Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
CAApphcanon
WakesRet 11985/00011
1 METHODS AND SYSTEMS FOR ESTIMATING THE HARDNESS OF A ROCK MASS
2 RELATED APPLICATIONS
3 100011 The present application claims priority to U.S. Provisional
Application No.
4 62/359,577, filed July 7, 2016, the entire contents of which is hereby
incorporated by reference.
BACKGROUND
6 100021 Embodiments of the present invention relate to mining
machines and, more
7 particularly, relate to blasthole drill rigs and estimating the hardness
of a rock mass during
8 operation of a blasthole drill rig.
9 SUMMARY
[0003] In surface and underground mining operations, explosives are
generally used to break
11 a rock mass so that the rock mass may be excavated and transported
within a mine for
12 stockpiling, minerai processing, and the like. In particular, one or
more blasthole drill rigs
13 ("drills") are used to drill a pattern of holes into a rock mass for
receiving explosives. The
14 design of the blast (in example, the geometric arrangement of holes and
the explosive energy
delivered to each hole) defines the distribution of fragmentation of the rock
mass (for example,
16 the size of the individual rock particles). Uniform fragmentation
results in consistent digging
17 and minerai processing operations. Conversely, non-uniform fragmentation
generally results in
18 inefficiencies in digging and transportation as well as additional cost
and downtime in minerai
19 processing operations. Poor and inconsistent fragmentation may occur
when a uniform blasting
energy is applied to a rock mass with varying hardness and other non-
homogeneous structures.
21 Because the material properties of a rock mass are generally not
uniform, the blast is ideally
22 designed to match the explosive energy applied to each three-dimensional
location of the rock
23 mass with the energy required to achieve uniform fragmentation. By
estimating the rock mass
24 hardness across various three-dimensional locations, the blast design
may be improved to match
the explosive energy applied at different three-dimensional locations of the
rock mass with the
26 explosive energy required to achieve a uniform fragmentation.
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1 100041 Current blasting practices combine sparse geological survey
data (for example, core
2 samples) as well as heuristic data from previous nearby mining activities
(for example, other
3 blasting and drilling activities) to identify blasting requirements (for
example, explosive energy
4 requirements). The resolution of the geological survey data is limited by
the cost and time
required for core sampling. As a result, blasting is often planned based on
the average material
6 properties across a large mass of rock. Variations in the material
lithology (for example,
7 hardness, faulting, boundaries between material types, and the like) are
flot accurately known and
8 may result in variability in the achieved fragmentation.
9 [0005] It is possible to use operational monitoring and other data
from a drill control system
to derive drilling performance metrics (for example, the specific energy of
drilling). Such
11 drilling performance metrics can be used to inform blasting activities.
However, data acquired
12 from the drill, and hence the measurement of quantities like specific
energy, may be corrupted.
13 For example, this data may be corrupted by the dynamics of the machine,
the coniplex
14 interaction between the machine and the rock mass, and an operational
state of the machine (for
example, more energy is required to drill with a worn bit than with a new
bit). As such, direct
16 measurement of the rock properties is difficult without considering the
performance of the
17 machine over time and without knowledge of the operational state of the
machine (for example,
18 replacement of a drill bit).
19 10006] It should also be noted that the blast design for a hole
may need to be identified
within a short time of the hole being drilled to charge the hole with
explosives quickly to
21 minimize material cave-in. As such, optimizations across a full drill
pattern prior to blast design
22 are not viable as a single batch computation.
23 100071 Accordingly, embodiments provide methods and systems for
estimating a hardness of
24 a rock mass during operation of an industrial machine, such as a
blasthole drill rig. For example,
one embodiment provides a method that includes receiving, with an electronic
processor, a rock
26 mass model and receiving live drilling data from the industrial machine.
The method also
27 includes updating the rock mass model based on the live drilling data
and estimating a drilling
28 index for a hole based on the updated rock mass model. The method also
includes setting a
29 blasting parameter for the hole based on the estimated drilling index.
Optionally, the method
2
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1 may also include receiving live loading data, such as from of least one
shovel, wheel loader,
2 excavator, another type of mining machine, and the like (collectively
referred to herein as a
3 "secondary industrial machine") collecting the fragmented rock, and
updating, with the
4 electronic processor, the updated rock mass model based on the live
loading data.
