Optimization design method for cantilever structure of automatic car cleaning robot

Abstract

The invention provides an automatic car cleaning robot cantilever structure optimization design method, which comprises the steps of simulating stress states of a cantilever under different working conditions by adopting a finite element analysis method aiming at a candidate high-strength light alloy material, obtaining a stress-strain cloud picture, and judging whether the material meets strength and rigidity requirements or not; a standardized quick-change interface is designed at the joint of the cantilever and the cleaning tool, the cleaning tool is divided into a plurality of functional modules, and each module is connected with the cantilever through the quick-change interface; a quick-change interface three-dimensional model is established, a precise positioning and locking mechanism is adopted, quick positioning and reliable connection of the cleaning tool module and the cantilever are achieved, and the interface gap after connection is smaller than a preset threshold value; three-dimensional CAD software is adopted, a cantilever structure parameterization design model is established, the cantilever key size and geometric characteristics are parameterized, and a parameterization driving frame is formed.

Description

Technical Field

[0001] The invention relates to the field of information technology, and in particular to a cantilever structure optimization design method for an automatic car cleaning robot. Background Art

[0002] Problem background:

[0003] There is a key technical problem in the application of automatic car cleaning robot technology in the cleaning of residual coal in empty car dumpers: how to design a standardized cantilever interface and module so that different types of car cleaning robots can share cantilever components and achieve fast and convenient cantilever storage and retrieval. Solving this problem is of great significance to reducing the manufacturing cost and maintenance difficulty of automatic car cleaning robots.

[0004] At present, different models of car cleaning robots usually use different cantilever designs, which makes the parts not interchangeable, increasing production and maintenance costs. In addition, when replacing or repairing the cantilever, it often requires a long equipment downtime, affecting the cleaning efficiency. Therefore, it is urgent to study and design a standardized cantilever interface and module so that it can be interchangeable on different models of car cleaning robots, and at the same time use a quick locking device to achieve rapid installation and removal of the cantilever to minimize equipment downtime.

[0005] The solution to this technical problem requires comprehensive consideration of multiple factors, such as the mechanical properties of the cantilever, material selection, standardized interface design, and quick locking device design, based on an in-depth analysis of the empty car residual coal cleaning process of the tipping machine and the operating characteristics of the automatic car cleaning robot. Repeated tests, verifications, and optimization improvements should be carried out in order to obtain a standardized cantilever solution that takes into account versatility, reliability, and efficiency, thereby promoting the widespread application of automatic car cleaning robot technology in the field of empty car residual coal cleaning of tipping machines. Summary of the invention

[0006] The present invention provides a cantilever structure optimization design method for an automatic car cleaning robot, which mainly includes:

[0007] Obtain information on the mechanical performance requirements and working environment characteristics of the cantilever of different models of automatic car cleaning robots, and based on the information, comprehensively consider factors such as material strength, stiffness, toughness, wear resistance and corrosion resistance to establish a material selection index system;

[0008] For the candidate high-strength lightweight alloy materials, the finite element analysis method is used to simulate the stress state of the cantilever under different working conditions, obtain the stress-strain cloud diagram, and determine whether the material meets the strength and stiffness requirements;

[0009] For candidate materials that meet the strength and stiffness requirements, cantilever fatigue life and fracture toughness tests are conducted. Based on the test results, combined with the wear resistance and corrosion resistance of the material, the optimal cantilever material selection scheme is determined;

[0010] A standardized quick-change interface is designed at the connection between the cantilever and the cleaning tool, and the cleaning tool is divided into several functional modules. Each module is connected to the cantilever through a quick-change interface.

[0011] A three-dimensional model of the quick-change interface is established, and a precise positioning and locking mechanism is used to achieve rapid positioning and reliable connection between the cleaning tool module and the cantilever. After connection, the interface gap is smaller than the preset threshold.

[0012] Use 3D CAD software to establish a parametric design model of the cantilever structure, parameterize the key dimensions and geometric features of the cantilever, and form a parametric driving framework;

[0013] In the parametric model, according to the usage requirements of a specific model of automatic car-clearing robot, the target cantilever performance parameters are input, and the optimization algorithm is called to automatically optimize the cantilever structure size and shape, generate the cantilever three-dimensional model and engineering drawing, and complete the cantilever structure design if the optimization result meets the performance requirements.

[0014] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0015] The present invention discloses a method for optimizing the cantilever structure of an automatic car-clearing robot. The method first establishes a material selection index system, comprehensively considers factors such as strength, stiffness, and toughness, and screens the optimal cantilever material through finite element analysis and fatigue testing. Then, a standardized quick-change interface is designed to realize modular connection of cleaning tools. Finally, a parametric design model of the cantilever structure is established, and the target performance parameters are input according to the needs of a specific model of robot, and the optimization algorithm is called to automatically complete the structural optimization. The present invention realizes the efficient customized design of the cantilever of the automatic car-clearing robot through a method combining material optimization, modular design, and parametric optimization, improves the performance and adaptability of the cantilever structure, and provides reliable technical support for car-clearing operations under different working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for optimizing the cantilever structure of an automatic car cleaning robot.

[0017] Figure 2 It is a schematic diagram of a cantilever structure optimization design method of an automatic car cleaning robot of the present invention.

