Systems and methods for drilling machines
Patent Information
- Authority / Receiving Office
- US · United States
- Patent Type
- Applications(United States)
- Current Assignee / Owner
- Filing Date
- 2025-02-12
- Publication Date
- 2026-08-13
Smart Images
Figure US20260234994A1-D00000_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present disclosure relates generally to drilling machines, and more specifically, relates to systems and methods associated with such a machine.BACKGROUND
[0002] Drilling machines, including mobile machines such as blasthole drilling machines, are typically used for drilling blastholes for mining and quarrying applications. The process of excavating rock, or other material, by blasthole drilling includes using the blasthole drilling machine to drill a plurality of holes into the intact rock mass, and filling the blastholes with explosives. The explosives are detonated in a controlled manner, causing the rock to fragment and to be displaced, after which the fragmented rock is removed using an excavating machine. Many current blasthole drilling machines utilize rotary or rotary-percussive drilling methods where axial and rotational energy that is produced by hydraulic or electric motors mounted on a rotary head connected to a drill string (which may include multiple pipes, a shock sub isolator, and a tricone or down-the-hole hammer bit), drill vertical and inclined blastholes between approximately 6 inches and 22 inches in diameter, with typical depths of up to approximately 30 meters or less. When drilling an individual blasthole, and when moving between a completed blasthole and a new area where another blasthole is to be drilled, an operator of the drilling machine may adjust a number of parameters controlling operation of the drill string, in an effort to optimize drilling of the blastholes.
[0003] U.S. Pat. No. 11,396,804 to Madasu (“the '804 patent”) is directed to automated rate-of-penetration optimization during drilling of a wellbore. According to the '804 patent, an operator of the machine may modify values in an algorithm that controls the drill, in order to achieve a desired rate of penetration during drilling. However, the '804 patent discloses only limited optimization of the drilling operation, and requires that an operator choose specific variables such as rotation rate of the drill string or drill bit.
[0004] Accordingly, the systems and methods of the present disclosure may address or solve one or more of the problems set forth above or other problems in the art. The scope of the current disclosure, however, is defined by the attached claims, and not by the ability to solve any specific problem.SUMMARY
[0005] In some aspects, a control system for adjusting operation of a drill string of a drilling machine includes: a classifier module including a neural network configured, during a drilling process, to classify a ground condition, and based on the ground condition to output a set of parameters for controlling operation of the drill string, and a range of permissible values for each parameter of the set of parameters; a genetic algorithm module configured to receive as inputs i) the output from the classifier module, and ii) a cost function, the genetic algorithm module configured to output, for each parameter of the set of parameters, a predetermined value within the range of permissible values, based on the inputs, wherein the cost function includes a value corresponding to performance of the drill string and lifetime of consumables of the drill string; and a parameter setpoint module configured to receive, as an input, the predetermined values, the parameter setpoint module configured to adjust operation of the drill string based on the predetermined values.
[0006] In some aspects, a drilling machine includes: a frame; a drill string supported on the frame; and a control system for adjusting operation of the drill string, the control system including: a neural network configured to output a set of parameters for controlling operation of the drill string, and a range of permissible values for each parameter of the set of parameters; a genetic algorithm module configured to receive as inputs i) the output from the neural network and ii) a cost function, the genetic algorithm module configured to output, for each parameter of the set of parameters, a predetermined value within the range of permissible values, based on the inputs, wherein the cost function includes a value corresponding to performance of the drill string and lifetime of a consumable of the drill string; and a parameter setpoint module configured to receive, as an input, the predetermined values, the parameter setpoint module configured to adjust operation of the drill string based on the predetermined values.
[0007] In some aspects, a method of adjusting drill parameters of a drill string of a drilling machine during a drilling operation, includes: inputting, by an operator, a value for a cost function, the value corresponding to performance of the drill string and lifetime of a consumable of the drill string; and outputting, by a genetic algorithm module, predetermined values for each parameter of a set of parameters for controlling operation of the drill string, based on the value of the cost function.BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate various exemplary embodiments and, together with the description, serve to explain the principles of the disclosure.
[0009] FIG. 1 illustrates a schematic side view of an exemplary drilling machine including a drill string, according to aspects of the disclosure.
