Note: Descriptions are shown in the official language in which they were submitted.
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SYSTEM AND METHOD FOR MONITORING THE OPERATION OF ONE OR
MORE TRUCKS
DESCRIPTION
PRIOR RELATED APPLICATIONS
[0001] This application claims priority to US Serial No.
63/140.504, filed
January 22, 2021, incorporated by reference in its entirety for all purposes.
TECHNICAL FIELD
[0002] The invention relates to a system and method for
monitoring the operation of one
or more trucks at worksites, preferably one or more mining trucks at mine
sites.
[0003] The main object of the invention is to provide an online
platform that addresses
underproduction and inefficiencies at mine sites, implementing Industry 4.0
concepts to
include mine analytics and performance monitoring on mining trucks,
particularly on its
hoppers or trays. The main approach of this invention is to be able to monitor
the truck's
performance in terms of payload, cycle efficiency, availability, fuel
consumption, wear
analysis, fatigue analysis, asset tracking and speed control. For this
purpose, the highest
technology in terms of sensors, data transmission and analytics is
implemented.
BACKGROUND
[0004] Monitoring and controlling operations at worksites are
major objects of most
industries. Characterizing a productive operation through data collection can
result in early
identification of operational issues that reduce operating efficiency. In
addition, such
characterization can help identify possible operational improvements that
lower operating
costs, reduce operational risks, and/or increase worksite productivity. This
is particularly true
in the monitoring and control of a fleet of trucks, which operation has a high
potential for
implementing improvements in terms of truck routes, fuel efficiency, fleet
availability,
operation cycles, maintenance and payload capacity.
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[0005] Different monitoring and controlling solutions have been
implemented for the
management of truck fleets, mostly directed to monitor key truck operational
parameters to
improve the availability of the fleet. For instance, publication
US2019019167A1 discloses a
solution for the monitoring, control and optimization of a waste pickup
service based on a
fleet of trucks. Then, the publication discloses a waste measurement device
directed to obtain
waste volume data and use the truck capacity as key input for managing the
fleet, including
data about traveled distance, fuel expenses, emissions and working hours.
[0006] The implementation of the solution above is relatively
simple since the key
operational parameter is limited to the waste volume being transported by the
trucks, for
which volume sensors are implemented. However, said approach is not direct for
managing
more complex operations like payload transport at mine sites, wherein multiple
key
operational parameters are involved in the operation of the truck fleet.
10007] The operation of mining trucks is ruled by several key
parameters not only related
to payload, operation cycles and fuel consumption, but also to wear and
fatigue due to harsh
mine site operation conditions. Different monitoring and controlling solutions
have been
implemented for improving operation of mine trucks, mostly directed to
identifying specific
operation issues and proposing solutions to the same. For instance,
publication US6157889A
discloses a load distribution system for mine trucks, wherein weight sensors
coupled to the
bed of a truck measure the weight applied to each tire strut as the truck is
being loaded. Then,
the exact position of the center of gravity of the load in the truck's bed can
be calculated and
displayed on a monitor relative to a target position deemed optimal for
uniform weight
distribution. Based on this information, the operator of the loading machine
can complete the
loading operation in such a way as to shift the center of gravity toward the
chosen target
position.
[0008] The implementation of the solution above solves the
problem of payload
distribution, which improves operation efficiency and reduces safety risks
regarding unevenly
distributed payloads. However, said solution only considers one operational
parameter of the
truck, and is not useful for determining a complete overview of the whole
truck operation,
from its loading point to its discharge point. Besides, specific solutions
like the one in
publication US6157889A requires special equipment that, in most cases, should
be included
when manufacturing the truck components. Therefore, are difficult to implement
in existing
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operations, resulting not only in increasing manufacturing costs, but also in
productivity
inefficiencies due to high downtimes.
[0009] Other many solutions, like the one in publication
US2015285650A1, are directed
to monitoring and controlling the navigation of mining vehicles, providing
directions on the
best route to follow by the operators based on the location of the vehicle.
Said solutions can
be implemented using location sensors like GPS, and are intended to improve
fleet
management in terms of geolocation. However, no other operational parameters
are
considered, and a holistic overview of the truck operation cannot be
determined.