[0018] Figure 3 It is another schematic diagram of the cantilever structure optimization design method of an automatic car cleaning robot of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] like Figure 1-3 In this embodiment, a cantilever structure optimization design method for an automatic car cleaning robot may specifically include:

[0021] S101. Obtain information on cantilever mechanical performance requirements and working environment characteristics of different types of automatic car cleaning robots. Based on the information, comprehensively consider factors such as material strength, stiffness, toughness, wear resistance and corrosion resistance to establish a material selection index system.

[0022] The three-dimensional model data of the cantilever of different types of automatic car cleaning robots are obtained, and the static and dynamic simulation analysis of the cantilever is performed through finite element analysis software to obtain the stress-strain distribution and vibration characteristic parameters of the cantilever under different working conditions; the working environment parameters of the automatic car cleaning robot are obtained to determine the degree of influence of the environment on the material performance and determine the performance requirements that the material needs to have; a hierarchical analysis method is used to establish a comprehensive evaluation system for material performance and to score and rank the candidate materials; the cantilever structure parameters obtained by the simulation analysis are used to analyze the correlation between material performance and the cantilever structure parameters using the April association rule mining algorithm to optimize the cantilever structure design scheme; the performance parameters and environmental factors of the candidate materials are used as input to construct a support vector machine regression model to predict the comprehensive performance of different materials in the actual working environment and screen out the material with the best adaptability; virtual assembly and motion analysis of the cantilever of different materials are performed through simulation technology to verify the mechanical reliability of the material selection scheme; comprehensive analysis of various results, balance material performance and the cantilever structure design requirements, determine the optimal material selection scheme, and generate a material selection report and the cantilever structure optimization suggestions.

[0023] Specifically, the three-dimensional model data of the cantilever of different types of automatic car cleaning robots are obtained, and the static and dynamic simulation analysis of the cantilever is performed through finite element analysis software to obtain the stress-strain distribution and vibration characteristic parameters of the cantilever under different working conditions; the working environment parameters of the automatic car cleaning robot are obtained to judge the degree of influence of the environment on the material performance and determine the performance requirements that the material needs to have; the hierarchical analysis method is used to establish a comprehensive evaluation system for material performance and to score and rank the candidate materials; the cantilever structure parameters obtained by simulation analysis are used to analyze the correlation between material performance and cantilever structure parameters using the April association rule mining algorithm to optimize the cantilever structure design scheme; the performance parameters and environmental factors of the candidate materials are used as input to construct a support vector machine regression model to predict the comprehensive performance of different materials in the actual working environment and screen out the most adaptable materials; virtual assembly and motion analysis of cantilevers of different materials are performed through simulation technology to verify the mechanical reliability of the material selection scheme; comprehensive analysis of various results, balance material performance and cantilever structure design requirements, determine the optimal material selection scheme, and generate a material selection report and cantilever structure optimization suggestions.

[0024] S102. For the candidate high-strength lightweight alloy materials, the finite element analysis method is used to simulate the stress state of the cantilever under different working conditions, obtain the stress-strain cloud diagram, and determine whether the material meets the strength and stiffness requirements.

[0025] The physical and mechanical parameters of the candidate high-strength lightweight alloy material are obtained, and the constitutive relationship of the material is established by adopting an isotropic linear elastic constitutive model to obtain the elastic modulus, Poisson's ratio and yield strength mechanical property parameters of the material; a geometric model of the cantilever structure is constructed by using a three-dimensional modeling software, and the mechanical property parameters of the material are assigned to the geometric model to define the material properties; the geometric model is meshed to generate a finite element mesh model; loads and boundary conditions are applied to the finite element model according to the actual working conditions of the cantilever; static finite element analysis is used to calculate the stress and strain distribution of the cantilever under the working condition, and a stress-strain cloud map and a deformation cloud map are obtained; according to the stress state and deformation characteristics of the cantilever, whether the material meets the strength and stiffness requirements under the working condition is determined; if the material meets the strength and stiffness requirements, it is used as a candidate material for subsequent optimization design; if the material does not meet the strength and stiffness requirements, the chemical composition ratio of the material is adjusted or other materials are selected, and the finite element analysis is performed again; according to the results of the finite element analysis, the stress concentration area of ​​the cantilever is structurally optimized to improve the strength of the cantilever and reduce the degree of stress concentration.

[0026] Specifically, according to the physical and mechanical parameters of the candidate high-strength lightweight alloy materials, a suitable constitutive model such as an isotropic linear elastic constitutive model is used to establish the material constitutive relationship, and the mechanical performance parameters such as elastic modulus, Poisson's ratio, and yield strength of the material are obtained. For the cantilever structure, a three-dimensional modeling software such as SolidWorks is used to build a geometric model, and the mechanical performance parameters of the material are assigned to the geometric model to define the material properties. Finite element pre-processing software such as ANSYSWorkbench is used to mesh the geometric model and generate mesh units. According to the actual working conditions of the cantilever, such as applying a downward concentrated force at the free end of the cantilever and applying a full constraint at the fixed end, the load and boundary conditions are set in the finite element model. Through the finite element solver, static analysis is used to calculate the stress and strain distribution of the cantilever under this working condition, obtain the stress and strain cloud map and deformation cloud map, and analyze the stress and strain concentration area. According to the stress state and deformation characteristics of the cantilever, the yield strength of the material is compared to determine whether the high-strength lightweight alloy material yields under this working condition. If the maximum stress is less than the yield strength of the material and the maximum deformation meets the stiffness requirements, the material is considered to meet the strength and stiffness requirements and can be used as a candidate material for the cantilever for subsequent optimization design and test verification. If the maximum stress is greater than the yield strength of the material, or the maximum deformation does not meet the stiffness requirements, it is necessary to adjust the chemical composition ratio of the material to improve the material strength, or select other lightweight alloy materials with higher strength and greater stiffness, and re-perform finite element analysis and evaluation. According to the results of the finite element analysis, the stress and strain concentration area of ​​the cantilever is structurally optimized, such as adding reinforcing ribs and optimizing the cross-sectional shape in the stress concentration area, so as to improve the strength of the cantilever in the stress concentration area, reduce the degree of stress concentration, and make the cantilever meet the strength and stiffness requirements. After the above analysis and optimization design, a cantilever structure that meets the strength and stiffness requirements can be obtained, providing a design reference for the manufacture and application of the cantilever.