[0008] Another embodiment provides a system for estimating a hardness of a
rock mass
6 during operation of an industrial machine. The system includes an
electronic processor
7 configured to receive a rock mass model and to receive live drilling data
from the industrial
8 machine. The electronic processor is also configured to update the rock
mass model based on
9 the live drilling data and to estimate a drilling index for a hole based
on the updated rock mass
model. After estimating a drilling index for the hole, the electronic
processor is also configured
11 to set a blasting parameter for the hole based on the estimated drilling
index.
12 [0009] Yet another embodiment provides a non-transitory, computer-
readable medium
13 including instructions that, when executed by an electronic processor,
cause the electronic
14 processor to execute a set of functions. The set of functions includes
receiving a rock mass
model and receiving live drilling data from the industrial machine. The set of
functions also
16 includes updating the rock mass model based on the live drilling data
and estimating a drilling
17 index for a hole based on the updated rock mass model. The set of
functions also includes
18 setting a blasting parameter for the hole based on the estimated
drilling index.
19 [0010] Other aspects of the invention will become apparent by
consideration of the detailed
description and accompanying drawings.
21 BRIEF DESCRIPTION OF THE DRAWINGS
22 [0011] FIG. 1 is a side view of a blasthole drill rig according to
one embodiment.
23 [0012] FIG. 2 schematically illustrates a system for estimating a
hardness of a rock mass
24 drilled by the blasthole drill of FIG. 1.
[0013] FIG. 3 schematically illustrates a controller of the system of FIG.
2.
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1 [0014] FIG. 4 is a flowchart illustrating a method of estimating a
hardness of a rock mass
2 using the system of FIG. 2.
3 [0015] FIG. 5 graphically illustrates a blast design for a hole
based on a distribution of a
4 drilling index for the hole.
[0016] FIG. 6 is a flowchart illustrating a method of providing feedback
relating to an
6 estimated hardness of a rock mass.
7 [0017] FIG. 7 schematically illustrates successive phases of
survey drilling, blast hole
8 drilling, and loading blasted material from the perspective of
information available to a model of
9 the rock mass.
DETAILED DESCRIPTION
11 [0018] Before any embodiments of the invention are explained in
detail, it is to be
12 understood that the invention is not limited in its application to the
details of construction and the
13 arrangement of components set forth in the following description or
illustrated in the following
14 drawings. The invention is capable of other embodiments and of being
practiced or of being
carried out in various ways. Also, it is to be understood that the phraseology
and terminology
16 used herein is for the purpose of description and should not be regarded
as limited. The use of
17 "including," "comprising" or "having" and variations thereof herein is
meant to encompass the
18 items listed thereafter and equivalents thereof as well as additional
items. The terms "mounted,"
19 "connected" and "coupled" are used broadly and encompass both direct and
indirect mounting,
connecting and coupling. Further, "connected" and "coupled" are not restricted
to physical or
21 mechanical connections or couplings, and may include electrical
connections or couplings,
22 whether direct or indirect. Also, electronic communications and
notifications may be performed
23 using any known means including direct connections, wireless
connections, and the like.
24 [0019] It should be noted that a plurality of hardware and
software based devices, as well as
a plurality of different structural components may be utilized to implement
the invention. In
26 addition, it should be understood that embodiments of the invention may
include hardware,
27 software, and electronic components or modules that, for purposes of
discussion, may be
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1 illustrated and described as if the majority of the components were
implemented solely in
2 hardware. However, one of ordinary skill in the art, and based on a
reading of this detailed
3 description, would recognize that, in at least one embodiment, the
electronic based aspects of the
4 invention may be implemented in software (for example, stored on non-
transitory computer-
readable medium) executable by one or more processors. As such, it should be
noted that a
6 plurality of hardware and software based devices, as well as a plurality
of different structural
7 components may be utilized to implement the invention. For example,
"controller" and "control
8 unit" described in the specification may include one or more processors,
one or more memory
9 modules including non-transitory computer-readable medium, one or more
input/output
interfaces, and various connections (for example, a system bus) connecting the
components.
11 Furthermore, and as described in subsequent paragraphs, the specific
configurations illustrated in
12 the drawings are intended to exemplify embodiments of the invention and
that other alternative
13 configurations are possible.
14 [0020] FIG. 1 illustrates a blasthole drill rig ("drill") 10. It
should be understood that the
drill 10 illustrated in FIG. 1 is provided as one example of a mining machine,
and the
16 embodiments described herein may be used with any type of mining machine
and are not limited
17 to the example drill 10 illustrated in FIG. I. Furthermore, the
embodiments described herein
18 may be used with any type of industrial machine and are not limited to a
mining machine.
