Structure optimization method and system for rubber crawler walking device

Abstract

The invention discloses a structure optimization method and system of a rubber crawler walking device, and relates to the technical field of engineering equipment optimization, environmental working condition parameters are obtained, and a crawler walking force optimization function of the rubber crawler walking device is constructed by taking the maximum comprehensive crawler walking force as an optimization target; according to the environment working condition parameters and a preset rubber crawler walking device model, a crawler simulation model is obtained, the crawler walking force optimization function is optimized and solved according to the crawler simulation model, target crawler parameters are obtained, the target crawler parameters are adopted for a load stress test, and optimized crawler parameters corresponding to the rubber crawler walking device are obtained. The technical problems that an existing crawler walking device is mainly a rubber crawler belt, but the existing rubber crawler belt cannot provide large mechanical traction force and is not tightly attached to the road surface, the pressure of the rubber crawler belt on the road surface is difficult to distribute evenly, and the reliability of the crawler walking device is reduced are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering equipment optimization, and in particular to a structure optimization method and system for a rubber crawler walking device. Background Art

[0002] At present, in the process of construction, transformation, operation and maintenance of power systems, the timeliness and efficiency of replacing faulty equipment in power systems are important evaluation indicators for judging the comprehensive management level of power grids. When substations replace faulty equipment, due to the complex working conditions in the complex environment of substations, crawler-type special operation machinery and equipment are usually used to cooperate with maintenance personnel to carry out replacement operations to adapt to complex working conditions. However, the crawler walking device of the current crawler-type special operation machinery and equipment is difficult to adapt to a variety of complex road conditions, resulting in poor stability of crawler-type special operation machinery and equipment when passing through complex roads, thereby reducing the replacement efficiency of faulty equipment. Therefore, it is very important to improve the stability of crawler-type special operation machinery and equipment when passing through complex roads.

[0003] The existing crawler walking device is mainly a rubber crawler, but the rubber crawler currently fails to provide a large mechanical traction force, does not fit the road surface tightly enough, and it is difficult to evenly distribute the pressure of the rubber crawler on the road surface, which reduces the reliability of the crawler walking device. Summary of the invention

[0004] The present invention provides a structural optimization method and system for a rubber crawler walking device, which solves the technical problem that the existing crawler walking device is mainly a rubber crawler, but the rubber crawler cannot provide a large mechanical traction force, does not fit the road surface tightly enough, and it is difficult to evenly distribute the pressure of the rubber crawler on the road surface, which reduces the reliability of the crawler walking device.

[0005] A first aspect of the present invention provides a method for optimizing the structure of a rubber crawler walking device, comprising:

[0006] Obtain environmental working condition parameters, take the maximum comprehensive crawler walking force as the optimization goal, and construct the crawler walking force optimization function of the rubber crawler walking device;

[0007] According to the environmental working condition parameters and the preset rubber crawler walking device model, a crawler simulation model is obtained;

[0008] Optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters;

[0009] The target crawler track parameters are used to carry out a load stress test to obtain the optimized crawler track parameters corresponding to the rubber crawler track walking device.

[0010] Optionally, the crawler walking force optimization function is specifically:

[0011]

[0012] in, For traction, is walking resistance, is the comprehensive evaluation value, is the first weight coefficient, is the second weight coefficient, is the internal friction coefficient, is the rolling resistance coefficient, For machine quality, is the acceleration due to gravity, is the weight of the whole machine, is the steering resistance coefficient, is the track ground contact length, is the track gauge, It is the longitudinal eccentricity between the center of gravity of the drilling rig and the ground contact centroid of the walking mechanism.

[0013] Optionally, the step of obtaining a crawler simulation model according to the environmental working condition parameters and a preset rubber crawler walking device model comprises:

[0014] Constructing a three-dimensional road surface model using the environmental operating condition parameters;

[0015] Performing geometric optimization processing on the three-dimensional road surface model to obtain a target road surface model;

[0016] The target road surface model is coupled with a preset rubber crawler walking device model to obtain a crawler simulation model.