[0010] FIG. 2 illustrates a schematic block diagram of an exemplary control system for adjusting parameters during drilling of a hole with the drill string of the drilling machine of FIG. 1, according to aspects of the disclosure.
[0011] FIG. 3 illustrates a flowchart of an exemplary method associated with the drilling machine of FIG. 1, according to some aspects of the invention.DETAILED DESCRIPTION
[0012] Both the foregoing general description and the following detailed description are exemplary and explanatory only and do not restrict the claims. The terms “comprises,”“comprising,”“having,”“including,” or other variations thereof, used herein cover a non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements, but may include other elements not expressly listed or inherent to such a process, method, article, or apparatus. Further, relative terms, such as, for example, “about,”“substantially,”“generally,”“approximately,” or other variations thereof, include a possible variation of ±10% in a stated value. Still further, the terms “one or more,”“at least one,” and variations thereof include one, two, or more than two.
[0013] With reference to the drawings, FIG. 1 illustrates a schematic side view of an exemplary mobile drilling machine 10, according to some aspects of the disclosure. Although the disclosure herein may be applicable to any type of drilling machine, such as but not limited to a mobile machine, whether performing rotary-percussive or rotary drilling, the below description describes aspects of the invention with respect to a mobile blasthole drilling machine. Thus, as shown in FIG. 1, mobile drilling machine 10 may include a control system 100 for adjusting parameters during a drilling operation, discussed in further detail below. Mobile drilling machine 10 also may include a frame 12, machinery 14, and a drilling mast 16, among other components. A transport mechanism 18, such as crawler tracks (or wheels), may support frame 12 on a ground surface. Transport mechanism 18 may allow mobile drilling machine 10 to maneuver about or across the ground surface to a desired location for a drilling operation, as further discussed.
[0014] Frame 12 may further include one or more jacks 20 (two shown in FIG. 1) for supporting and leveling mobile drilling machine 10 on the ground surface during the drilling operation. Frame 12 may support machinery 14, which may include engines, motors, batteries, pumps, air compressors, a hydraulic fluid storage tank 38 (shown schematically in FIG. 1), or any other equipment necessary or desirable to power and operate mobile drilling machine 10. Frame 12 may further support an operator cab 22, in which an operator may sit and from which the operator may maneuver or control operation of mobile drilling machine 10, including the drilling operation, via an input device 40, which may include user interfaces or displays. Although FIG. 1 illustrates frame 12 supporting operator cab 22 that includes input device 40, input device 40 may be remote from mobile drilling machine 10 (e.g., not within operator cab 22 or otherwise not located on frame 12 or any other component of mobile drilling machine 10), such that mobile drilling machine 10 may be controlled remotely by the operator. In some instances, mobile drilling machine 10 may operate autonomously or semi-autonomously.
[0015] As FIG. 1 illustrates, drilling mast 16 may include a mast frame 24, which may support a rotary head 26 movably mounted on mast frame 24. Rotary head 26 may couple to, and may be controllable to rotate, a drill string 28 including one or more drilling pipe sections, on which a drill bit 30 may be mounted for drilling into the ground surface, as further described below. In some aspects, when drill string 28 reaches its maximum depth, drill string 28 may include multiple (e.g., more than one) drilling pipe sections, while in other aspects, drill string 28 may include only one drilling pipe section when drill string 28 is at its maximum depth. In some instances, the one or more drilling pipe sections may be approximately 10 meters to approximately 15 meters in length, although the drilling pipe sections may be greater than approximately 15 meters in length, or less than approximately 10 meters in length. In some instances, the one or more drilling pipe sections may be approximately 6 inches and 22 inches in diameter, although the drilling pipe sections may be greater than approximately inches in diameter, or less than approximately 6 inches in diameter.