19 100211 As illustrated in FIG. 1, the drill 10 includes a mast or
drill tower 14, a base 18 (for
example, a machinery house) that supports the drill tower 14, an operator's
cab 22 coupled to the
21 base 18, and crawlers 26 driven by a crawler drive 30 that moves the
drill 10 along a surface 34
22 (for example, the ground). The drill tower 14 is coupled to and supports
a drill string 38
23 including a plurality of components such as, for example, drill pipes, a
shock sub, a thread, a drill
24 bit, and a bit stabilizer. As illustrated in FIG. 1, the drill string 38
is configured to extend
downward (for example, vertically or at an angle) through the surface 34 and
into a borehole.
26 The drill 10 also includes one or more leveling jacks 42 to support the
drill 10 on the surface 34.
27 In the extended position, a jack 42 engages with the surface 34 to
support the drill 10. When the
28 drill 10 is not in use (e.g., not drilling), the jack 42 may be moved to
a fully retracted position to
29 allow the drill 10 to move via the crawlers 26 without the jack 42
interfering with the surface 34.
Furthermore, the drill 10 may include one or more drill sensors 48 (not shown
in FIG. 1). The
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1 drill 10 may also include one or more controllers 49 for controlling the
components of the drill
2 10. In some embodiments, the one or more controllers 49 communicate with
the one or more
3 drill sensors 48. Also, it should be understood that in some embodiments,
the one or more
4 controllers 49 are remote from the drill 10 and communicate with
components of the drill 10 (for
example, the drill sensors 48, other controllers, and the like) directly (over
one or more wired or
6 wireless connections) or through one or more intermediary devices (over
one or more wired or
7 wireless connections).
8 [0022] The drill sensors 48 are used to measure drilling
parameters. The drilling parameters
9 may include, for example, a depth of the drill bit, a rate of
penetration, a pull-down force, a
rotational speed and torque, a hydraulic pressure, an inclination of the drill
tower 14, a position
11 of the drill string 38, other drilling parameters, or a combination
thereof. For example, the drill
12 sensors 48 may include a voltage sensor, a current sensor, or a
combination thereof for sensing
13 the electrical rotary torque of the drill 10. As another example, the
drill sensors 48 may include a
14 voltage sensor, a current sensor, a pressure sensor, or a combination
thereof installed on the drive
of the drill 10 for sensing a pull-down force (for example, the amount of
downward force applied
16 by the drill 10 during vertical drilling). In some embodiments, the
drill sensors 48 include one or
17 more inclinometers for determining the inclination of the drill tower
14.
18 [00231 FIG. 2 illustrates a system 50 for estimating a hardness of
a rock mass drilled using
19 the drill 10 according to one embodiment. The systein 50 includes a rock
mass lithography
database 52 and a controller 54. The rock mass lithography database 52 stores
a rock mass
21 model. The rock mass model represents rock mass data related to the
material properties of a
22 rock mass that may affect the drilling process. In particular, the rock
mass data represented by
23 the rock mass model may include data relating to, for example, a
composition, a hardness, a
24 location of one or more fault planes, an abrasiveness, other material
properties of a rock mass
that may affect drilling, or a combination thereof. In some embodiments, the
rock mass model
26 includes data representing a three-dimensional geo-spatial
representation of material properties
27 of a rock mass. In some embodiments, the rock mass model is based on
previously collected
28 rock mass data regarding a specific rock mass. For example, the rock
mass model may be based
29 on previously collected geological survey data (for example, a core
sample), drilling data from
previously drilled holes within the same rock mass, data relating to
previously determined
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I uncertainty of the material properties of a drilled hole, other
previously collected rock mass data,
2 or a combination thereof.
3 [0024] Additionally, as described in more detail below, the rock
mass model may be based
4 on (for example, updated with) rock mass data relating to previously
achieved fragmentation (for
example, from previous blastings), feedback data associated with machine
performance (for
6 example, indirect measurements of previous blastings collected by other
machines), and the like.
7 For example, when a rock mass is blasted, a secondary industrial machine
may be used to collect
8 the blasted rock mass material. While the secondary industrial machine
interacts with the blasted
9 rock mass material, indirect measurements (for example, live loading
data) are collected by the
secondary industrial machine. The indirect measurements may relate to, for
example, whether
11 the blast design was successful based on machine performance metrics
relating to fragmentation
12 of the blasted rock mass material, (for example, digging energy, digging
forces, motion through
13 the dig face, payload, and the like), whether adjustments to the blast
design should be made, and
14 the like.