[0017] Optionally, the step of optimizing and solving the track walking force optimization function according to the track simulation model to obtain target track parameters includes:

[0018] Constructing an initial track structure particle group, wherein each initial particle of the initial track structure particle group corresponds to a track width, a track pitch, a track material, a track pattern, a track tension, a track wheel diameter, a track wheel data, a track thickness, and a track contact area;

[0019] Determining the fitness corresponding to each of the initial particles according to each of the initial particles, the crawler simulation model and the crawler walking force optimization function;

[0020] The position of the initial particle with the largest fitness in the initial track structure particle swarm is taken as the global optimal position, the speed and position of each initial particle are iteratively updated through the particle swarm algorithm, and the global optimal position when the iteration is updated to meet the iteration stop condition is taken as the target track parameter.

[0021] Optionally, the step of determining the fitness corresponding to each of the initial particles according to each of the initial particles, the crawler simulation model and the crawler walking force optimization function comprises:

[0022] Inputting each of the initial particles into the crawler simulation model respectively to obtain walking-related parameters corresponding to each of the initial particles;

[0023] Each of the walking related parameters is input into the crawler walking force optimization function to obtain the fitness corresponding to each of the initial particles.

[0024] Optionally, the step of performing a load stress test using the target track parameters to obtain optimized track parameters corresponding to the rubber track walking device includes:

[0025] constructing a track finite element model using the target track parameters;

[0026] Using the crawler finite element model to conduct a dynamic simulation test under a preset load stress field to obtain a target stress value;

[0027] Determining that the target stress value is less than or equal to a preset yield strength threshold;

[0028] If the target stress value is greater than the yield strength threshold, the step of optimizing and solving the track walking force optimization function according to the track simulation model to obtain target track parameters is skipped until the target stress value is less than or equal to the yield strength threshold;

[0029] If the target stress value is less than or equal to the yield strength threshold, the target track parameter is used as the optimized track parameter corresponding to the rubber track walking device.

[0030] A second aspect of the present invention provides a structural optimization system for a rubber crawler walking device, comprising:

[0031] The acquisition module is used to obtain environmental working condition parameters, take the maximum comprehensive crawler walking force as the optimization target, and construct the crawler walking force optimization function of the rubber crawler walking device;

[0032] A construction module is used to obtain a crawler simulation model according to the environmental working condition parameters and a preset rubber crawler walking device model;

[0033] An analysis module, used for optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters;

[0034] The verification module is used to perform a load stress test using the target track parameters to obtain the optimized track parameters corresponding to the rubber track walking device.

[0035] A third aspect of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the structural optimization method of the rubber crawler walking device as described in any one of the above items.

[0036] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed, implements the structural optimization method of the rubber crawler walking device as described in any one of the above items.

[0037] A fifth aspect of the present invention provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer executes the structural optimization method of the rubber crawler walking device as described in any one of the above items.

[0038] It can be seen from the above technical solutions that the present invention has the following advantages:

[0039] The present invention obtains environmental working condition parameters and takes the maximum comprehensive track walking force as the optimization target, constructs a track walking force optimization function of a rubber track walking device, optimizes and solves the track walking force optimization function according to a track simulation model to obtain target track parameters, and then obtains the optimized track parameters after verification through a load stress test on the target track parameters. It overcomes the technical problems that the existing rubber tracks fail to provide greater mechanical traction, do not fit the road surface tightly enough, make it difficult to evenly distribute the pressure of the rubber tracks on the road surface, and reduce the reliability of the track walking device. The present invention optimizes and solves the track walking force optimization function through a track simulation model to obtain target track parameters, and then corrects the target track parameters according to the test structure of the target track parameter load stress test, thereby obtaining optimized track parameters and improving the reliability of the track walking device. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 A flowchart of the steps of a method for optimizing the structure of a rubber crawler walking device provided in Embodiment 1 of the present invention;

[0042] Figure 2A flowchart of the steps of a method for optimizing the structure of a rubber crawler walking device provided in the second embodiment of the present invention;

[0043] Figure 3 A schematic diagram of the structure of a rubber crawler walking device provided in the second embodiment of the present invention;

[0044] Figure 4 A structural block diagram of a structural optimization system for a rubber crawler walking device provided in Embodiment 3 of the present invention;

[0045] Figure 5 This is a structural block diagram of a computer device provided in Embodiment 4 of the present invention.