[0010] Based on the above, there is a need to provide a
monitoring solution able to
provide a complete overview of the truck operation, considering multiple
operational
parameters directed to a holistic management of truck fleets. In addition, the
solution should
be assembled easily, preferably in the form of a kit, reducing installation
downtimes, and
substantially reducing the implementation of special equipment. The main
difference between
this invention and current solutions is that it does not depend on the OEM
(Original
Equipment Manufacturer) of the truck because it does not intervene the truck
at any point, not
requiring authorization from a third party to implement it. This means that
the invention is
proposed in the form of an enclosure, which can be installed in the truck's
dump body with
minor interventions. This allows for a quick installation, reducing the
downtime of the trucks
when the system is being installed and during maintenance processes. Besides,
the enclosure
being installed in the dump body of trucks is independent of the type of
truck, meaning that it
is possible to adapt the same to any truck in the industry. The enclosure can
be presented as
part of a kit, with minimum intervention to existing trucks or its dump
bodies.
[0011] It is another object of the invention to implement a
sensor for metal/uncrushable
early detection. At the moment, the mining industry is highly impacted by
metal fragments
that breach the operation when the ore is being processed. The invention can
implement metal
detector sensors and/or cameras in order to identify these metal fragments
before it damages
the crusher or the conveyor belt, affecting the entire operation.
[0012] The applicant is developing first-class technology for
cycle monitoring and timing
improvement. In this regard, one of the key characteristics of the invention
is its online
technology and real time data processing, using 3G, 4G or 5G. Non-invasive
sensors monitor
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the performance of the truck in real time. giving relevant information for
improving the
productivity of the operations.
SUMMARY OF INVENTION
[0013] As indicated above, the invention is related to a system
and method for
monitoring the operation of one or more trucks at worksites, preferably one or
more mining
trucks at mine sites. For performing said monitoring, the system and method
arc implemented
in a hardware-software environment, directed to monitor, process and display
data, including
calculation of specific operational parameters.
[0014] According to its general aspects, the hardware related
features of the invention are
directed to monitor operational data of the trucks or trays, storing said
operational data and
communicating said data to an online platform. Alternatively, the hardware
related features
can also preprocess the operational data, e.g. calculating operational
parameters from raw
operational data, debugging the operational data or preparing tables or graphs
with the
captured data, providing pre-processed operational data to one or more users.
[0015] Then, the monitored, stored and/or preprocessed
operational data is communicated
to an online platform for processing, obtaining operation information and
statistics of all the
trucks at one or more worksites. The online platform is software-implemented,
providing
different tools for analyzing the operational data according to preferences of
end users.
Besides, this platform provides a clear visualization of the data through a
user interface,
which can be displayed in different user equipment.
[0016] According to a main embodiment of the invention a system
for monitoring the
operation of one or more trucks comprises:
at least one truck with a tray;
an inertial measurement unit (IMU) arranged on a first surface of the tray,
configured to characterize the movement of the tray, obtaining real-time
movement data
of the tray;
a location sensor configured to track the location of the tray, obtaining real-
time
location data of the tray;
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at least one processing unit configured to process the movement and location
data,
obtaining processed data;
at least one server configured to receive the real-time movement and location
data
and/or the processed data;
at least one communication unit configured to communicate the real-time
movement and location data and/or the processed data from the at least one
truck to the
at least one server; and
a display interface configured to display the real-time movement and location
data
and/or the processed data to a user.
[0017] The at least one server is further configured to obtain
truck operation information
from the real-time movement and location data and/or the processed data, said
operation
information including at least one or a combination of truck status
information, truck payload
information, truck travel information, truck efficiency information, truck
cycle information
and truck availability information. The display interface is further
configured to display said
truck operation information.
[0018] According to a main embodiment of the invention a method
for monitoring the
operation of one or more trucks comprises:
providing at least one truck with a tray;
characterizing the movement of the tray by means of an inertial measurement
unit
(IMU) arranged on a first surface of the tray, obtaining real-time movement
data of the
tray;
tracking the location of the tray by means of a location sensor, obtaining
real-time
location data of the tray;
processing the movement and location data by means of at least one processing
unit, obtaining processed data;
receiving the real-time movement and location data and/or the processed data
by
at least one server, wherein said real-time movement and location data and/or
the
processed data is communicated from the at least one truck to the at least one
server by
at least one communication unit;
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obtaining, by the at least one server, truck operation information from the
real-
time movement and location data and/or the processed data, said operation
information
including at least one or a combination of truck status information, truck
payload
information, truck travel information, truck efficiency information, truck
cycle
information and truck availability information; and
displaying the real-time movement and location data and/or the processed data
to
a user by means of a display interface, wherein the display interface also
displays said
truck operation information.
[0019] According to a main embodiment of the invention a
monitoring kit for monitoring
the operation of a truck comprises:
at least one processing unit;
an inertial measurement unit (1MU) in communication with the at least one
processing unit;
a location sensor in communication with the at least one processing unit;
at least one communication unit in communication with the at least one
processing
unit;
at least one data storage unit in communication with the at least one
processing
unit; and
at least one power source.