[00251 In some embodiments, the rock mass lithography database 52 commun
icates with (for
16 example, transmits data to and receives data from) the controller 54
over a communication
17 network 56. The communication network 56 may include the Internet, a
cellular network, a
18 public network, a private network, or other wired or wireless network.
It should be understood
19 that in some embodiments, the communication network 56 includes a direct
channel of
communication between the rock mass lithography database 52 and the controller
54 (for
21 example, a dedicated wired connection). Furthermore, in some
embodiments, the rock mass
22 lithography database 52 communicates with the controller 54 indirectly
through one or more
23 intermediary computing devices. For example, the rock mass lithography
database 52 may
24 communicate (for example, through a wired or wireless connection or
network) with an
intermediary computing device (for example, a desktop computer, a laptop
computer, a tablet
26 computer, a communication device, such as a smart telephone or smart
wearable, and the like),
27 and the intermediary computing device may communicate with the
controller 54 (for example,
28 through the communication network 56).
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1 100261 As illustrated in FIG. 2, the controller 54 is in
communication with the drill sensors
2 48. The controller 54 and the drill sensors 48 may communicate over one
or more wired or
3 wireless connections. Although flot illustrated in FIG. 2, in some
embodiments, the controller 54
4 communicates with the drill sensors 48 through the communication network
56. Also, it should
be understood that the controller 54 may communicate with the drill sensors 48
indirectly
6 through one or more intermediary computing devices, one or more
intermediary storage devices,
7 or a combination thereof. For example, the controller 54 may communicate
(for example,
8 through a wired or wireless connection or network) with an intermediary
computing device (for
9 example, a desktop computer, laptop computer, a tablet computer, a
communication device, such
as a smart telephone or smart wearable, and the like), and the intermediary
computing device
11 may communicate with the drill sensors 48 (for example, through a wired
or wireless connection
12 or network). In some embodiments, the controller 54 may communicate with
other equipment,
13 such as from at least one shovel, wheel loader, excavator, another type
of mining machine, and
14 the like (collectively referred to herein as a "secondary industrial
machine") to receive, for
example, the feedback data, as mentioned above. Further, the controller 54 may
communicate
16 (for example, through a wired or wireless connection or network) with an
intermediary storage
17 device (for example, an intermediary database), and the intermediary
storage device may
18 communicate with the drill sensors 48 (for example, through a wired or
wireless connection or
19 network). Similarly, the controller 54 may communicate with the drill
sensors 48 through the
controller 49 of the drill 10.
21 100271 lt should be understood that, in some embodiments, the
controller 54 is included in
22 the controller 49 of the drill 10. Accordingly, the controller 54 may be
located on the drill 10 or
23 remote from the drill 10. For example, the controller 54 may be included
in a remote control
24 device or a remote control station for the drill 10.
100281 FIG. 3 schematically illustrates the controller 54 of the system 50
according to one
26 embodiment. As illustrated in FIG. 3, the controller 54 includes an
electronic processor 58 (for
27 example, a microprocessor, application specific integrated circuit
("ASIC"), or other
28 programmable device), an input/output interface 60, and a computer-
readable medium 62 (for
29 example, a non-transitory computer-readable medium). The electronic
processor 58, the
input/output interface 60, and the computer-readable medium 62 are connected
by and
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1 communicate through one or more communication unes or busses. It should
be understood that
2 the controller 54 may include fewer or additional components than as
illustrated in FIG. 3 and
3 may include components in configurations other than the configuration
illustrated in FIG. 3.
4 Also, the controller 54 may be configured to perform additional
functionality than the
functionality described herein. Additionally, the functionality of the
controller 54 may be
6 distributed among multiple controllers or devices.
7 100291 The computer-readable medium 62 includes non-transitory
memory (for example,
8 read-only memory, random-access memory, or combinations thereof) storing
program
9 instructions and data. The electronic processor 58 is configured to
retrieve instructions and data
from the computer-readable medium 62 and execute, among other things, the
instructions to
11 perform the methods described herein. The input/output interface 60
transmits data from the
12 controller 54 to externat systems, networks, and devices and receives
data from externat systems,
13 networks, and devices. The input/output interface 60 may also store data
received from externat
14 sources to the computer-readable medium 62 or provide received data to
the electronic processor
58. For example, in some embodiments, the input/output interface 60 includes a
wireless
16 transmitter that communicates with the communication network 56 to
access the rock mass
17 lithography database 52. Alternatively or in addition, the input/output
interface 60 may include a
18 connector or port for receiving a wired connection to the rock mass
lithography database 52, an
19 intermediate computing device, or an intermediate storage device as
described above (for
example, a universal serial bus cable). In some embodiments, the computer-
readable medium 62
21 also stores the rock mass lithography database 52 or a portion thereof.