[0046] The reference numerals are as follows:

[0047] 1. Driving wheel; 2. Driving mechanism; 3. Frame; 4. Tensioning wheel; 5. Tensioning device; 6. Supporting wheel; 7. Tugboat. DETAILED DESCRIPTION

[0048] The embodiments of the present invention provide a structural optimization method and system for a rubber crawler walking device, which is used to solve the technical problem that the existing crawler walking device is mainly a rubber crawler, but the rubber crawler currently fails to provide a large mechanical traction force, does not fit the road surface tightly enough, and it is difficult to evenly distribute the pressure of the rubber crawler on the road surface, which reduces the reliability of the crawler walking device.

[0049] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] See also Figure 1 , Figure 1 A flowchart of the steps of a method for structural optimization of a rubber crawler walking device provided in Example 1 of the present invention.

[0051] The present invention provides a method for optimizing the structure of a rubber crawler walking device, comprising:

[0052] Step 101, obtaining environmental working condition parameters, taking the maximum comprehensive crawler walking force as the optimization target, and constructing a crawler walking force optimization function of the rubber crawler walking device;

[0053] In the embodiment of the present invention, the environmental working condition parameters in the substation are obtained, and the first optimization function is constructed with the goal of maximizing the traction force of the rubber crawler walking device. The second optimization function is constructed with the goal of minimizing the walking resistance of the rubber crawler walking device, and according to the preset weight parameters, the first optimization function and the second optimization function are coupled with the maximum comprehensive crawler walking force as the optimization goal to obtain the crawler walking force optimization function of the rubber crawler walking device.

[0054] It should be noted that the comprehensive track running force refers to the comprehensive rating value of the rubber track running device.

[0055] Step 102, obtaining a crawler simulation model according to environmental working condition parameters and a preset rubber crawler walking device model;

[0056] In the embodiment of the present invention, based on the environmental working condition parameters, a three-dimensional road surface model is constructed using simulation engineering software (such as ANSYS, ADAMS, etc.), and then the three-dimensional road surface model is coupled with a preset rubber crawler walking device model to obtain a crawler simulation model.

[0057] It should be noted that the preset rubber crawler running gear model is a rubber crawler running gear model established in advance by simulation engineering software according to the geometric structure of the rubber crawler running gear.

[0058] Step 103: Optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters;

[0059] In the embodiment of the present invention, the track simulation model and the track travel force optimization function are used as the adaptation function of the optimization algorithm, and the optimization algorithm is used to optimize and solve the track travel force optimization function to obtain the target track parameters.

[0060] It should be noted that the optimization algorithm may be a particle swarm algorithm, a genetic algorithm or an annealing algorithm.

[0061] Step 104: Perform a load stress test using the target track parameters to obtain optimized track parameters corresponding to the rubber track walking device.

[0062] In the embodiment of the present invention, a track finite element model is constructed according to the target track parameters, and a load stress test is performed using the track finite element model to obtain optimized track parameters corresponding to the rubber track walking device.

[0063] In an embodiment of the present invention, the present invention obtains environmental working condition parameters and takes the maximum comprehensive track walking force as the optimization target to construct a track walking force optimization function of a rubber track walking device, optimizes and solves the track walking force optimization function according to a track simulation model to obtain target track parameters, and then obtains the optimized track parameters after verification through a load stress test on the target track parameters. It overcomes the technical problems that the existing rubber tracks fail to provide greater mechanical traction, do not fit the road surface tightly enough, make it difficult to evenly distribute the pressure of the rubber tracks on the road surface, and reduce the reliability of the track walking device. The present invention optimizes and solves the track walking force optimization function through a track simulation model to obtain target track parameters, and then corrects the target track parameters according to the test structure of the target track parameter load stress test, thereby obtaining optimized track parameters and improving the reliability of the track walking device.

[0064] See also Figure 2 , Figure 2 A flowchart of the steps of a method for structural optimization of a rubber crawler walking device provided in Embodiment 2 of the present invention.

[0065] The present invention provides a method for optimizing the structure of a rubber crawler walking device, comprising:

[0066] Step 201, obtaining environmental working condition parameters, taking the maximum comprehensive crawler walking force as the optimization target, and constructing a crawler walking force optimization function of the rubber crawler walking device;

[0067] In an embodiment of the present invention, referring to Table 1, according to the road conditions in the substation, the corresponding adhesion coefficient is obtained as the environmental operating condition parameter, and the track walking force optimization function of the rubber track walking device is constructed with the maximum comprehensive track walking force as the optimization goal.