[0020] The at least one processing unit, the IMU, a first part
of the location sensor, a first
part of the at least one communication unit, the at least one data storage and
the at least one
power source are housed within a Sensor Signal Processing Cabinet or
enclosure, said
enclosure being arranged on the first surface of the tray.
[0021] An embodiment of the invention further comprises at least
one power source that
can be configured to energize the IMU, the location sensor, the at least one
processing unit
and/or the at least one communication unit. When the invention is presented as
a kit, the at
least one power source can be comprised in said kit, within the enclosure.
[0022] According to an embodiment of the invention at least part
of the location sensor
and/or at least part of the at least one communication unit can be arranged on
a second surface
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of the tray, facing sky. When the invention is presented as a kit, first parts
of the location
sensor and communication unit are comprised by the kit, within the enclosure.
Then, a second
part of the location sensor and a second part of the at least one
communication unit are
arranged on a second surface of the tray, facing sky, wherein said second
parts are in data
communication with said first parts wirelessly or by means of a data cable.
Commonly, said
second parts are one or more antennas of the location sensor and communication
unit.
Preferably, all the components of the location sensor and communication unit,
including the
antennas, are housed inside the enclosure, which is possible when said
arrangement does not
jeopardize the location and communication data acquisition by the system.
[0023] According to an embodiment of the invention, the IMU, the
at least one
processing unit and the at least one power source can be housed within the
enclosure, said
enclosure being arranged on the first surface of the tray. The enclosure can
comprise at least
one data storage unit in communication with the at least one processing unit.
[0024] According to an embodiment of the invention, the system
and kit can further
comprise wear sensors arranged on wear surfaces of the tray. Said wear
sensors, forming a
wear sensor arrangement, can be configured to obtain real-time thickness data
of the tray,
which can be used by the at least one server to calculate and display tray
lifetime information.
The wear sensors can be in data communication with the at least one processor
of the system
and kit by means of data cables or wireles sly. The data cables can be
embedded in the
structure of the tray, inside columns/beams, or wired over said structure.
[0025] Alternatively, the wear sensors are implemented in fixing
elements used for fixing
one or more plates fat ______ lung the tray or for fixing one or more wear
plates to working surfaces
of the tray. Said wear sensors can form a mesh of wear sensors communicating
the thickness
data of the tray wireles sly through the mesh, from multiple sensing points to
the at least one
processing unit. According to this embodiment each wear sensor is capable of
sensing
thickness data and communicating the same to neighboring wear sensors,
propagating the
thickness data of each sensor through the mesh and towards the at least one
processing unit,
for further processing.
[0026] According to an embodiment of the invention, the system
and kit further comprise
weight sensors arranged on predetermined locations of the tray and/or of a
chassis of the at
least one truck. Said weight sensors are configured to obtain real-time weight
data of the
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payload in the tray. The weight sensors, the IMU and the location sensor
comprise a cycle
timing sensor arrangement. Similarly, to the wear sensors, the weight sensors
can be in data
communication with the at least one processor of the system and kit by means
of data cables
or wirelessly. The data cables can be embedded in the structure of the tray
and/or truck
chassis, inside columns/beams, or wired over said structures.
[0027] The cycle timing sensor arrangement obtains real-time
movement, location and
weight data of the tray. Said data is communicated to the at least one
processor and/or to the
at least one server to identify and count timing of the truck on each of the
following operation
cycle stages:
- queuing to load stage, defined as a stage in which a truck is waiting for
being
loaded;
loading stage, defined as a stage in which a truck is being loaded at a load
site;
- to dump or returning stage, defined as a stage in which a truck is loaded
and in
movement from the load site to a dump site;
queuing to dump stage, defined as a stage in which a truck is waiting for
dumping
the load;
- dumping stage, defined as a stage in which a truck is dumping the load at
the
dump site;
- to load stage, defined as a stage in which a truck is returning to the
load site from
the dump site;
- fueling stage, defined as a stage in which a truck is being fueled;
- other stages, defined as a stage that is not part of an operation cycle,
like a service
stage.
[0028] Then, the cycle timing sensor arrangement can obtain a
time it takes a truck to
complete the above operation cycle stages, allowing complete characterization
of the
operation cycle.
[0029] According to the embodiment above, the queuing to load
stage is identified when:
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the real-time movement data from the IMU indicates that a speed of the tray is
approximately zero, that a tilt angle of the tray is approximately zero and
that an
acceleration/impact indicator of the tray is approximately zero;
the real-time location data from the location sensor indicates that the tray
is within
an area near the load site;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is approximately zero; and
a previous operation cycle stage was the to load stage.