22 100301 As illustrated in FIG. 3, the controller 54 also
communicates with the drill sensors 48.
23 It should be understood that, in some embodiments, the drill sensors 48
are included in the
24 controller 54. As described above, when the controller 54 is located
remote from the drill 10, the
controller 54 may communicate with the drill sensors 48 directly or through
one or more
26 intermediary devices. Furthermore, in some embodiments, the controller
54 receives input from
27 one or more operator control devices (for example, a joystick, a lever,
a foot pedal, another
28 actuator operated by an operator to control the operation of the drill
10, or a combination
29 thereof). For example, an operator may use the operator control devices
to operate the drill 10 to
drill a hole within a rock mass. In some embodiments, the controller 54 also
communicates with
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1 a user interface (for example, through the input/output interface 60),
such as a display device or a
2 touchscreen. The user interface may allow an operator to operate the
drill 10 and, in some
3 embodiments, displays feedback to an operator regarding, for example, a
hardness of a rock
4 mass, a drilling sequence, a drilling index, and the like. Additionally,
as mentioned above, the
controller 54 may also communicate with other equipment (for example, one or
more secondary
6 industrial machines) to, for example, receive feedback data.
7 [0031] FIG. 4 illustrates a method 70 of estimating a hardness of
a rock mass performed by
8 the controller 54 (the electronic processor 58) according to one
embodiment. It should be
9 understood that the method 70 may include more or less steps than
illustrated in FIG. 4.
Additionally, it should be understood that the steps illustrated in FIG. 4 may
be performed in an
11 alternative order, simultaneously, continuously, or a combination
thereof.
12 [0032] As illustrated in FIG. 4, the method 70 includes receiving,
with the electronic
13 processor 58, a rock mass model (at block 71). In some embodiments, the
controller 54 receives
14 (via the input/output interface 60) the rock mass model from the rock
mass lithography database
52 over the communication network 56. Alternatively or in addition, the rock
mass model or
16 portions thereof may be locally stored or programmed in the controller
54 (for example, the
17 computer-readable medium 62). As described above, the rock mass model
may be based on a
18 priori data relating to the material properties of a rock mass (for
example, obtained by core
19 sampling). Additionally, as described in more detail below, the rock
mass model may be
updated based on feedback data received from other equipment (for example, one
or more
21 secondary industrial machines), drilling data previously-collected by
the industrial machine
22 before the live drilling data (for example, data collected by the drill
10 during the drilling of
23 previously drilled holes), or a combination thereof.
24 [0033] The method 70 also includes receiving, with the electronic
processor 58, live drilling
data from the drill 10 (at block 72). In some embodiments, the live drilling
data provides
26 indirect measurements of the material properties of the rock mass using
the drill 10 as a sensor.
27 For example, the live drilling data may be detected using the one or
more drill sensors 48. As
28 described above, the live drilling data may include, for example, a
depth of the drill bit, a rate of
29 penetration, a pull-down force, a rotational speed and torque of the
drill bit, a hydraulic pressure,
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I a flow rate, an electrical signal, other material properties of the rock
mass that may affect the
2 drilling process, or a combination thereof. The drilling data may be
referred to herein as "live
3 drilling data" or "online measurement data." Additionally, the live
drilling data may include data
4 (determined via the Global Navigation Satellite System (GNSS)) relating
to a pose of the drill 10
(for example, a three-dimensional orientation of the drill 10 and a three-
dimensional position of
6 the drill 10 in a global frame of reference).