[0068] Table 1

[0069]

[0070] It should be noted that the track walking force optimization function is specifically:

[0071]

[0072] in, For traction, is walking resistance, is the comprehensive evaluation value, is the first weight coefficient, is the second weight coefficient, is the internal friction coefficient, is the rolling resistance coefficient, For machine quality, is the acceleration due to gravity, is the weight of the whole machine, is the steering resistance coefficient, is the track ground contact length, is the track gauge, It is the longitudinal eccentricity between the center of gravity of the drilling rig and the ground contact centroid of the walking mechanism.

[0073] Step 202, obtaining a crawler simulation model according to environmental working condition parameters and a preset rubber crawler walking device model;

[0074] Further, step 202 includes the following sub-steps:

[0075] S11, constructing a three-dimensional road surface model using environmental working condition parameters;

[0076] In the embodiment of the present invention, an initial road surface three-dimensional model is constructed according to the geometric structure of the road surface, and environmental working condition parameters are input into the initial road surface three-dimensional model to obtain the road surface three-dimensional model.

[0077] S12, performing geometric optimization processing on the road surface three-dimensional model to obtain a target road surface model;

[0078] In an embodiment of the present invention, the geometric defects of the three-dimensional road surface model are checked and repaired (for example, overlapping surfaces, non-manifold geometric bodies, etc. in the model are removed to ensure that the geometric features of the road surface such as undulation and roughness are complete and reasonable) to obtain a target road surface model.

[0079] S13, coupling the target road surface model with the preset rubber crawler walking device model to obtain a crawler simulation model.

[0080] In an embodiment of the present invention, the target road surface model is coupled with a preset rubber crawler walking device model, and a suitable grid type is selected according to the complexity of the coupled model and the analysis requirements, and the coupled model is meshed to obtain a crawler simulation model.

[0081] Step 203, constructing an initial track structure particle group, wherein each initial particle of the initial track structure particle group corresponds to a track width, a track pitch, a track material, a track pattern, a track tension, a track wheel diameter, a track wheel data, a track thickness and a track contact area;

[0082] In an embodiment of the present invention, an initial track structure particle group is constructed according to the rubber track parameters of the rubber track walking device, wherein each initial particle of the initial track structure particle group corresponds to the track width, track pitch, track material, track pattern, track tension, track wheel diameter, track wheel data, track thickness and track contact area.

[0083] It should be noted that, see Figure 3As shown, the rubber crawler walking device is based on a frame 3, on which a driving mechanism 2, a tensioning wheel 4, a tensioning device 5, a supporting roller 6, a tug wheel 7 and a walking mechanism are arranged. The driving mechanism 2 includes a hydraulic pump, a hydraulic motor, a walking control valve, a walking steering valve, a hydraulic oil tank and a reducer. The hydraulic oil tank is connected to the hydraulic pump, the walking control valve and the walking steering valve are both connected to the hydraulic oil tank, and the output shaft of the hydraulic motor is connected to the reducer. The walking mechanism includes a driving wheel 1, a track chain, supporting rollers and a tug wheel. Among them, the driving wheel 1 includes a main driving wheel and a slave driving wheel, both of which are meshed and connected with the track chain, and the main driving wheel and the slave driving wheel are driven by the track chain. The main driving wheel is connected to the output end of the reducer, and the main driving wheel drives the track chain to rotate, and then the driven wheel supports the track chain, so that the vehicle can walk on the ground, playing a supporting and traction role. Therefore, the key parts and components of the rubber track traveling device (i.e. driving wheels, rubber tracks and other key components) are quantified to obtain the track width, track pitch, track material, track pattern, track tension, track wheel diameter, track wheel data, track thickness and track contact area of ​​the rubber track traveling device.

[0084] Step 204, determining the fitness corresponding to each initial particle according to each initial particle, the crawler simulation model and the crawler walking force optimization function;

[0085] Further, step 204 includes the following sub-steps:

[0086] S21, inputting each initial particle into the crawler simulation model respectively to obtain walking related parameters corresponding to each initial particle;

[0087] The walking-related parameters refer to the longitudinal eccentricity between the center of gravity of the drilling rig and the ground contact centroid of the walking mechanism in the crawler simulation model and the machine mass.

[0088] In the embodiment of the present invention, each initial particle is input into the crawler simulation model respectively to obtain the longitudinal eccentricity and machine mass of the drilling rig gravity center and the ground contact centroid of the walking mechanism in the crawler simulation model corresponding to each initial particle.