[0027] S103. For candidate materials that meet the strength and stiffness requirements, conduct cantilever fatigue life and fracture toughness tests. Based on the test results and combined with the wear resistance and corrosion resistance of the materials, determine the optimal cantilever material selection solution.

[0028] Obtain a list of candidate materials that meet the strength and stiffness requirements; design a fatigue life test plan and a fracture toughness test plan for the materials in the candidate material list, the fatigue life test plan includes stress level and number of cycles test parameters, and the fracture toughness test plan includes load and crack size test parameters; carry out fatigue life tests and fracture toughness tests on the candidate materials to obtain quantitative results of fatigue life and fracture toughness of the candidate materials; screen out preferred materials with long fatigue life and high fracture toughness based on the quantitative results of fatigue life and fracture toughness; obtain wear resistance data and corrosion resistance data of the candidate materials, calculate the wear rate of the candidate materials using a wear rate calculation method, and test the corrosion rate of the candidate materials using a corrosion rate test method; establish a hierarchical structure model of material performance indicators based on the fatigue life, fracture toughness, wear resistance and corrosion resistance of the candidate materials, determine the weight of each material performance indicator using a hierarchical analysis method, and calculate the comprehensive performance weighted score of each candidate material; determine the optimal cantilever material selection plan based on the ranking results of the comprehensive performance weighted score and the actual working environment conditions and use requirements of the cantilever.

[0029] Specifically, according to the material performance database, a list of candidate materials that meet the strength and stiffness requirements is obtained. For the materials in the candidate material list, fatigue life and fracture toughness test plans are designed, and test parameters and evaluation indicators are formulated, such as stress level and number of cycles for fatigue life test and load and crack size for fracture toughness test. Fatigue life test and fracture toughness test of candidate materials are carried out, and test process data are collected to obtain quantitative results of fatigue life and fracture toughness of materials. According to the results of fatigue life and fracture toughness tests, the fatigue and fracture properties of candidate materials are evaluated, and preferred materials with long fatigue life and high fracture toughness are screened out. By consulting literature and material manuals, wear resistance and corrosion resistance data of candidate materials are obtained. Combined with the existing material performance database, quantitative evaluation methods such as wear rate calculation and corrosion rate test are used to evaluate the wear resistance and corrosion resistance of materials. On the basis of comprehensive consideration of material fatigue life, fracture toughness, wear resistance and corrosion resistance, the hierarchical analysis method is used to establish a hierarchical structure model of material performance indicators, and the weight of each indicator is determined by pairwise comparison, and the comprehensive performance weighted score of each candidate material is calculated. According to the ranking results of the comprehensive performance scores, combined with the actual working environment conditions of the cantilever such as load spectrum, temperature, humidity, etc., as well as the use requirements such as design life, reliability, etc., the mechanical properties, environmental adaptability and economic cost of the material are weighed to determine the optimal cantilever material selection plan and complete the material selection process.

[0030] S104. Design a standardized quick-change interface at the connection between the cantilever and the cleaning tool, divide the cleaning tool into several functional modules, and each module is connected to the cantilever through the quick-change interface.

[0031] Obtain preset functional module division rules, the functional module division rules include the material of the cleaning object, the size of the cleaning area, and the cleaning frequency factors; divide the cleaning tool into several functional modules according to the functional module division rules, each of which is responsible for a specific cleaning task; for each functional module, design a corresponding standardized quick-change interface, the standardized quick-change interface is combined with the size, weight, and power supply requirement parameters of the functional module; obtain functional module data, the functional module data includes the applicable scenarios, performance parameters, and historical usage data of each functional module; use the support vector machine algorithm to train the functional module data to obtain a functional module selection model; obtain the attribute data of the cleaning task to be executed, input the attribute data into the functional module selection model, and obtain the functional module combination required for the cleaning task to be executed; obtain the real-time working Status data, the real-time working status data includes energy consumption, noise, and vibration; the real-time working status data is analyzed by a random forest algorithm, and when it is determined that the performance of a certain functional module has declined or a fault occurs, the cantilever is controlled to move to a specified position, and a new functional module is automatically replaced through the standardized quick-change interface; according to the attribute parameters of the functional module and the real-time working status data, the motion parameters of the cantilever are dynamically adjusted, and the motion parameters include moving speed, acceleration, and motion trajectory, so as to improve the cleaning efficiency and reduce energy consumption while ensuring the cleaning effect; a reinforcement learning model is constructed, and the time, energy consumption, and noise indicators for completing the cleaning task are taken as optimization goals, and a reward function is set accordingly; the selection and combination of the functional modules are taken as the action space; through continuous trial and learning, the optimal decision path that can obtain the maximum cumulative reward is obtained; and the optimal decision path is applied to actual cleaning operations.