[0030] According to the embodiment above, the loading stage is
identified when:
the real-time movement data from the IMU indicates that a speed of the tray is
approximately zero, that a tilt angle of the tray is approximately zero and
that an
acceleration/impact indicator of the tray is positive;
the real-time location data from the location sensor indicates that the tray
is within
an area near the load site;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is increasing; and
a previous operation cycle stage was the to load stage or queuing to load
stage.
[0031[ According to the embodiment above, the to dump or
returning stage is identified
when:
the real-time movement data from the IMU indicates that a speed of the tray is
above zero, that a tilt angle of the tray is approximately zero and that an
acceleration/impact indicator of the tray is zero or positive;
the real-time location data from the location sensor indicates that the tray
is within
a road area;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is above zero; and
a previous operation cycle stage was the loading stage.
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[0032] According to the embodiment above, the queuing to dump
stage is identified
when:
the real-time movement data from the IMU indicates that a speed of the tray is
approximately zero, that a tilt angle of the tray is approximately zero and
that an
acceleration/impact indicator of the tray is approximately zero or negative;
the real-time location data from the location sensor indicates that the tray
is within
an area near the dump site;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is above zero; and
a previous operation cycle stage was the to dump or returning stage.
[0033] According to the embodiment above, the dumping stage is
identified when:
the real-time movement data from the IMU indicates that a speed of the tray is
approximately zero, that a tilt angle of the tray is above zero and that an
acceleration/impact indicator of the tray is positive;
the real-time location data from the location sensor indicates that the tray
is within
an area near the dump site;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is decreasing; and
a previous operation cycle stage was the queuing to dump or to dump stage.
[0034] According to the embodiment above, the to load stage is
identified when:
the real-time movement data from the IMU indicates that a speed of the tray is
above zero, that a tilt angle of the tray is approximately zero and that an
acceleration/impact indicator of the tray is zero or positive;
the real-time location data from the location sensor indicates that the tray
is within
the road area;
the real-time weight data from the weight sensors indicates that the weight of
the
payload is approximately zero; and
a previous operation cycle stage was the dumping stage.
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[0035] According to the embodiment above, the fueling stage is
identified when:
- the real-time movement data from the IMU indicates that a speed of the
tray is
approximately zero, and that an acceleration/impact indicator of the tray is
approximately zero; and
- the real-time location data shows that the truck is within a fueling
area.
[0036] Finally, the at least one communication unit is
configured to communicate all data
to a communication system of the at least one truck and/or to wireles sly
communicate said
data to the at least one server, for instance, by means of a wireless network.
BRIEF DEFINITION OF THE FIGURES
[0037] As part of the present invention, the following
representative figures thereof are
presented, which teach preferred embodiments of the invention and, therefore,
should not be
considered as limiting the definition of the claimed matter.
Fig. 1 is a graph of the Truck Operation Cycle from sensor data, according to
an
embodiment of the invention.
Fig. 2a and Fig. 2b are a representation of the payload sensor arrangement
with pressure
sensors in the tire struts, according to an embodiment of the invention.
Fig. 3a is a representation of wire loops inside wear bolts or cylinders
installed on
critical locations of the tray, according to an embodiment of the invention.
Fig. 3b is a representation of an internal perspective of a wear bolt or
cylinder
implementing the tray wear sensor, according to a first embodiment of the
invention.
Fig. 3c is a representation of an external perspective of wear bolts or
cylinder
implementing the tray wear sensor. according to the first embodiment of the
invention.
Fig. 3d is an exploded view of a wear cylinder implementing the tray wear
sensor,
according to a second embodiment of the invention.
Fig. 3e is a cross-section view of the wear cylinder of Fig. 3d.
Fig. 3f is a perspective view of a wear cylinder implementing the tray wear
sensor,
according to a third embodiment of the invention.
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Fig. 3g is a cross-section view of the wear cylinder of Fig. 3f.
Fig. 3h is a perspective view of a wear cylinder implementing the tray wear
sensor,
according to a fourth embodiment of the invention.
Fig. 3i is a cross-section view of the wear cylinder of Fig. 3h.
Fig. 3j is a perspective view of a wear cylinder implementing the tray wear
sensor,
according to a fifth embodiment of the invention.
Fig. 3k is a first cross-section view of the wear cylinder of Fig. 3j.
Fig. 31 is a second cross-section view of the wear cylinder of Fig. 3j.
Fig. 3m is a view of the installation system of the wear cylinder of Fig. 3j
on the tray.
Fig. 4 is a representation of the location of the location sensor (GPS) and
communication antenna on a surface of the tray, according to an embodiment of
the
invention.