7 10034] In some embodiments, the live drilling data is filtered
using one or more models
8 associated with the drilling process. The one or more models associated
with the drilling process
9 may include, for example, a drill dynamic model, a drill-rock interaction
model, a drill
operational state model, a drill string model, a drill location model, a
kinematic model, and the
11 like. The drill dynamic model may capture dominate dynamics of the drill
10 and the main
12 operating components, actuators, and the like of the drill 10. The drill-
rock interaction model
13 may capture interactions between a drill bit and a surface being drilled
(for example, the surface
14 34 of FIG. 1). The drill operational state model may track a current
operational state of the drill
10, such as whether the drill 10 is idle, repositioning, drilling, and the
like, and may track holes
16 drilled by the drill 10. In some embodiments, the operational state of
the drill 10 is tracked using
17 a finite-state machine (for example, an abstract machine encoded as an
algorithm that may be in
18 one of a finite number of states). The drill string model may track a
state of the drill string 38,
19 such as an age of a drill bit or a state of a drill bit (for example,
new or used, new or dull, and the
like). The drill location model may track a location of the drill 10, and the
kinematic model may
21 track a position of the drill string 38 relative to the base 18. In some
embodiments, the models
22 associated with the drilling process interact. For example, the drill
dynamic model may be
23 augmented with the state of the drill-rock interaction mode' in an
optimal estimation framework
24 to invert the system dynamics and estimate drilling forces and torque
front indirect
measurements.
26 100351 In some embodiments, the models associated with the
drilling process are locally
27 stored or programmed in the controller 54 and are customized for the
drill 10 and other
28 environment factors (for example, a drilling program, a drilling
schedule, a drilling method, and
29 the like). Alternatively or in addition, the models associated with the
drilling process may be
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1 stored on an external memory accessible by the controller 54 (for
example, directly or indirectly
2 through one or more intermediary devices over a wired or wireless
connection).
3 [0036] Upon receiving the live drilling data, the electronic
processor 58 updates the rock
4 mass rnodel based on the received live drilling data (at block 75). For
example, in some
embodiments, the electronic processor 58 updates the rock mass model by adding
or updating
6 data points in the rock mass model based on (determined based on) the
received live drilling
7 data. In some embodiments, the additions or updates to the rock mass
model includes a rock
8 hardness value and an uncertainty value. Also, in some embodiments, the
additions or updates to
9 the rock mass model includes the live drilling data or a portion thereof
(for example, drilling
forces and torque). For example, an operational state of the drill 10 may be
included in a data
11 point to link a detected rock hardness with a particular operational
state of the drill 10 or
12 components thereof (for example, a dullness of the drill bit).
13 [0037] The electronic processor 58 uses the updated rock mass
model to estimate a drilling
14 index (at block 76). In some embodiments, the drilling index represents
an identification of one
or more material properties (for example, a rock hardness) at a specific depth
within a particular
16 hole. For example, as described above, the rock mass model may include a
three-dimensional
17 geo-spatial representation of material properties of a rock mass. In
some embodiments, at the
18 commencement of drilling, the rock mass model is queried to determine a
distribution of material
19 properties for a hole to be drilled based on ail information available
to the rock mass model up to
that point in time (for example, an a priori distribution of a drilling
index). For example, the
21 rock mass model may be queried to estimate the material properties of a
specific three-
22 dimensional location (for example, a specific depth) within a hole to be
drilled. Alternatively or
23 in addition, the rock mass model may be queried to estimate an
uncertainty value associated with
24 the estimated material properties. Thus, the distribution may be
expressed in terms of material
properties of the lithography of the rock mass and an uncertainty value
associated with the
26 estimated material properties (for example, with the estimated drilling
index). In some
27 embodiments, the uncertainty value is a number indicating a spread or an
uncertainty in the
28 estimated material properties (for example, a variance, a standard
deviation, and the like).
29 Alternatively or in addition, the uncertainty value may represent a
level of information available
in the rock mass lithography database 52 (in example, the availability and
extent of prior survey
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1 data). In some embodiments, the distribution is made based on the nominal
drilling depth of the
2 drill 10. Alternatively or in addition, the distribution may be made
based on a pose of the drill
3 10 (for example, a three-dimensional location of the drill 10 as
determined by GNSS and a three-
4 dimensional orientation of the drill 10). The prior distribution is then
updated based on the live
drilling data to form a posterior estimate of the material properties of the
rock mass (for example,
6 using an optimal estimation framework).
7 [0038] In some embodiments, the drilling index distribution for
each hole is used to
8 categorize rock mass hardness into discrete bands used for blast design.
Accordingly, the
9 method 70 may include setting, with the electronic processor 58, a
blasting parameter for the
hole based on the estimated drilling index (at block 77). The drilling index
may be used to set a
11 blasting parameter, such as a blasting energy, a blasting sequence, a
blasting configuration and
12 the like, for each or a plurality of holes. Additionally, in the case of
a blasting energy, the
13 drilling index may also be used to set a blasting parameter fora
plurality of depths within each or
14 a plurality of the holes. Also, in some embodiments, the drilling index
and the performance of
the process can be used to provide a design of a blast, a process of drilling,
or a combination
16 thereof.