[0032] Specifically, according to the preset functional module division rules, the cleaning tool is divided into several functional modules, and each functional module is responsible for a specific cleaning task. The basis for functional module division includes factors such as the material of the cleaning object, the size of the cleaning area, and the cleaning frequency. For each functional module, a corresponding standardized quick-change interface is designed. The design of the interface needs to consider parameters such as the size, weight, and power supply requirements of the functional module to ensure that the functional module and the cantilever can be quickly and reliably connected and separated. The interface specifications of different functional modules should be unified as much as possible to reduce the complexity of replacement. A functional module database is established to record the applicable scenarios, performance parameters, historical usage data, etc. of each functional module. The support vector machine algorithm is used to train the data and generate a functional module selection model. Before executing the cleaning task, relevant data is obtained from the database according to the task attributes and input into the selection model to automatically determine the functional module combination to be used. During the cleaning process, the working status data of each functional module is obtained in real time, including energy consumption, noise, vibration, etc. The random forest algorithm is used to analyze the status data. When it is determined that the performance of a functional module has degraded or failed, the cantilever is controlled to move to the specified position and a new functional module is automatically replaced through the quick-change interface. According to the attribute parameters of the functional module and the actual working status, the motion parameters of the cantilever are dynamically adjusted, including moving speed, acceleration, motion trajectory, etc. The optimization goal is to improve cleaning efficiency and reduce energy consumption while ensuring the cleaning effect. The adjustment strategy is generated according to pre-set rules and continuously self-optimizes as the actual working data accumulates. In the reinforcement learning model, the time, energy consumption, noise and other indicators to complete the cleaning task are used as optimization targets, and the reward function is set accordingly. The selection and combination of functional modules are used as the action space. Through continuous trial and learning, the optimal decision path that can obtain the maximum cumulative reward is found and applied to the actual cleaning operation.

[0033] S105. Establish a three-dimensional model of the quick-change interface, and use a precise positioning and locking mechanism to achieve rapid positioning and reliable connection between the cleaning tool module and the cantilever, so that the interface gap is smaller than a preset threshold after connection.

[0034] Obtain a three-dimensional model of the cleaning tool module and the cantilever. According to the positioning requirements of the quick-change interface, set the positioning boss and positioning hole on the connection surface. If the size and shape of the positioning boss and the positioning hole are set reasonably, the cleaning tool module can be accurately positioned relative to the cantilever. According to the reliable connection requirements of the quick-change interface, arrange the locking device on the connection surface and set the appropriate locking force. Use a pressure sensor to measure the locking force of the locking device, obtain the actual locking force data, compare the actual locking force data with the preset threshold, and judge whether it meets the design requirements. According to the sealing requirements of the quick-change interface, reasonably set the installation groove of the sealing ring on the connection surface, control the processing accuracy of the connection surface, use a CNC machining center to process the connection surface, ensure that the surface roughness meets the requirements, and control the interface gap after connection within the preset range. Use a three-coordinate measuring machine to detect the positioning accuracy of the quick-change interface, obtain the actual positioning deviation value, and compare the actual positioning deviation value with the preset threshold. If the positioning accuracy of the quick-change interface does not reach the preset threshold, the finite element analysis software is used to optimize the structure of the precision positioning mechanism. By adjusting the parameters of the positioning boss and the positioning hole, the positioning accuracy of the quick-change interface is improved, and the three-dimensional modeling and processing are re-performed until the design requirements are met. The finite element analysis software is used to simulate the stress conditions of the quick-change interface under actual working conditions. The load is applied to the connection surface, and the stress distribution cloud map of the connection surface is obtained to determine the stress concentration area. For the stress concentration area, the structural design of the quick-change interface is optimized to improve the reliability of the quick-change interface. Finally, the sample is processed, and through actual assembly and testing, it is verified whether the performance of the quick-change interface meets the design requirements.

[0035] Specifically, according to the functional requirements of the quick-change interface, the SolidWorks software is used to establish a three-dimensional model including the cleaning tool module and the cantilever, and the connection structure between the two is designed. According to the positioning requirements of the quick-change interface, positioning bosses and positioning holes are set on the connection surface to achieve accurate positioning of the cleaning tool module relative to the cantilever. In order to ensure the reliable connection of the quick-change interface, a locking device is arranged on the connection surface, and an appropriate locking force is set to ensure reliable fixation between the cleaning tool module and the cantilever. According to the sealing requirements of the quick-change interface, the installation groove of the sealing ring is reasonably set on the connection surface, and the processing accuracy of the connection surface is controlled. The connection surface is processed by a CNC machining center to ensure that the surface roughness Ra is not greater than 6μm, so that the interface gap after connection is controlled within 1mm. The positioning accuracy of the quick-change interface is detected by a three-coordinate measuring machine, and the locking force of the locking device is measured by a pressure sensor. The actual positioning deviation value and locking force data are obtained, and compared with the preset thresholds of 05mm and 1000N to determine whether the design requirements are met. If the positioning accuracy or locking reliability of the quick-change interface does not reach the preset threshold, the ANSYS finite element analysis software is used to optimize the structure of the precision positioning mechanism and the locking mechanism. By adjusting the size, shape, and layout position of the positioning boss and the positioning hole, the positioning accuracy and locking reliability of the quick-change interface are improved, and the three-dimensional modeling and processing are re-performed until the design requirements are met. The ANSYS finite element analysis software is used to simulate the stress conditions of the quick-change interface under actual working conditions. The load is applied to the connection surface, and the Von-Mi ses stress distribution cloud map of the connection surface is obtained to determine the stress concentration area. For the stress concentration area, the structural design of the quick-change interface is optimized by increasing the thickness of the connection surface, setting chamfers, and other measures to improve the reliability of the quick-change interface. Finally, the sample is processed, and the performance of the quick-change interface is verified to meet the design requirements through actual assembly and testing.