Fig. 5 is a representation of the Sensor Signal Processing Cabinet or
enclosure,
according to an embodiment of the invention.
Fig. 6a is a representation of the location of the enclosure at the front of
the tray,
according to an embodiment of the invention.
Fig. 6b is a representation of the location of the enclosure at the front of
the tray
according to Fig. 6a.
Fig. 7 is a scheme of the system arrangement on the tray (enclosure and
external
sensor/devices), according to an embodiment of the invention.
Fig. 8 is a representation of the system arrangement on the cabin of the
truck, according
to an embodiment of the invention.
Fig. 9 is a representation of the system arrangement with the integration of
the wear
cylinder and the mesh network system.
DEFINITION OF THE PREFERRED EMBODIMENTS
[0038] The preferred embodiments of the invention can be defined
in connection to its
hardware and software related features as described below.
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Hardware related features
Sensors
[0039] The invention implements different types of sensors, with
specific aims. The main
sensors being installed are described below, as implemented in connection to a
single truck or
tray.
Cycle Timing Sensors
[0040] The named Cycle Timing Sensors are a set of sensors
directed to identify the truck
operation cycle stages. These sensors count timing of the truck on each of the
following
stages: returning or to dump, dumping, queuing to dump, to load, loading,
queuing to load,
fueling, and other unknown activity. The cycle timing sensors provide the time
it takes a truck
to complete the loading, travelling and dumping processes, allowing complete
characterization of the operation cycle.
[0041] The cycle timing sensors are formed by a set of sensors
allowing timing
calculation, such as:
Location sensor: This sensor is for tracking the tray location, for instance
tracking
its latitude and longitude, and its speed with standard GPS accuracy. Jointly
with
the online platform, the data from the location sensor is able to provide 3ll
visualization of tray data overlaid on aerial view of the worksite or mine
site.
According to a preferred embodiment, the sensor for this purpose is a GNSS
(Global Navigation Satellite System).
IMU (Inertial Measurement Unit): This sensor is for tracking impacts in the
tray,
inclination angle, acceleration and speed. The 1MU uses a combination of
accelerometers, gyroscopes, and sometimes magnetometers, directed to obtain
data with the aim of characterize the movement of the tray.
Pressure/weight sensor: This sensor is for tracking the weight of the payload
or
changes in the weight of the tray.
[0042] The logic behind the procedure or algorithm for
determining the stage of the
operation cycle can be visualized in connection to Fig. 1, showing the output
of the sensors, or
sensor data, in connection to the main stages of the truck operation cycle. As
can be seen in
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Fig. 1, the output of the sensors is a clear indication operational changes,
which in
combination allow for clear determination of the cycle stages identified
above.
[0043] In addition, the data in Table 1 also shows how the data
from the sensors can be
used for determining the stage of the operation cycle.
CiEigniginiMME
000toloVEMEREM trgaionoms000a Lo weight TJ1t ng1em]mm'eQE
Queue to load Loading area .=0 .=0 .=0 .=0 To
load
Loading Loading area .=0 .++ .=0 .++ To
load or Queue to load
To dump or returning Road .>0 .>0 .=0 .++ Loading
Queue to dump Dump area .=0 .>0 .=0 .=0 To dump or
returning
Dumping Dump area .=0 .>0 .++ Queue to
dump or To dump
To load Road .>0 .=0 .=0 .++ Dumping
Service Service area Any Any Any Any Any
Table 1: Truck Operation Cycle from sensor data.
[0044] For example, to determine when the truck is being loaded,
the sensors will have to
show: speed is zero ("0") or approximately 0, weight is increasing and is
greater than 0, angle
of the tray is 0 and the tray is receiving impacts, though is increasing or
positive. Through
these four insights can be concluded that the truck is being loaded. It is
important to note that
some variations can be occur in connection to the data in Table 1. For
instance, the
accelerations/impact can output zero (or negative) or positive during the to
load task, to dump
or returning tasks, being expected to receive a continuous oscillation between
zero and
positive reads during said tasks, due to the smoothness or roughness of the
truck path. Said
oscillations are not affecting the determination of the task due to the other
data received from
the sensors (location, speed, payload weight, title angle and previous task).
Payload Weight Sensor
[0045] For measuring the weight of the payload, two approaches
are proposed:
Pressure Sensors installed in the tire struts of the truck. Pressure sensors
can
measure the pressure inside the struts, which are connected to specific
locations of
the chassis of the truck and have a response to the weight of the payload.