[0089] S22, inputting each walking-related parameter into the track walking force optimization function respectively to obtain the fitness corresponding to each initial particle.

[0090] In the embodiment of the present invention, the longitudinal eccentricity between the rig gravity center and the ground contact centroid of the walking mechanism and the machine mass in the crawler simulation model corresponding to each particle are respectively input into the crawler walking force optimization function to obtain the fitness corresponding to each initial particle.

[0091] Step 205: Taking the position of the initial particle with the largest fitness in the initial track structure particle swarm as the global optimal position, iteratively updating the speed and position of each initial particle through the particle swarm algorithm, and taking the global optimal position when the iteration is updated to meet the iteration stop condition as the target track parameter.

[0092] In an embodiment of the present invention, the position of the initial particle with the largest fitness is selected from the initial track structure particle group as the global optimal position, and the speed and position of each initial particle are iteratively updated through the particle swarm algorithm. When the iterative update reaches a preset number of iterations, the particle at the global optimal position is used as the target track parameter.

[0093] Step 206: Perform a load stress test using the target track parameters to obtain optimized track parameters corresponding to the rubber track walking device.

[0094] Further, step 206 includes the following sub-steps:

[0095] S31, constructing a track finite element model using target track parameters;

[0096] In the embodiment of the present invention, a finite element model of the track is constructed by using finite element analysis software (such as ANSYS) according to target track parameters.

[0097] S32, performing a dynamic simulation test using a track finite element model under a preset load stress field to obtain a target stress value;

[0098] The target stress value refers to the maximum stress value of the track finite element model during the dynamic simulation test.

[0099] In the embodiment of the present invention, a dynamic simulation test is performed on a rubber crawler walking device constructed by simulating target crawler parameters using a crawler finite element model under a preset load stress field to obtain a target stress value.

[0100] S33, determining that the target stress value is less than or equal to a preset yield strength threshold;

[0101] The yield strength threshold refers to the critical stress value when the rubber track walking device is deformed.

[0102] In an embodiment of the present invention, it is determined that the target stress value is less than or equal to a preset yield strength threshold (the yield strength threshold is determined according to the target crawler parameters).

[0103] S34, if the target stress value is greater than the yield strength threshold, jump to execute the step of optimizing and solving the track walking force optimization function according to the track simulation model to obtain the target track parameters, until the target stress value is less than or equal to the yield strength threshold;

[0104] In an embodiment of the present invention, when the target stress value is greater than the yield strength threshold, it means that the target track parameters do not meet the actual working conditions, and the execution is jumped to optimize and solve the track walking force optimization function according to the track simulation model to obtain the target track parameters until the target stress value is less than or equal to the yield strength threshold.

[0105] S35. If the target stress value is less than or equal to the yield strength threshold, the target track parameters are used as optimized track parameters corresponding to the rubber track walking device.

[0106] In the embodiment of the present invention, when the target stress value is less than or equal to the yield strength threshold, it means that the target track parameters meet the actual working condition requirements, and the target track parameters are used as the optimized track parameters corresponding to the rubber track walking device.

[0107] In an embodiment of the present invention, the present invention obtains environmental working condition parameters and takes the maximum comprehensive track walking force as the optimization target to construct a track walking force optimization function of a rubber track walking device, optimizes and solves the track walking force optimization function according to a track simulation model to obtain target track parameters, and then obtains the optimized track parameters after verification through a load stress test on the target track parameters. It overcomes the technical problems that the existing rubber tracks fail to provide greater mechanical traction, do not fit the road surface tightly enough, make it difficult to evenly distribute the pressure of the rubber tracks on the road surface, and reduce the reliability of the track walking device. The present invention optimizes and solves the track walking force optimization function through a track simulation model to obtain target track parameters, and then corrects the target track parameters according to the test structure of the target track parameter load stress test, thereby obtaining optimized track parameters and improving the reliability of the track walking device.

[0108] See also Figure 4 , Figure 4 This is a structural block diagram of a structural optimization system for a rubber crawler walking device provided in Example 3 of the present invention.