[0036] S106. Use 3D CAD software to establish a parametric design model of the cantilever structure, parameterize the key dimensions and geometric features of the cantilever, and form a parametric driving framework.

[0037] The method comprises the steps of: obtaining geometric characteristic parameters of a cantilever structure, wherein the geometric characteristic parameters include length, width and height; calculating a dimension ratio coefficient according to the geometric characteristic parameters and a preset calculation formula, wherein the calculation formula includes the length, width and height; judging whether the dimension ratio coefficient meets a preset threshold range; if the dimension ratio coefficient meets the preset threshold range, adjusting the key dimension parameters of the cantilever using the dimension ratio coefficient to obtain preliminary model data of the cantilever structure; extracting a shape characteristic vector from the preliminary model data, wherein the shape characteristic vector includes a cross-sectional shape, a cross-sectional size and a length; grouping the shape characteristic vector according to a preset characteristic grouping rule to obtain characteristic grouping data, wherein the characteristic grouping rule includes classification according to cross-sectional shape and size range; associating the characteristic grouping data with a pre-established driving framework, and adjusting the driving framework through the driving framework. The geometric topological relationship in the preliminary model data is adjusted, and the geometric topological relationship includes the connection mode and angle between each cross section, so as to obtain the optimized geometric topological model data; a preset number of types of design schemes for the cantilever structure are automatically generated according to the geometric topological model data, and the preset number of types of design schemes cover combinations of different sizes and geometric features; the three-dimensional solid model of the preset number of types of design schemes is imported into the finite element analysis software, and the material properties, constraints and load conditions are set to perform static and modal analysis to obtain the stress strain, deformation and vibration frequency of the cantilever structure under different load conditions; the stress strain, deformation and vibration frequency are compared with the preset strength and stability standards; if the stress strain meets the preset strength standard, and the vibration frequency meets the preset stability standard, the three-dimensional model drawing of the corresponding design scheme is output.

[0038] Specifically, a database of geometric features and key dimensions of the cantilever structure in the parametric design model is pre-established. The geometric feature parameters of the cantilever structure are obtained, including dimensional information such as length, width, and height. The dimension ratio coefficient is calculated according to the preset calculation formula based on the geometric feature parameters, and the formula includes geometric parameters such as length, width, and height. After the dimension ratio coefficient is determined, it is judged whether the coefficient meets the preset threshold range. If it meets the preset threshold range, the key dimension parameters of the cantilever are adjusted using the coefficient, and the preliminary model data of the cantilever structure is obtained by adjusting the key dimension parameters. The shape feature vector is extracted from the preliminary model data, including feature parameters such as cross-sectional shape, cross-sectional size, and length. The shape feature vectors are grouped according to the preset feature grouping rules, and the grouping rules are classified according to the cross-sectional shape, size range, etc. to obtain feature grouping data. The feature grouping data is associated with a pre-established driving framework, and the geometric topological relationship in the preliminary model data is adjusted through the driving framework, including adjusting the connection method and angle between each cross section, to obtain the optimized geometric topological model data. According to the geometric topological model data, a variety of design schemes for the cantilever structure are automatically generated, and these schemes cover combinations of different sizes and geometric features. Use 3D modeling software such as SolidWorks to build a 3D solid model based on the geometric topology model data of the design scheme. Import the 3D solid model into finite element analysis software such as ANSYS, set material properties, constraints and load conditions, perform static and modal analysis, and obtain the strength and stability parameters such as stress strain, deformation and vibration frequency of the cantilever structure under different load conditions. The strength and stability parameters are compared with the preset strength and stability standards. If the stress level and deformation meet the strength requirements and the vibration frequency meets the stability requirements, the 3D model drawings of the corresponding scheme are output.

[0039] S107. In the parametric model, according to the use requirements of a specific model of automatic car cleaning robot, the target cantilever performance parameters are input, the optimization algorithm is called, the cantilever structure size and shape are optimized automatically, and the cantilever three-dimensional model and engineering drawing are generated. If the optimization result meets the performance requirements, the cantilever structure design is completed.