Different
approaches can be implemented to calculate payload weight from various
algorithms. For instance, pressure measurements from sensors in the tire
struts can
be converted to payload weight from a correlation between pressure inside each
strut and weight of the payload being loaded into the tray. Fig. 2a and 2b
show a
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scheme of the payload sensor arrangement, with pressure sensors in the struts
that
are connected to the chassis, according to an embodiment of the invention.
As shown in Fig. 2b, the Pressure Sensors can be located in connection to each
tire strut of the truck and, by means of testing the response of the struts
during
loading operations, a correlation between payload weight and pressure
measurement in each strut can be defined. Said correlation is useful for
obtaining
payload weight data in trucks with similar strut configuration, meaning that
different correlations may be required depending on the model of the truck.
When applicable, depending on the configuration of the truck and the struts,
pressure sensors in two struts of the back tires of the truck are implemented,
and
the gathered pressure data is communicated to a Sensor Signal Processing
Cabinet
or Enclosure, by means of sensor connection cables or Bluetooth where
possible,
as represented in Fig. 2a. From said cabinet or enclosure, the data can be
processed to obtain payload weight and/or transmitted wirelessly to further
processing.
Data transmission from the Dump Truck Payload Meter. When the trucks are
already having a Payload Meter, the information can be obtained from the truck
through a wired connected device or wirelessly, if applicable.
Wear and Fatigue Analysis Sensor
[0046] For obtaining data directed to a mechanical wear or
fatigue analysis of the trays, a
wear sensor is proposed.
[0047] The tray wear sensor measures the thickness of the wear
floor plate, using said
information to determine the end of the tray life. In particular, the proposed
approach
measures the reduction on the tray thickness over time to schedule tray
replacement on time,
implementing wear bolts or cylinders with wire loops to be electronically
monitored. For
instance, Fig. 3a, Fig. 3b and Fig. 3c show how the proposed approach works,
implementing
special wear cylinders including an electrical circuit inside, wherein the
wear of the plates will
break the electrical circuit indicating wear depth and though predict
beforehand when plates
should be replaced.
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[0048] According to an embodiment of the invention, the wear
sensor considers the
design and fabrication of a device directly installed in the tray, with an
independent power
system through batteries and independent communication that goes directly to
the enclosure.
The evaluation of the thickness of the tray will be carried out every lmm of
wear, with a
range of up to 50mm.
[0049] The communication of the thickness data to the enclosure
can be over a mesh
network system through wireless communication, like Bluetooth, between the
sensors itself
and a mesh gateway included in the system of the invention.
[0050] According to an embodiment, the wear sensors can
implement a special
configuration as shown in Figs. 3b-1. Figs. 3b and 3c are representing an
embodiment using
wired sensors, which are connected to the processing unit by means of data
cable. Said cables
are also energizing the sensors from a power source in the enclosure.
Alternatively, the wear
sensors can communicate thickness data wirelessly, and can be presented as
independent units
with its own power source, as shown in Figs. 3d-1. According to said wireless
embodiment of
the wear sensors, the same can be distributed in multiple measurement points
of the tray
forming the mesh network system or sensor mesh, communicating the thickness
data to the
processing unit through said mesh. This approach allows using low energy
wireless network,
allowing that the data from the furthest wear sensor reach the data processing
unit with low
energy consumption. This means that the data of the furthest sensors reach the
processing unit
by a wireless communication with the closest sensors. As indicated above, the
mesh network
system contemplates that each wear sensor is a mesh node and includes a mesh
gateway that
can be implemented in the enclosure as another component of the system of the
invention, for
retrieving the wear data from each node.
[0051] Figs. 3d and 3e represent a first embodiment of the
wireless wear sensor, in which
power, communication and sensing units are attached to an existing wired
sensing wear
cylinder, converting the same to wireless sensing wear cylinder. The power
unit and the
communication unit, jointly with related circuitry, are housed in a wear
sensor enclosure that
can be fixed to the head of the existing sensing wear cylinder, having a lid
for accessing to the
components without requiring removal of the wear cylinder. Fig. 3e shows a
cross-sectional
view of this embodiment, wherein the wear cylinder is fixing a wear plate to a
surface of the
tray.
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[0052] Figs. 3f and 3g represent a second embodiment of the
wireless wear sensor,
similar to the first embodiment but in which the wear sensor enclosure housing
the power
unit, communication unit and related circuitry is integrated to the head of
the wear bolt or
cylinder.
[0053] Figs. 3h and 3i represent a third embodiment of the
wireless wear sensor, similar
to the second embodiment but in which the wear sensor enclosure housing the
power unit,
communication unit and related circuitry is the head of the wear bolt or
cylinder.