[0109] The present invention provides a structural optimization system for a rubber crawler walking device, comprising:

[0110] The acquisition module 301 is used to obtain environmental working condition parameters, take the maximum comprehensive crawler walking force as the optimization target, and construct the crawler walking force optimization function of the rubber crawler walking device;

[0111] A construction module 302 is used to obtain a crawler simulation model according to environmental working condition parameters and a preset rubber crawler walking device model;

[0112] The analysis module 303 is used to optimize and solve the crawler walking force optimization function according to the crawler simulation model to obtain the target crawler parameters;

[0113] The verification module 304 is used to perform a load stress test using the target track parameters to obtain the optimized track parameters corresponding to the rubber track walking device.

[0114] Furthermore, the track walking force optimization function is specifically:

[0115]

[0116] in, For traction, is walking resistance, is the comprehensive evaluation value, is the first weight coefficient, is the second weight coefficient, is the internal friction coefficient, is the rolling resistance coefficient, For machine quality, is the acceleration due to gravity, is the weight of the whole machine, is the steering resistance coefficient, is the track ground contact length, is the track gauge, It is the longitudinal eccentricity between the center of gravity of the drilling rig and the ground contact centroid of the walking mechanism.

[0117] Further, the construction module 302 includes:

[0118] The first construction submodule is used to construct a three-dimensional road surface model using environmental working condition parameters;

[0119] The geometry optimization submodule is used to perform geometry optimization on the three-dimensional road surface model to obtain the target road surface model;

[0120] The coupling submodule is used to couple the target road surface model with the preset rubber crawler walking device model to obtain a crawler simulation model.

[0121] Furthermore, the analysis module 303 includes:

[0122] The second construction submodule is used to construct an initial track structure particle group, wherein each initial particle of the initial track structure particle group corresponds to a track width, a track pitch, a track material, a track pattern, a track tension, a track wheel diameter, a track wheel data, a track thickness and a track contact area;

[0123] The first analysis submodule is used to determine the fitness corresponding to each initial particle according to each initial particle, the crawler simulation model and the crawler walking force optimization function;

[0124] The second analysis submodule is used to take the position of the initial particle with the largest fitness in the initial track structure particle swarm as the global optimal position, iteratively update the speed and position of each initial particle through the particle swarm algorithm, and use the global optimal position when the iteration is updated to meet the iteration stop condition as the target track parameter.

[0125] Furthermore, the first analysis submodule includes:

[0126] The first analysis unit is used to input each initial particle into the crawler simulation model to obtain the walking related parameters corresponding to each initial particle;

[0127] The second analysis unit is used to input various walking related parameters into the crawler walking force optimization function respectively to obtain the fitness corresponding to each initial particle.

[0128] Furthermore, the verification module 304 includes:

[0129] The second construction submodule is used to construct a crawler finite element model using target crawler parameters;

[0130] The third analysis submodule is used to perform a dynamic simulation test using a track finite element model under a preset load stress field to obtain a target stress value;

[0131] A fourth analysis submodule is used to determine whether the target stress value is less than or equal to a preset yield strength threshold;

[0132] If the target stress value is greater than the yield strength threshold, the step of optimizing and solving the track walking force optimization function according to the track simulation model to obtain the target track parameters is jumped to the execution until the target stress value is less than or equal to the yield strength threshold;

[0133] If the target stress value is less than or equal to the yield strength threshold, the target track parameters are used as the optimized track parameters corresponding to the rubber track walking device.

[0134] See also Figure 5 , Figure 5 This is a structural block diagram of a computer device provided in Embodiment 4 of the present invention.

[0135] An electronic device according to an embodiment of the present invention comprises: a memory 401 and a processor 402, wherein the memory 402 stores a computer program; when the computer program is executed by the processor 402, the processor 402 executes a structural optimization method for a rubber crawler walking device according to any of the above embodiments.

[0136] The memory 401 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. The memory 401 has a storage space 403 for a program code 413 for executing any method step in the above method. For example, the storage space 403 for the program code may include individual program codes 413 for implementing the various steps in the above method, respectively. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program code may be compressed, for example, in an appropriate form. When these codes are run by a computing and processing device, the computing and processing device performs the various steps in the method described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program code may be compressed, for example, in an appropriate form. When these codes are run by a computing and processing device, they cause the computing and processing device to execute the various steps in the structural optimization method of the rubber crawler walking device described above.

[0137] Embodiment 5 of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the structural optimization method of the rubber crawler walking device as described in any of the above embodiments is implemented.

[0138] Embodiment 6 of the present invention further provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer executes a structural optimization method for a rubber crawler walking device as in any of the above embodiments.