[0040] The input target cantilever performance parameters are obtained, and the preset genetic algorithm is used to calculate and generate the optimal size and shape data of the cantilever structure. The genetic algorithm searches for the optimal solution by simulating the biological evolution process, including selection, crossover, and mutation operations. The key geometric parameters are extracted from the generated size and shape data, and the corresponding geometric model is created in the three-dimensional CAD software to construct a three-dimensional solid model of the cantilever structure. The engineering drawing function of the three-dimensional CAD software is used to extract projection views in different directions based on the generated three-dimensional solid model, and the key dimensions are marked to automatically generate two-dimensional engineering drawings that meet the engineering drawing specifications. The three-dimensional solid model of the cantilever structure is imported into the finite element analysis software, the material properties, constraints and load conditions are defined, and the tetrahedral mesh division model is used to simulate and calculate the stress distribution and deformation of the cantilever under the actual stress state, and the maximum stress and maximum deformation of the cantilever are obtained. The performance index values ​​obtained by the finite element analysis are compared with the input target performance parameters one by one to determine whether all indicators meet the requirements. If all performance indicators reach or exceed the target value, the current design parameters and the generated three-dimensional model and engineering drawings are output. If there are still performance indicators that are not met, return to the genetic algorithm optimization step, adjust the algorithm parameters, recalculate and generate new cantilever structure dimensions, and perform three-dimensional modeling, finite element analysis and performance evaluation again until the optimal design solution that meets all performance requirements is found.

[0041] Specifically, according to the input target cantilever performance parameters, the preset genetic algorithm is applied to calculate and generate the optimal size and shape data of the cantilever structure. The genetic algorithm searches for the optimal solution by simulating the biological evolution process, including operations such as selection, crossover, and mutation, and is suitable for solving complex structural optimization problems. Key geometric parameters such as length, width, thickness, and cross-sectional shape are extracted from the generated size and shape data, and the corresponding geometric model is created in the three-dimensional CAD software SolidWorks to construct a three-dimensional solid model of the cantilever structure. Using the engineering drawing function of SolidWorks, based on the generated three-dimensional solid model, the projection views in different directions such as the top view, the main view, and the left view are extracted, and the key dimensions are marked to automatically generate two-dimensional engineering drawings that meet the engineering drawing specifications. The three-dimensional solid model of the cantilever structure is imported into the finite element analysis software ANSYS, and the material properties, constraints, and load conditions are defined. Using the static analysis module of ANSYS, the tetrahedral meshing model is adopted to simulate and calculate the stress distribution and deformation of the cantilever under the actual stress state, and the key performance index values ​​such as the maximum stress and maximum deformation of the cantilever are obtained. Compare the performance index values ​​obtained by finite element analysis with the input target performance parameters one by one to determine whether all indicators meet the requirements. If all performance indicators reach or exceed the target values, the optimization design of the cantilever structure is completed, and the current design parameters and the generated three-dimensional model and engineering drawings are output. If there are still performance indicators that do not meet the standards, return to the genetic algorithm optimization step, adjust the algorithm parameters, such as increasing the population size, increasing the crossover probability and mutation probability, etc., or use other optimization methods such as simulated annealing algorithm, recalculate and generate new cantilever structure dimensions, and perform three-dimensional modeling, finite element analysis and performance evaluation again until the optimal design solution that meets all performance requirements is found.

[0042] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A cantilever structure optimization design method for an automatic car cleaning robot, characterized in that: The method comprises: Obtain information on the mechanical performance requirements and working environment characteristics of the cantilever of different models of automatic car cleaning robots, and based on the information, comprehensively consider factors such as material strength, stiffness, toughness, wear resistance and corrosion resistance to establish a material selection index system; For the candidate high-strength lightweight alloy materials, the finite element analysis method is used to simulate the stress state of the cantilever under different working conditions, obtain the stress-strain cloud diagram, and determine whether the material meets the strength and stiffness requirements; For candidate materials that meet the strength and stiffness requirements, cantilever fatigue life and fracture toughness tests are conducted. Based on the test results, combined with the wear resistance and corrosion resistance of the material, the optimal cantilever material selection scheme is determined; A standardized quick-change interface is designed at the connection between the cantilever and the cleaning tool, and the cleaning tool is divided into several functional modules. Each module is connected to the cantilever through a quick-change interface. A three-dimensional model of the quick-change interface is established, and a precise positioning and locking mechanism is used to achieve rapid positioning and reliable connection between the cleaning tool module and the cantilever. After connection, the interface gap is smaller than the preset threshold. Use 3D CAD software to establish a parametric design model of the cantilever structure, parameterize the key dimensions and geometric features of the cantilever, and form a parametric driving framework; In the parametric model, according to the usage requirements of a specific model of automatic car-clearing robot, the target cantilever performance parameters are input, and the optimization algorithm is called to automatically optimize the cantilever structure size and shape, generate the cantilever three-dimensional model and engineering drawing, and complete the cantilever structure design if the optimization result meets the performance requirements.

2. The method according to claim 1, characterized in that The mechanical performance requirements and working environment characteristics of the cantilever of different types of automatic car cleaning robots are obtained, and based on the information, the material strength, stiffness, toughness, wear resistance and corrosion resistance are comprehensively considered to establish a material selection index system, including: Acquire the three-dimensional model data of the cantilever of different models of automatic car cleaning robots, perform static and dynamic simulation analysis on the cantilever through finite element analysis software, and obtain the stress-strain distribution and vibration characteristic parameters of the cantilever under different working conditions; Obtain the working environment parameters of the automatic car cleaning robot, determine the degree of influence of the environment on the material performance, and determine the performance requirements that the material needs to have; Using the analytic hierarchy process, a comprehensive evaluation system for material performance is established to score and rank candidate materials; Using the cantilever structure parameters obtained by the simulation analysis, the Apriori association rule mining algorithm is used to analyze the correlation between material properties and the cantilever structure parameters, so as to optimize the cantilever structure design scheme; Taking the performance parameters and environmental factors of the candidate materials as input, a support vector machine regression model is constructed to predict the comprehensive performance of different materials in the actual working environment and select the material with the best adaptability; Through simulation technology, virtual assembly and motion analysis of the cantilever made of different materials are performed to verify the mechanical reliability of the material selection scheme; Comprehensively analyze various results, balance material properties and cantilever structure design requirements, determine the optimal material selection solution, and generate a material selection report and cantilever structure optimization suggestions.