[0016] At the end of drill string 28, mobile drilling machine 10 may include a drill bit 30. Drill bit 30 may include different types of drill bits, such as a rotary drill bit (e.g., a tricone drill bit), a claw drill bit, a down-the-hole bit, or another drill bit type. Rotary head 26 may be any type of rotary head, such as a hydraulically or electrically powered rotary head or the like. Rotary head 26 may further include a hydraulic fluid line (not shown) for receiving hydraulic fluid. The hydraulic fluid may be used to rotate a shaft of rotary head 26 on which drill string 28 is connected for rotating drill string 28 (and thus rotating drill bit 30). The hydraulic fluid line of rotary head 26 may be coupled to a hydraulic valve 32 (shown schematically in FIG. 1) for controlling the amount, and flow rate, of the hydraulic fluid into rotary head 26. In the exemplary embodiment, hydraulic valve 32 may be located on hydraulic fluid storage tank 38. However, hydraulic valve 32 may be located anywhere along the hydraulic fluid line of rotary head 26, as necessary or desired.
[0017] Drilling mast 16 may further include a hydraulic feed cylinder 34 (located within mast frame 24) connected to rotary head 26 via a cable and pulley system (not shown) for moving rotary head 26 up and down along mast frame 24. As such, when hydraulic feed cylinder 34 is extended, hydraulic feed cylinder 34 may exert a force on rotary head 26 for pulling-down rotary head 26 along mast frame 24. Further, when hydraulic feed cylinder 34 is retracted, hydraulic feed cylinder 34 may exert a force on rotary head 26 for hoisting up rotary head 26 along mast frame 24. Thus, hydraulic feed cylinder 34 may be controllable to move rotary head 26 up and down mast frame 24 such that drill bit 30 on drill string 28 may be pulled-down towards, and into, the ground surface or hoisted up from the ground surface. As used herein, the term “feed” in the context of hydraulic feed cylinder 34 may include movement of drill string 28 in either direction (up or down). Hydraulic feed cylinder 34 may include hydraulic fluid lines (not shown) for receiving and conveying hydraulic fluid to and from hydraulic feed cylinder 34. The hydraulic fluid may be used to actuate hydraulic feed cylinder 34 such that a rod of hydraulic feed cylinder 34 may be extended or retracted. The hydraulic fluid line of hydraulic feed cylinder 34 may be coupled to hydraulic valves 36 (shown schematically in FIG. 1) for controlling the amount, as well as flow rate and pressure, of the hydraulic fluid into hydraulic feed cylinder 34. In the exemplary embodiment, hydraulic valve 36 may be located on hydraulic fluid storage tank 38. However, hydraulic valve 36 may be located anywhere along or in fluid communication with the hydraulic fluid line of the hydraulic feed cylinder 34, as necessary or desired. It is understood that hydraulic fluid may be any type of hydraulic fluid, such as hydraulic oil or another fluid. In some instances, drilling mast 16 may include an electrical system, in place of or in addition to hydraulic feed cylinder 34 and the above-described associated hydraulic components, for moving rotary head 26 up and down along mast frame 24.
[0018] FIG. 1 shows drill string 28 located in a hole 50 drilled by drill string 28, during a drilling operation into the ground surface. Hole 50 may include a top 52 of hole 50, and a bottom 54 of hole 50 (e.g., desired depth of hole). As shown by the arrows in FIG. 1, drill string 28 may rotate, and move up and down (e.g., feed and retract / hoist) such that drill bit 30 rotates and moves up and down, respectively. Drill bit 30 may also reciprocate (e.g., when a down-the-hole hammer is added to the drill string, such as at the top of drill string 28 near rotary head 26, or at the bottom of drill string 28 behind drill bit 30).
[0019] Mobile drilling machine 10 may include, as part of machinery 14, an air compressor (not shown), and drill string 28 may include an airline (not shown) for supplying bailing air from the air compressor through an interior of drill string 28, including through an interior of thread saver assembly 60, as well as through drill bit 30, into hole 50. The bailing air may clear out rubble from within hole 50 and may cool drill bit 30.
[0020] FIG. 2 is a schematic block diagram of control system 100 for adjusting parameters during the drilling operation by mobile drilling machine 10, in accordance with some aspects of the disclosure. During drilling of hole 50 with drill string 28 of mobile drilling machine 10, control system 100 may adjust various parameters of drill string 28, in order to optimize the drilling operation, as further discussed. By way of example, the parameters of drill string 28 that may be controlled or adjusted may include one or more of the following: collar feed maximum speed; drill flushing pressure threshold; air flow; water flow; drill fee maximum speed; drill flushing pressure; rotation adaption; drill speed; water injection; drill bit load limit; drill rotation torque limit; or drill retraction rate, among other parameters. Each of the parameters may have a range of permissible values, within which a specific, predetermined value may be set, to optimize operation of drill string 28.