[0054] Finally, Figs. 3j, 3k, 31 and 3m represent a fourth
embodiment of the wireless
wear sensor, in which the wear sensor is not implemented in an existing bolt,
being a
completely different sensing unit that includes a first portion and a second
portion. The first
portion is an elongated probe that projects towards the wear plates, having
the sensing means
within. The second portion is a probe head that houses the power unit,
communication unit
and related circuitry. Said second portion is fixed to the tray from outside,
by common fixing
bolts, and the first portion is inserted into a perforation of said tray and
related wear plate. Fig.
3m shows how the wear sensor can be installed on the tray.
Other Sensors
[0055] The invention also contemplates other sensors per truck
or tray, for instance:
Time sensor: the aim of this sensor is to precisely record all operational
data that
is collected against time, and to collect raw data that will enable the
classification
of time, location, speed, vibration, acceleration, angle and height. Allows
for
accurate time stamping of all collected data from each of the trucks. The
system is
able to time stamp all incoming data and system actions which allows for
accurate
data comparisons to be made across all devices. Allows for global pinpointing
when events occur on the data.
Uncrushable/metal detector: at least one metal detector sensor and/or one or
more
cameras can be implemented in order to detect uncrushable or metal fragments
inside the tray (payload). If those fragments get to the crusher and/or
conveyor
belt, may affect and stop the entire operation. Uncrushablametal detectors
(sensors and/or cameras) are installed facing the load area of the tray, at
one or
more heights, detecting metal uncrushable within the load.
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Fuel sensor: the invention is also able to obtain fuel level data from the
truck's
fuel sensor or from a specific sensor arranged in connection to fuel tanks.
Sensor Signal Processing Cabinet or Enclosure
[0056] All the information obtained from the sensors is gathered
in a special device
named Sensor Signal Processing Cabinet or enclosure. Said enclosure is
strategically fixed to
the tray of each truck, housing most of the sensors and connected to all the
sensors at the tray.
In this regard, some sensors/devices may be required to be external to the
enclosure. For
instance, the location sensor (e.g., GPS) and the communication antenna may
need to be
installed at the top of the tray, facing the sky, preferably at the top of the
tray canopy for
improving location accuracy and communication fidelity (see Fig. 4). Said
sensor/devices are
named external sensor/devices. Other main sensors, like the IMU, can be
implemented inside
the enclosure, which is presented as a hardcase housing enclosing electronics
and circuitry
(see Fig. 5). However, current technologies in location and communication
antennas allow
implementing the location sensor and/or the communication antenna inside the
enclosure,
without substantially jeopardizing the operation of the system.
[0057] It should be understood that other additional sensors,
like the weight sensor,
uncrushable/metal detector and fuel sensor, need to be installed in clear
connection to the
measured object, meaning that said sensors will be most likely installed
remote from the
enclosure, like the GPS if needed, falling within the definition of external
sensor/devices. In
said cases, the information from/to the external sensors/devices travels to
the enclosure via
small and non-invasive cables, from the different components/locations of the
tray in which
the sensors/devices are installed. Said cables may be integrated into the
structure of the tray,
encased by the same structure, but the most preferred option is to facilitate
its installation over
the external surface of the tray, allowing integration of the invention to
existing trays and
reducing the required intervention. In this regard, when wireless sensors can
be used, the same
are implemented in data wireless communication with the enclosure.
[0058] The enclosure can be located at the front wall of the
tray, where possible, for ease
of access. For instance, Fig. 6a and Fig. 6b show a preferred location of the
enclosure at the
front side of the tray, facing the driver access of the truck.
[0059] The information processed in the enclosure can be sent
directly to the online
platform or through an internal system on the cabin of the truck via
Bluetooth, were further
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data collection, storage and/or processing can be made, as well as data
displaying for the
driver's consideration.
[0060] The configuration of the enclosure with internal
sensor/devices and the
arrangement of the external sensor/devices in data communication with the
enclosure, being
self-energized, conforms a monitoring kit that can be easily installed in
existing trays without
interference to the operation. If data cables are used for said data
communication, the same
can be arranged in the external structure of the tray and/or truck chassis,
with minor structural
interference that does not affect the operation of the tray.