3. The method according to claim 1, characterized in that The method of using a finite element analysis method to simulate the stress state of the cantilever under different working conditions for the candidate high-strength lightweight alloy material, obtains a stress-strain cloud diagram, and determines whether the material meets the strength and stiffness requirements, including: Obtaining the physical and mechanical parameters of the candidate high-strength lightweight alloy material, using an isotropic linear elastic constitutive model to establish the constitutive relationship of the material, and obtaining the elastic modulus, Poisson's ratio and yield strength mechanical property parameters of the material; Using three-dimensional modeling software to build a geometric model of the cantilever structure, assigning mechanical performance parameters of the material to the geometric model, and defining material properties; Meshing the geometric model to generate a finite element mesh model; Applying loads and boundary conditions in the finite element model according to the actual working condition of the cantilever; Static finite element analysis is used to calculate the stress and strain distribution of the cantilever under the working condition, and a stress and strain cloud diagram and a deformation cloud diagram are obtained; According to the stress state and deformation characteristics of the cantilever, determine whether the material meets the strength and stiffness requirements under the working condition; If the material meets the strength and stiffness requirements, it is used as a candidate material for subsequent optimization design; If the material does not meet the strength and stiffness requirements, adjust the chemical composition ratio of the material or select other materials and re-perform finite element analysis; According to the finite element analysis results, the stress concentration area of ​​the cantilever is structurally optimized to improve the strength of the cantilever and reduce the degree of stress concentration.

4. The method according to claim 1, characterized in that: The cantilever fatigue life and fracture toughness tests are conducted on candidate materials that meet the strength and stiffness requirements, and the optimal cantilever material selection scheme is determined based on the test results and the wear resistance and corrosion resistance of the materials, including: Obtain a list of candidate materials that meet strength and stiffness requirements; Designing a fatigue life test scheme and a fracture toughness test scheme for the materials in the candidate material list, wherein the fatigue life test scheme includes stress level and cycle number test parameters, and the fracture toughness test scheme includes load and crack size test parameters; Conduct fatigue life tests and fracture toughness tests on the candidate materials to obtain quantitative results of fatigue life and fracture toughness of the candidate materials; According to the quantitative results of fatigue life and fracture toughness, selecting preferred materials with long fatigue life and high fracture toughness; Obtaining wear resistance data and corrosion resistance data of the candidate material, calculating the wear rate of the candidate material using a wear rate calculation method, and testing the corrosion rate of the candidate material using a corrosion rate test method; In combination with the fatigue life, fracture toughness, wear resistance and corrosion resistance of the candidate materials, a hierarchical structure model of material performance indicators is established, the weight of each material performance indicator is determined by using the hierarchical analysis method, and the comprehensive performance weighted score of each candidate material is calculated; According to the ranking result of the weighted score of the comprehensive performance, combined with the actual working environment conditions and use requirements of the cantilever, the optimal cantilever material selection scheme is determined.

5. The method according to claim 1, characterized in that At the connection between the cantilever and the cleaning tool, a standardized quick-change interface is designed to divide the cleaning tool into several functional modules, each module is connected to the cantilever through the quick-change interface, including: Obtaining a preset functional module division rule, wherein the functional module division rule includes factors such as the material of the cleaning object, the size of the cleaning area, and the cleaning frequency; According to the functional module division rule, the cleaning tool is divided into several functional modules, each of which is responsible for a specific cleaning task; For each of the functional modules, a corresponding standardized quick-change interface is designed, wherein the standardized quick-change interface is combined with the size, weight and power supply requirement parameters of the functional module; Acquire function module data, wherein the function module data includes applicable scenarios, performance parameters and historical usage data of each function module; Using a support vector machine algorithm to train the functional module data to obtain a functional module selection model; Acquire attribute data of the cleaning task to be performed, input the attribute data into the function module selection model, and obtain the function module combination required for the cleaning task to be performed; Acquiring real-time working status data of each of the functional modules, wherein the real-time working status data includes energy consumption, noise and vibration; The real-time working status data is analyzed by using a random forest algorithm. When it is determined that the performance of a certain functional module has degraded or a failure has occurred, the cantilever is controlled to move to a specified position, and a new functional module is automatically replaced through the standardized quick-change interface. According to the attribute parameters of the functional module and the real-time working status data, the motion parameters of the cantilever are dynamically adjusted, and the motion parameters include moving speed, acceleration and motion trajectory, so as to improve cleaning efficiency and reduce energy consumption while ensuring the cleaning effect; Build a reinforcement learning model, take the time, energy consumption and noise indicators to complete the cleaning task as optimization targets, and set the corresponding reward function; The selection and combination of the functional modules are used as an action space; Through continuous trial and learning, we can obtain the optimal decision path that can obtain the maximum cumulative reward; The optimal decision path is applied to the actual cleaning operation.