[0021] In some instances, control system 100 may include one or more controllers, which may embody a single microprocessor or multiple microprocessors that may include systems for performing any of the operations mentioned herein. In some instances, control system 100 may include a memory, a secondary storage device, a processor, such as a central processing unit, or any other systems for accomplishing a task consistent with the present disclosure. The memory or secondary storage device associated with control system 100 may be non-transitory computer-readable media that stores data and / or software routines that may assist control system 100 in performing its functions, such as the functions of method or process discussed with reference to FIG. 2. Further, the memory or secondary storage device associated with control system 100 may also store data received from the various inputs or sensors associated with the mobile drilling machine 10, including the data discussed below. Numerous commercially available microprocessors may be configured to perform one or more of the functions of control system 100. In some instances, control system 100 may include a general machine controller capable of controlling numerous other machine functions. Various other known circuits may be associated with control system 100, including signal-conditioning circuitry, communication circuitry, hydraulic or other actuation circuitry, or other appropriate circuitry.
[0022] As shown in FIG. 2, in some instances, control system 100 may include a classifier module 110, a genetic algorithm module 120, a parameter setpoint module 130, a control module 140, and machine measurements 160. In some aspects, as FIG. 2 shows, classifier module 110 may receive data 141 and data 151 as inputs, data 141 representing specific values of one or more parameters used to control operation of drill string 28, which may represent an expected or desired operation of drill string 28, and data 151 representing a monitored or measured drilling output that is based on actual operation of drill string 28 during the drilling of hole 50 in the ground surface, as further described below.
[0023] Based on data 141 and data 151, classifier module 110 may determine ranges of permissible values for one or more of the parameters controlling operation of drill string 28, during the drilling operation that drills hole 50 in the ground surface. In some instances, the parameters may include all of the parameters used to control drill string 28. In some instances, the parameters may be a subset of (e.g., at least one but less than all of) the parameters. Based on data 141 and data 151 which classifier module 110 receives as inputs, classifier module 110 may output data 111 that includes a subset of parameters of all available parameters controlling operation of drill string 28, and may output, for each parameter of the subset of parameters, ranges of permissible values.
[0024] In some aspects, classifier module 110 may include a neural network learning and classification system 115 (“neural network 115”). For example, neural network 115 may receive data 141 and data 151 as inputs to an input layer 116. Neural network 115 may process information received in input layer 116 with one or more hidden layers 117. Neural network 115 may output information processed by one or more hidden layers 117 to an output layer 118. Output layer 118 may output, as data 111, the subset of parameters of all available parameters controlling operation of drill string 28, data 111 including the ranges of permissible values for the parameters controlling operation of drill string 28.
[0025] As FIG. 2 illustrates, control system 100 may include genetic algorithm module 120. In some aspects, genetic algorithm module 120 may receive, as an input, data 111 that is output from classifier module 110. Thus, genetic algorithm module 120 may receive, as an input, ranges of permissible values for the parameters of the subset of parameters controlling operation of drill string 28.
[0026] Genetic algorithm module 120 also may receive as an input a cost function 121. In some aspects, cost function 121 may include a value corresponding to performance of drill string 28 and lifetime of consumables of drill string 28. In some instances, there is a generally inverse relationship between performance and lifetime of consumables. For example, in some aspects, a value of cost function 121 may be set to maximize performance (e.g., to minimize the time to complete the drilling of hole 50 in the ground surface), regardless of the impact on the lifetime of consumables of drill string 28. In some other aspects, the value of cost function 121 may be set to maximize the lifetime of the consumable (e.g., to minimize the number of times drill bit 30 is replaced), regardless of the impact on the performance of drill string 28. In some instances, when the value of cost function 121 is set to maximize the performance of drill string 28, the lifetime of consumables may not be maximized, and in some aspects the lifetime of consumables may be minimized. In some other aspects, when the value of cost function 121 is set to maximize the lifetime of consumables of drill string 28, the performance may not be maximized, and in some instances the performance may be minimized, such that it takes a maximum amount of time to drill hole 50 to its final depth in the ground surface with drill string 28.