17 [00391 For example, FIG. 5 illustrates an example of how the
drilling index distribution is
18 converted to a discrete categorization that maps to blasting design. In
particular, FIG. 5
19 illustrates a graphical representation of a hole 78 and associated rock
hardness at various depths
within the hole 78. Based on the relationship between the depth and the
associated rock hardness
21 of various depths, discrete bands of explosive energy (for example, how
much explosive energy
22 is needed of a given depth based on the associated rock hardness with
that given depth) may be
23 identified. The discrete bands may be used to provide instructions to,
for example, a vehicle 79
24 dispensing liquid explosives. The instructions may relate to how much
liquid explosive to
dispense and at what depth to dispense that specific amount of liquid
explosives. The
26 instructions may be communicated electronically over a wired or wireless
connection.
27 [0040] FIG. 6 illustrates a method 80 of providing feedback
relating to an estimated hardness
28 of a rock mass. il should be understood that the method 80 may include
more or less steps than
29 illustrated in FIG. 6. Additionally, it should be understood that the
steps illustrated in FIG. 6
13
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1 may be performed in an alternative order, simultaneously, continuously,
or a combination
2 thereof. Furthermore, it should be understood that the steps illustrated
in FIG. 6 may be
3 performed in conjunction with the steps illustrated in the method 70 of
FIG. 4. Also, although
4 the method 80 is described herein as being performed by the electronic
processor 58, the method
80 or portions thereof may be performed by other devices (other electronic
processers).
6 [0041] As illustrated in FIG. 6, the method 80 includes receiving,
with the electronic
7 processor 58, the rock mass model (at block 82). As described above, with
regard to the method
8 70, in some embodiments, the controller 54 receives (via the input/output
interface 60) the rock
9 mass model from the rock mass lithography database 52 over the
communication network 56 or
a local medium. In some embodiments, the rock mass model described in method
80 includes
11 the updated rock mass model described above with respect to the method
70.
12 100421 As illustrated in FIG. 6, the method 80 also includes
receiving, with the electronic
13 processor 58, live loading data (of block 84). As mentioned above, in
some embodiments, live
14 data is collected from other equipment, such as one or more secondary
industrial machines (for
example, other drills, shovels, wheel loaders, vehicles, and the like). For
example, when a rock
16 mass is blasted, a shovel may be used to remove/transport the blasted
rock mass material. While
17 the shovel interacts with the blasted rock mass material, the shovel
(for example, one or more
18 sensors included in the shovel) collects indirect measurements of the
fragmented rock (for
19 example, a payload amount, a digging force, a motion through the dig
face, and the like). The
indirect measurements may relate to, for example, a particle size of the
blasted rock material, a
21 composition of the blasted rock material, and the like.
22 [0043] The method 80 also includes updating, with the electronic
processor 58, the rock
23 mass model based on the received live loading data (at block 85). In
some embodiments, the
24 rock mass model is updated by adding data points to the rock mass model,
updating data points
included in the rock mass model, or a combination thereof based on the
received live loading
26 data. As described above with respect to method 70, the electronic
processor 58 uses the updated
27 rock mass model to estimate one or more drilling indexes (for example,
an identification of rock
28 hardness of a depth within a hole) (at block 88). In some embodiments,
as described above with
14
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I respect to method 70, the electronic processor 58 sets a blasting
parameter for the hole based on
2 the estimated drilling index (at block 89).
3 [0044] Accordingly, in some embodiments, the live loading data is
used as feedback data for
4 the rock mass model. For example, the live loading data may be used to
correct the rock mass
model for deviations between a desired fragmentation and an achieved
fragmentation. For
6 example, FIG. 7 illustrates three exemplary phases of a drilling process.
A first phase 90
7 illustrates a rock mass model and the associated information in the rock
mass model based on
8 geological survey data (for example, core sampling). As the drilling
process progresses and
9 additional data (in example, the live drilling data) is collected, the
rock mass model is updated
(for example, the knowledge of material properties of the rock mass increases
and the
11 uncertainty value associated with the estimated material properties
decreases), as illustrated in a
12 second phase 95. Additionally, in some embodiments, once blasting is
performed, the live
13 loading data is collected to further update the rock mass model (for
example, to correct for
14 deviations between a desired fragmentation and an achieved
fragmentation), as illustrated in a
third phase 100.