6. The method according to claim 1, characterized in that The three-dimensional model of the quick-change interface is established, and a precise positioning and locking mechanism is used to achieve rapid positioning and reliable connection between the cleaning tool module and the cantilever, and the interface gap after connection is less than a preset threshold, including: Obtain a three-dimensional model of the cleaning tool module and the cantilever, and set a positioning boss and a positioning hole on the connection surface according to the positioning requirements of the quick-change interface; If the size and shape of the positioning boss and the positioning hole are set reasonably, the cleaning tool module can be accurately positioned relative to the cantilever; According to the reliable connection requirements of the quick-change interface, a locking device is arranged on the connection surface, and an appropriate locking force is set; Using a pressure sensor to measure the locking force of the locking device, obtaining actual locking force data, and comparing the actual locking force data with a preset threshold to determine whether the design requirements are met; In view of the sealing requirements of the quick-change interface, a sealing ring installation groove is reasonably set on the connection surface. By controlling the processing accuracy of the connection surface, the connection surface is processed using a CNC machining center to ensure that the surface roughness meets the requirements and the interface gap after connection is controlled within a preset range; Use a three-dimensional coordinate measuring machine to test the positioning accuracy of the quick-change interface, obtain the actual positioning deviation value, and compare the actual positioning deviation value with the preset threshold value; If the positioning accuracy of the quick-change interface does not reach the preset threshold, the finite element analysis software is used to optimize the structure of the precision positioning mechanism, and the positioning accuracy of the quick-change interface is improved by adjusting the parameters of the positioning boss and the positioning hole, and the three-dimensional modeling and processing are re-performed until the design requirements are met; Finite element analysis software is used to simulate the stress conditions of the quick-change interface under actual working conditions. The load is applied to the connection surface, and the stress distribution cloud map of the connection surface is obtained to determine the stress concentration area. Aiming at the stress concentration area, the reliability of the quick-change interface is improved by optimizing the structural design of the quick-change interface; Finally, a sample is produced and, through actual assembly and testing, it is verified whether the performance of the quick-change interface meets the design requirements.

7. The method according to claim 1, characterized in that The three-dimensional CAD software is used to establish a parametric design model of the cantilever structure, parameterize the key dimensions and geometric features of the cantilever, and form a parametric driving framework, including: Acquire geometric characteristic parameters of the cantilever structure, wherein the geometric characteristic parameters include length, width and height; Calculate the size ratio coefficient according to the geometric feature parameters and a preset calculation formula, wherein the calculation formula includes the length, width and height; Determining whether the size ratio coefficient meets a preset threshold range; If the size ratio coefficient meets the preset threshold range, the key size parameters of the cantilever are adjusted using the size ratio coefficient to obtain preliminary model data of the cantilever structure; Extracting a shape feature vector from the preliminary model data, wherein the shape feature vector includes a cross-sectional shape, a cross-sectional size, and a length; Grouping the shape feature vectors according to a preset feature grouping rule to obtain feature grouping data, wherein the feature grouping rule includes classification according to cross-sectional shape and size range; Associating the feature grouping data with a pre-established driving framework, adjusting the geometric topological relationship in the preliminary model data through the driving framework, the geometric topological relationship including the connection mode and angle between each cross section, to obtain optimized geometric topological model data; Automatically generate a preset number of design solutions for the cantilever structure according to the geometric topology model data, wherein the preset number of design solutions covers combinations of different sizes and geometric features; Importing the three-dimensional solid models of the preset number of types of design schemes into finite element analysis software, setting material properties, constraint conditions and load conditions, performing static and modal analysis, and obtaining stress, strain, deformation and vibration frequency of the cantilever structure under different load conditions; comparing the stress strain, deformation and vibration frequency with preset strength and stability standards; If the stress-strain meets the preset strength standard, and the vibration frequency meets the preset stability standard, a three-dimensional model drawing of the corresponding design solution is output.

8. The method according to claim 1, characterized in that In the parametric model, according to the use requirements of a specific model of automatic car cleaning robot, the target cantilever performance parameters are input, the optimization algorithm is called, the cantilever structure size and shape are optimized automatically, and the cantilever three-dimensional model and engineering drawing are generated. If the optimization result meets the performance requirements, the cantilever structure design is completed, including: Obtain the input target cantilever performance parameters, and use the preset genetic algorithm to calculate and generate the optimal size and shape data of the cantilever structure; The genetic algorithm searches for the optimal solution by simulating the biological evolution process, including selection, crossover and mutation operations; Extract key geometric parameters from the generated size and shape data, create the corresponding geometric model in 3D CAD software, and construct a 3D solid model of the cantilever structure; Utilizing the engineering drawing function of the 3D CAD software, based on the generated 3D solid model, extracting projection views in different directions, and marking key dimensions, automatically generating 2D engineering drawings that meet engineering drawing specifications; The three-dimensional solid model of the cantilever structure is imported into the finite element analysis software, material properties, constraints and load conditions are defined, and the tetrahedral meshing model is used to simulate and calculate the stress distribution and deformation of the cantilever under the actual stress state, and the key performance indicator values ​​of the maximum stress and maximum deformation of the cantilever are obtained; Compare the performance index values ​​obtained by finite element analysis with the input target performance parameters one by one to determine whether all indicators meet the requirements; If all performance indicators reach or exceed the target values, the current design parameters and the generated 3D model and engineering drawings are output; If there are still performance indicators that are not met, return to the genetic algorithm optimization step, adjust the algorithm parameters, recalculate and generate new cantilever structure dimensions, and perform three-dimensional modeling, finite element analysis and performance evaluation again until the optimal design solution that meets all performance requirements is found.

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