[0027] In some aspects, an operator of mobile drilling machine 10 may set the value of cost function 121. For example, an operator within operator cab 22 may set the value for cost function 121, such as through an input device—e.g., input device 40 in operator cab 22. In some aspects, the input device may require selection of either one of two settings—either a setting maximizing performance, or a setting maximizing lifetime of consumables. In some aspects, the input device may require selection by the operator of one of a discrete number of settings, which may include an extreme setting maximizing the performance of drill string 28, an extreme setting maximizing lifetime of consumables of drill string 28, and one or more intermediate settings between or among the extreme settings. In some aspects, the input device may provide a continuum of selectable cost functions 121, such as by providing a spectrum of selectable settings with an extreme setting maximizing performance on one end, and an extreme setting maximizing lifetime of consumables on the other end, and a number of selectable settings between the extreme settings. In such a setup, the operator may set the value of cost function 121 anywhere along the spectrum. In some instances, some of the settings balance performance against lifetime of consumables, such that a setting increasing performance decreases the lifetime of consumables, and vice versa.
[0028] In some instances, control system 100 may communicate to the operator or to another person or system information regarding performance and lifetime of consumables for the set value of cost function 121. Thus, for example, in some instances, a display associated with input device 40 within operator cab 22 may display an expected time to drill hole 50 in the ground surface, as well as an expected lifetime of the consumable components, corresponding to the set value of cost function 121. Thus, when the operator contemplates setting the value of cost function 121, the operator may be able to see the performance and lifetime of consumables at various values, before the operator sets the specific value of cost function 121.
[0029] As discussed, genetic algorithm module 120 may receive, as an input, data 111 that is output from classifier module 110, which includes the ranges of permissible values for one or more parameters controlling operation of drill string 28. Based on the selected value of cost function 121 that also is received by genetic algorithm module 120, genetic algorithm module 120 may determine, for the one or more parameters controlling operation of drill string 28, specific values within the range of permissible values. The specific values for the one or more parameters may represent optimal parameters based on the set value of cost function 121. Thus, for example, when the value of cost function 121 is set to maximize performance (e.g., minimize the time it take to drill hole 50 in the ground surface), genetic algorithm module 120 may determine specific values for parameters that cause drill string 28 to decrease to a minimum a time it take to drill hole 50, regardless of the impact on the lifetime of consumables. In another example, when the value of cost function 121 is set to maximize lifetime of consumables (e.g., minimize the number of times consumables such as drill bit 30 are replaced), genetic algorithm module 120 may determine specific values for parameters that control operation of drill string 28 to decrease to a minimum a number of times consumables are replaced, regardless of how long it takes to drill hole 50 in the ground surface with drill string 28. Genetic algorithm module 120 may output the determined, specific values for the parameters as data 123.
[0030] As FIG. 2 shows, control system 100 may include parameter setpoint module 130. Parameter setpoint module 130 may receive, as an input, data 123 output from genetic algorithm module 120. Parameter setpoint module 130 may also store or otherwise receive current values for the parameters currently controlling operation of drill string 28. As discussed, data 123 output from genetic algorithm module 120 may include specific values for parameters controlling operation of drill string 28. Parameter setpoint module 130 may compare the received values from data 123, to the current values of the parameters controlling operation of drill string 28. When parameter setpoint module 130 determines that there is a difference between the values for a parameter from data 123, and the current value of the parameter, parameter setpoint module 130 may output, as data 131, the specific and desired value of the parameter from data 123. Thus, parameter setpoint module 130 may control or adjust operation of drill string 28 based on the output of genetic algorithm module 120, and based on the value of cost function 121.
[0031] As illustrated in FIG. 2, control system 100 may include control module 140. Control module 140 may receive, as an input, data 131 output from parameter setpoint module 130, which includes specific desired values for parameters controlling operation of drill string 28. Control module 140 may send the settings to various components that control operation of drill string 28, so that drill string 28 operates in accordance with the specific desired values for each of the parameters—e.g., such that drill string 28 operates in accordance with the values output by parameter setpoint module 130. Restated, control module 140 controls operation of drill string 28 taking into account the value of cost function 121. In order to further control operation of drill string 28, control module 140 may output, as data 141, the control commands based on the values received from parameter setpoint module 130. In some instances, as FIG. 2 shows, control module 140 may output data 141 to classifier module 110. As discussed, data 141 includes specific values for parameters controlling operation of drill string 28.