16 [0045] In the methods described herein, the information (for
example, material properties of
17 a rock mass) from the rock mass model is updated with the live drilling
data, the live loading
18 data, or a combination thereof. Accordingly, in some embodiments, the
rock mass model is
19 continuously updated to incrementally build knowledge and confidence in
the rock mass model.
In other words, both the live drilling data and the live loading data may be
used as the feedback
21 data for the rock mass model. Thus, an optimal scheme is developed by
continuously updating
22 the rock mass model. As noted above, the live drilling data may include
a depth of the drill bit, a
23 rate of penetration, a pull-down force, a rotational speed and torque,
or a combination therefore.
24 In some embodiments, the estimated drilling index also takes into
account a configuration of a
plan area of a face of a drill bit (for example, a design of the drill bit) as
set by, for example, a
26 manufacturer of the drill bit. Such configuration information may be
received from, for
27 example, a device (for example, a controller) associated with the drill
10. The live drilling data,
28 the live loading data, or a combination thereof may be used to modify
the distribution provided
29 by the rock mass model to provide a distribution with a higher
resolution (for example, a higher
accuracy) than geological surveying may practicably provide. For example, the
live drilling
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1 data, the live loading data, or a combination thereof may be used to
modify the uncertainty value
2 to also account for noise associated with the live drilling data, the
live loading data, or a
3 combination thereof.
4 [0046] In some embodiments, a classification scheme is used to
determine a drilling index.
In this embodiment, the rock mass model is used to determine a plurality of
probabilities of
6 particular lithographie features, by location, down the hole. The
lithographie features are treated
7 as sub-populations with unique characteristics in terms of the
distributions of operational metrics
8 and performance metrics logged from the drill 10 (for example, a specific
energy of drilling, a
9 rate of penetration, a pull-down force, a rotation speed and torque, and
the like). The drilling
index or classifier may then be framed as a missing-data problem whereby the
live drilling data
11 is used as inputs to determine the member of the rock mass being drilled
within the sub-
12 populations of lithography.
13 [0047] In other embodiments, the drilling index is determined
using a Markov-transition
14 model that determines when a drilling regime changes based on a
likelihood of transition
determined from the a priori rock mass information queried from the rock mass
model and the
16 live drilling data, the live loading data, or a combination thereof.
17 [0048] As described above, regardless of how the drilling index is
determined, as drilling
18 progresses, the rock mass model may also be updated with the latest
estimates of material
19 properties (in example, previously determined drilling indexes), an
operational state of the drill
10, and a blasting parai-neter, and a subsequent operation of the controller
54 may use the
21 updated rock mass model for future holes in the rock mass. Furthermore,
as described above, the
22 rock mass model may also be updated with data acquired from other
equipment, such as a second
23 industrial machine (for example, other drills, shovels, wheel loaders,
and the like). For example,
24 when a worksite includes two drills, three shovels, and one wheel
loader, data collected by all six
machines may be used to update the rock mass model. In some embodiments, the
rock mass
26 model is updated based on drilling data previously-collected by the
industrial machine before the
27 live drilling data is received.
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1 [0049] Also, in some embodiments, the controller 54 detects
significant deviations between
2 the modeled rock properties (for example, from the rock mass model) and
the measured rock
3 properties (for example, from the live drilling data, the live loading
data, or a combination
4 thereof). The controller 54 may detect the significant deviations by
comparing the modeled rock
properties to the measured rock properties. The significant deviations may be
flagged as
6 potential un-modelled features (for example, rock mass properties flot
currently represented
7 within the rock mass model) in the lithography of the rock mass. In some
embodiments, the
8 deviations represent distinct changes in the lithology of a rock mass
that may affect blast
9 planning (for example, a void, a fault, and the like). The rock mass
model may be updated based
on these flagged un-modelled features to account for the un-modelled features
in subsequent
11 operation.
12 100501 Furthermore, trends in the statistics of the operational
and performance data (in
13 example, the live drilling data, the live loading data, or a combination
thereof) over time may
14 also be used to track the operational state of the drill bit (in
example, wear). In other words, by
tracking a performance of the drill 10 over time, the controller 54 may remove
the effects of
16 changes to machine state (for example, bit wear) and machine dynamics
that may corrupt the
17 online drilling data.
18 [0051] Thus, embodiments described herein provide, among other
things, systems and
19 methods for estimating the hardness of a rock mass during operation of
an industrial machine.
Various features and advantages of some embodiments are set forth in the
following claims.
17
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