[0139] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0140] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0141] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0142] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0143] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0144] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the structure of a rubber crawler walking device, characterized in that: include: Obtain environmental working condition parameters, take the maximum comprehensive crawler walking force as the optimization goal, and construct the crawler walking force optimization function of the rubber crawler walking device; According to the environmental working condition parameters and the preset rubber crawler walking device model, a crawler simulation model is obtained; Optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters; The target crawler track parameters are used to carry out a load stress test to obtain the optimized crawler track parameters corresponding to the rubber crawler track walking device.

2. The structural optimization method of the rubber crawler walking device according to claim 1, characterized in that: The crawler walking force optimization function is specifically: in, For traction, is walking resistance, is the comprehensive evaluation value, is the first weight coefficient, is the second weight coefficient, is the internal friction coefficient, is the rolling resistance coefficient, For machine quality, is the acceleration due to gravity, is the weight of the whole machine, is the steering resistance coefficient, is the track ground contact length, is the track gauge, It is the longitudinal eccentricity between the center of gravity of the drilling rig and the ground contact centroid of the walking mechanism.

3. The structural optimization method of the rubber crawler walking device according to claim 1, characterized in that: The step of obtaining a crawler simulation model according to the environmental working condition parameters and a preset rubber crawler walking device model comprises: Constructing a three-dimensional road surface model using the environmental operating condition parameters; Performing geometric optimization processing on the three-dimensional road surface model to obtain a target road surface model; The target road surface model is coupled with a preset rubber crawler walking device model to obtain a crawler simulation model.

4. The structural optimization method of the rubber crawler walking device according to claim 1, characterized in that: The step of optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters includes: Constructing an initial track structure particle group, wherein each initial particle of the initial track structure particle group corresponds to a track width, a track pitch, a track material, a track pattern, a track tension, a track wheel diameter, a track wheel data, a track thickness, and a track contact area; Determining the fitness corresponding to each of the initial particles according to each of the initial particles, the crawler simulation model and the crawler walking force optimization function; The position of the initial particle with the largest fitness in the initial track structure particle swarm is taken as the global optimal position, the speed and position of each initial particle are iteratively updated through the particle swarm algorithm, and the global optimal position when the iteration is updated to meet the iteration stop condition is taken as the target track parameter.

5. The structural optimization method of the rubber crawler walking device according to claim 4, characterized in that: The step of determining the fitness corresponding to each of the initial particles according to each of the initial particles, the crawler simulation model and the crawler walking force optimization function comprises: Inputting each of the initial particles into the crawler simulation model respectively to obtain walking-related parameters corresponding to each of the initial particles; Each of the walking related parameters is input into the crawler walking force optimization function to obtain the fitness corresponding to each of the initial particles.

6. The structural optimization method of the rubber crawler walking device according to claim 1, characterized in that: The step of performing a load stress test using the target track parameters to obtain the optimized track parameters corresponding to the rubber track walking device comprises: constructing a track finite element model using the target track parameters; Using the crawler finite element model to conduct a dynamic simulation test under a preset load stress field to obtain a target stress value; Determining that the target stress value is less than or equal to a preset yield strength threshold; If the target stress value is greater than the yield strength threshold, the step of optimizing and solving the track walking force optimization function according to the track simulation model to obtain target track parameters is skipped until the target stress value is less than or equal to the yield strength threshold; If the target stress value is less than or equal to the yield strength threshold, the target track parameter is used as the optimized track parameter corresponding to the rubber track walking device.

7. A structural optimization system for a rubber crawler walking device, characterized in that: include: The acquisition module is used to obtain environmental working condition parameters, take the maximum comprehensive crawler walking force as the optimization target, and construct the crawler walking force optimization function of the rubber crawler walking device; A construction module is used to obtain a crawler simulation model according to the environmental working condition parameters and a preset rubber crawler walking device model; An analysis module, used for optimizing and solving the crawler walking force optimization function according to the crawler simulation model to obtain target crawler parameters; The verification module is used to perform a load stress test using the target track parameters to obtain the optimized track parameters corresponding to the rubber track walking device.

8. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the structural optimization method of the rubber crawler walking device as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the structural optimization method of the rubber crawler walking device according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions, wherein when the program instructions are executed by a computer, the computer executes the structural optimization method of the rubber crawler walking device as described in any one of claims 1-6.

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