[0032] As FIG. 2 further shows, classifier module 110 also may receive, as an input, data 151, which represents a monitored drilling output. In some instances, data 151 may represent measured or actual operating conditions of drill string 28 during the drilling operation of hole 50 in the ground surface, which may differ from the set or expected operation of drill string 28. For example, data 151 may include rotation speed, adjusted or actual penetration rate, or other conditions, of drill string 28. The machine measurements 160 may be used to determine a difference between the expected operation of drill string 28, and the actual measured operation of drill string 28. Classifier module 110 may compensate for the difference, when providing output to genetic algorithm module 120.
[0033] As FIG. 2 illustrates, and as discussed above, based on data 141 and data 151, classifier module 110 provides, as an output, data 111, which includes ranges of permissible values for a subset of parameters of all parameters controlling operation of drill string 28. Accordingly, control system 100 may continue operation as described above.
[0034] FIG. 3 illustrates a flowchart of an exemplary method 300 associated with mobile drilling machine 10, according to some aspects of the invention. Method 300 may provide adjustment of drill parameters of drill string 28 during a drilling operation. As FIG. 3 illustrates, method 300 may include a step 310 of inputting, such as by an operator, a value for cost function 121, the value corresponding to the performance of drill string 28 and the lifetime of a consumable of drill string 28, as shown and described. Although method 300 shows step 310 as a preliminary step, step 310 may be performed at any time, such as before, during, between, or after any other step or steps. Method 300 may include a step 320 of outputting, by classifier module 110, a range of permissible values for each parameter of the set of parameters. As set forth, classifier module 110 may utilize neural network 115. Method 300 may include a step 330 of receiving, by genetic algorithm module 120, the output from classifier module 110. Method 300 may include a step 340 of outputting, by genetic algorithm module 120, predetermined values for one or more of the parameter of the set of parameters for controlling operation of the drill string, based on the value of cost function 121.
[0035] Although FIG. 3 and its description describe exemplary steps 310, 320, 330, 340, method 300 may include more, fewer, or other steps. Further, the steps of method 300 may be in a different order than shown or described.INDUSTRIAL APPLICABILITY
[0036] The disclosed control system 100 may be used in mobile drilling machines 10 to optimize performance of drill strings, as described. More specifically, as discussed, in some aspects, control system 100 may permit an operator to set cost function 121 to optimize the drilling operation, the optimization based on a preference or requirement of the operator. For example, as discussed, in some aspects, the operator can set cost function 121 to optimize the performance of the drilling operation, e.g., to reduce to a minimum a time required to drill hole 50 in the ground surface. In another example, the operator can set cost function 121 to optimize the lifetime of consumable components during the drilling operation—e.g., to reduce to a minimum a number of times consumables, such as drill bit 30, require replacement. In some instances, the operator may see, such as on a display associated with input device 40 within operator cab 22, how changes to cost function 121 among different values increases or decreases performance while decreasing or increasing lifetime of consumables, such that the operator may determine an acceptable level for each of performance and lifetime of consumables.
[0037] Accordingly, control system 100 may allow the operator to better optimize the drilling operation without requiring the operator to manually set or change any specific parameter used to control drill string 28. Instead, as discussed, neural network 115 provides permissible ranges of values for the parameters controlling operation of drill string 28, and, based on the value of cost function 121 set by the operator, genetic algorithm module 120 sets specific, predetermined values within the ranges of permissible values, and subsequently controls operation of drill string 28. Thus, control system 100 allows the operator to simply and better optimize operation of drill string 28 to achieve a specific result—better optimization of performance, or lifetime of consumables.
[0038] It will be apparent to those skilled in the art that various modifications and variations may be made to the disclosed system without departing from the scope of the disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
Claims
1. A control system for adjusting operation of a drill string of a drilling machine, the control system comprising:a classifier module including a neural network configured, during a drilling process, to classify a ground condition, and based on the ground condition to output a set of parameters for controlling operation of the drill string, and a range of permissible values for each parameter of the set of parameters;a genetic algorithm module configured to receive as inputs i) the output from the classifier module, and ii) a cost function, the genetic algorithm module configured to output, for each parameter of the set of parameters, a predetermined value within the range of permissible values, based on the inputs,wherein the cost function includes a value corresponding to performance of the drill string and lifetime of consumables of the drill string; anda parameter setpoint module configured to receive, as an input, the predetermined values, the parameter setpoint module configured to adjust operation of the drill string based on the predetermined values.
