173] Alternative Implementation 79. The
system according to alternative
implementation 78, wherein the first metric and the second metric are
indicative of the presence
or absence of joints, welds, or both, on the one or more rails of the railroad
track at the first
location and the second location.
[0174] Alternative Implementation 80. The
system according to alternative
implementation 67, wherein the condition is a condition of the switch of the
railroad track.
[0175] Alternative Implementation 81. The system according to alternative
implementation 80, wherein the first metric and the second metric are
indicative of the presence
or absence of the switch at the first location and the second location.
[0176] Alternative Implementation 82. The system according to any one of
alternative
implementations 66-82, wherein the one or more rails of the railroad track
include a first
running rail, a second running rail, and a conductor rail and the railroad
includes a conductor
rail cover configured to at least partially overlie a surface of the conductor
rail.
[0177] Alternative Implementation 83. The
system according to alternative
implementation 82, wherein the first metric and the second metric are
indicative of a distance
between the cover and a surface of the conductor rail at the first location
and the second
location.
[0178] Alternative Implementation 84. The
system according to alternative
implementation 66, wherein the transportation pathway is a railroad including
a railroad track
having one or more rails and crossties.
[0179] Alternative Implementation 85. The
system according to alternative
implementation 84, wherein the condition is a drainage condition of the
railroad track.
[0180] Alternative Implementation 86. The system according to alternative
implementation 85, wherein the first metric and the second metric are
indicative of the presence
or absence of standing water at the first location and the second location.
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[0181] Alternative Implementation 87. The
system according to alternative
implementation 67, wherein the condition is a condition of vegetation on or
adjacent to the
railroad track.
[0182] Alternative Implementation 88. The system according to alternative
implementation 87, wherein the first metric and the second metric are
indicative of a volume
of the vegetation on or adjacent to the railroad track at the first location
and the second location.
[0183] Alternative Implementation 89. The
system according to alternative
implementation 67, wherein the imaging device is a thermal imaging device
configured to
generate thermal image data reproducible as thermal images of the portions of
the
transportation pathway and the condition is a thermal condition of the
railroad track.
[0184] Alternative Implementation 90. The system according to alternative
implementation 89, wherein the first metric and the second metric are
indicative of an average
temperature, a maximum temperature, a minimum temperature, a standard
deviation of
temperature, or any combination therefor, for at least a portion of the
railroad track at the first
location and the second location.
[0185] Alternative Implementation 91. The system according to
implementation 66,
wherein the transportation pathway is a roadway.
[0186] Alternative Implementation 92. The system according to alternative
implementation 91, wherein the condition is a condition of a surface of the
roadway.
[0187] Alternative Implementation 93. The system according to alternative
implementation 92, wherein the first metric and the second metric are
indicative of a crack
density of the surface of the roadway at the first location and the second
location.
[0188] Alternative Implementation 94. The system according to any one of
alternative
implementations 91-93, wherein the imaging device is a thermal imaging device
configured to
generate thermal image data reproducible as thermal images of the portions of
the
transportation pathway and the condition is a thermal condition of the
roadway.
[0189] Alternative Implementation 95. The system according to alternative
implementation 94, wherein the first metric and the second metric are
indicative of an average
temperature, a maximum temperature, a minimum temperature, a standard
deviation of
temperature, or any combination therefor, for at least a portion of the
railroad track at the first
location and the second location.
[0190] Alternative Implementation 96. The
system according to alternative
implementation 91, wherein the condition is a drainage condition of the
roadway.
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[0191] Alternative Implementation 97. The
system according to alternative
implementation 96, wherein the first metric and the second metric are
indicative of the presence
or absence of standing water on the roadway at the first location and the
second location.
[0192] Alternative Implementation 98. The system according to any one of
alternative
implementations 66-97, wherein the imaging device is coupled to a transport
device configured
to move along the transportation pathway.
[0193] Alternative Implementation 99. The system according to alternative
implementation 98, wherein the memory device and one or more processors are
coupled to the
transport device.
[0194] Alternative Implementation 100. The system according to
alternative
implementation 99, further comprising a communication module configured to
transmit the
generated graph to a remote device that is not coupled to the transport
device.
[0195] Alternative Implementation 101. The system according to
alternative
implementation 100, wherein the remote device is configured to display the
generated graph.
[0196] Alternative Implementation 102. The
system according to alternative
implementation 101, wherein the remote device is configured to display a
second graph
indicative of a third metric and a fourth metric, the third metric and the
fourth metric being
indicative of the condition of the first portion and the second portion of the
transportation
pathway and having been determined prior to the first metric and the second
metric.
[0197] One or more elements or aspects or steps, or any portion(s)
thereof, from one or
more of any of Alternative Implementations 1-102 above can be combined with
one or more
elements or aspects or steps, or any portion(s) thereof, from one or more of
any of the other
Alternative Implementations 1-102 or combinations thereof, to form one or more
additional
implementations and/or claims of the present disclosure.
[0198] While the present disclosure has been described with reference to
one or more
particular embodiments or implementations, those skilled in the art will
recognize that many
changes may be made thereto without departing from the spirit and scope of the
present
disclosure. Each of these implementations and obvious variations thereof is
contemplated as
falling within the spirit and scope of the present disclosure. It is also
contemplated that
additional implementations according to aspects of the present disclosure may
combine any
number of features from any of the implementations described herein.
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