System arrangement
[0061] Regarding the arrangement of the system of the invention,
it is important to note
that the information is transmitted from the sensors to the cloud or online
platform via the
system arrangement on the tray, which main components are the enclosure and
sensors, as
shown in Fig. 7. According to an embodiment of the invention, internal
components like a
processor, an IMU, a data storage and a power supply (battery pack), as
represented in Fig. 7,
are housed inside the enclosure, jointly with circuitry related to data
communication (3G/4G,
Bluetooth), positioning (GPS), and power management, among others. According
to the
embodiment of Fig. 7, external components are represented by dots in the
perimeter of Fig. 7,
arranged outside the enclosure to send/receive data from/to the enclosure. For
instance, the
external components in the represented embodiment are: an antenna arranged to
send/receive
data to/from the online platform, establishing data communication within the
enclosure and
the online platform; an antenna arranged to receive location related data
(GPS); and/or one or
more external sensors, located in the truck but remote the enclosure, for
instance, the fuel
and/or payload related sensors. It is important to note that, thanks to
current technologies,
some location and communication antennas can be arranged inside the enclosure
without
jeopardizing the reception of location and communication data, meaning that
most of the
components of the system can be arranged inside the enclosure.
[0062] According to the preferred embodiment, all the information gathered in
the enclosure
can be sent via Bluetooth to the internal system arrangement installed in the
cabin of the
truck. From the cabin, the information can be uploaded to the cloud for
analysis through the
online platform, as show in Fig. 8. As in Fig. 7, Fig. 8 also shows dots at
the perimeter of the
figure, representing external existing components that would be related to the
internal system
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arrangement installed in the cabin of the truck. According to an embodiment of
the invention,
said external existing components might be a truck computer, providing truck
information to
the payload system; and/or a truck alternator/generator/batteries, as power
source to the
components of the invention.
[0063] Finally, Fig. 9 shows an embodiment of the system arrangement according
to Fig. 7
and integrating the wear cylinder and the mesh network system. As shown in
Fig. 9, a Mesh
Gateway can be implemented as an internal component within the enclosure, said
gateway in
wireless communication with remote sensors that need to be arranged at
different points of the
tray, like the wear sensors that are also nodes of the mesh network system.
Alternatively,
other remote sensors with similar communication capabilities can be
implemented, like the
pressure sensors for obtaining weight data and/or uncrushable/metal detectors.
Software related features
[0064] The aim of the software related features is to create a
platform to gather all the
information mentioned above, for instance, using a WEB service Front-end with
HMI (human
machine interface) approach.
[0065] The main features of this component of the invention are:
- Data storage: all data is remotely communicated using a cloud server from
the pit,
in real time. The purpose of the data storage is to store data to upload to
the cloud
while disconnected, as well as ensure record keeping in case upload is not
possible.
- Cloud storage: this feature has the ability to automatically count the
number of
loads/cycles and report results. The cloud server will be used to transmit all
the
data obtained from the sensors and transmit it to the display interface.
Different
algorithms process the data to generate relevant information.
- Report Generator: Generate reports for evaluating different operational
parameters. For instance, issue operational reports on each one of the trays
with
the following information: GPS location, cycle status, speed and inclination,
payload, efficiency, availability, real time monitor, impact loads, time
between
loads, fuel usage, wear analysis, and impacts on stress zones
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Display Interface: Display all available tray sensor information in online
tools that
can be accessed anywhere. Besides, the display interface can be useful for
visualizing the location of tray using a map visualization platform like
Google
Maps. For instance, the display interface can:
= Show the last route of the truck and display speed of tray around the
mine and tray cycle times.
= Provide 3D visualization of the tray data overlaid on an aerial view of
the mine.
= Generate different statistics and parameters that will enable the mine
operator to evaluate performance over time. The system will offer
comparisons between one truck over time, different trucks at the same
time, and different trucks over time, grouped by fleet, loading zones,
truck routes, time shift, among others.
[0066] Besides, the online platform has the following
capabilities: support integration
with a third-party data, support all trays sending data to the cloud, can use
the processor on
the phone/desktop/laptop, generate reports from any device for qualified
operators, provide
manual data analysis via a data processor like Excel, automatically classify
data collected
from the tray into cycle times, and remotely communicate with cloud server
from the pit in
real time.
[0067] As indicated above, the display interface is the key
component for user
interaction, providing access to the online platform and to the gathered
information for the
end users, mine site operators an any other relevant user duly registered for
access.
[0068] Using the online platform, users are able to select a
truck, display current location
and previous path on an open map. Also, users are able to see graphs and
information
displaying wear, payload, cycle timing, fuel consumption, efficiency,
availability, speed,
fueling, wear and fatigue, impacts on stress zones, and all data provided by
the sensors. In
addition, the online platform is also capable of comparing data in connection
to the truck's
performance, driver's performance or full mine site, as well as by specific
data requirements
such as payload comparison by truck. timing comparison by truck, fuel
consumption and any
combinations from the above.
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[0069] Upon mine site requests, the online platfoint can be
connected to the mine site
previous hardware system, meaning that the software is independent from the
hardware and it
can be used with any sensors or data recollection system.
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