2. The control system of claim 1, wherein the genetic algorithm module is configured to receive the cost function from an operator of the drilling machine.
3. The control system of claim 1, wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of the consumables.
4. The control system of claim 1, wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of a drill bit of the drill string.
5. The control system of claim 1, wherein the value of the cost function varies among a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, a second extreme value to maximize a lifetime of the consumables, and at least one intermediate value between the first and second extreme values.
6. The control system of claim 1, wherein the control system further comprises an input device in an operator cab of the drilling machine, wherein the genetic algorithm module is configured to receive the cost function from the input device.
7. The control system of claim 1, wherein the control system further comprises a display, wherein the display is configured to display a lifetime of at least one consumable of the consumables and an expected time to drill a hole, based on a value of the cost function.
8. The control system of claim 1, wherein the classifier module is configured to output the set of parameters for controlling operation of the drill string, and the range of permissible values for each parameter of the set of parameters, based on a difference between an expected operation of the drill string and a measured operation of the drill string.
9. A drilling machine, comprising:a frame;a drill string supported on the frame; anda control system for adjusting operation of the drill string, the control system comprising:a neural network configured to output a set of parameters for controlling operation of the drill string, and a range of permissible values for each parameter of the set of parameters;a genetic algorithm module configured to receive as inputs i) the output from the neural network and ii) a cost function, the genetic algorithm module configured to output, for each parameter of the set of parameters, a predetermined value within the range of permissible values, based on the inputs,wherein the cost function includes a value corresponding to performance of the drill string and lifetime of a consumable of the drill string; anda parameter setpoint module configured to receive, as an input, the predetermined values, the parameter setpoint module configured to adjust operation of the drill string based on the predetermined values.
10. The drilling machine of claim 9, further comprising:an input device configured to receive the cost function from an operator of the drilling machine.
11. The drilling machine of claim 9, wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of the consumable.
12. The drilling machine of claim 9, wherein the value of the cost function varies between a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, and a second extreme value to maximize a lifetime of a drill bit of the drill string.
13. The drilling machine of claim 9, wherein the value of the cost function varies among a first extreme value to maximize performance by minimizing a time to drill a hole with the drill string, a second extreme value to maximize a lifetime of the consumable, and at least one intermediate value between the first and second extreme values.
14. The drilling machine of claim 9, wherein the neural network is configured to output the set of parameters for controlling operation of the drill string, and the range of permissible values for each parameter of the set of parameters, based on a difference between an expected operation of the drill string and a measured operation of the drill string.
15. The drilling machine of claim 9, wherein the neural network is configured to output, as the set of parameters, a subset of a group of parameters.
16. A method of adjusting drill parameters of a drill string of a drilling machine during a drilling operation, the method comprising:inputting, by an operator, a value for a cost function, the value corresponding to performance of the drill string and lifetime of a consumable of the drill string; andoutputting, by a genetic algorithm module, predetermined values for each parameter of a set of parameters for controlling operation of the drill string, based on the value of the cost function.
17. The method of claim 16, further comprising:outputting, by a neural network, a range of permissible values for each parameter of the set of parameters,wherein the outputting, by the genetic algorithm module, comprises outputting predetermined values within the range of permissible values received from the neural network, for each parameter of the set of parameters.
18. The method of claim 16, further comprising:outputting, by a classifier module, a range of permissible values for each parameter of the set of parameters,wherein the outputting, by the genetic algorithm module, comprises outputting predetermined values within the range of permissible values received from the classifier module, for each parameter of the set of parameters.
19. The method of claim 16, wherein the inputting comprises inputting, by the operator, on an input device in a cab of the drilling machine.
20. The method of claim 16, wherein the inputting comprises setting a value of the cost function between a first extreme value that maximizes performance by minimizing a time to drill a hole with the drill string, and a second extreme value that maximizes a lifetime of a drill bit of the drill string.