Wheel body detection method based on high-precision wear resistance test platform

Abstract

The invention discloses a wheel body detection method based on a high-precision wear resistance test platform, and the method achieves the precise evaluation of wear resistance under a complex working condition. The test platform is composed of a test pressurization system, a multi-dimensional monitoring system and an intelligent control system, and the test pressurization system comprises a test pressurization mechanism and a test simulation mechanism which are arranged in parallel and can simulate various road surface working conditions and pressure changes; the multi-dimensional monitoring system collects data in multiple aspects of vision, mechanics and the like in real time, and the intelligent control system achieves automatic testing and data processing. The test method comprises the steps of test preparation, initial contact calibration, multi-stage dynamic pressurization test, data processing analysis, wear resistance comprehensive evaluation and the like, a unique multi-stage dynamic loading mode is adopted, and machine learning and finite element analysis are combined; compared with the prior art, the actual working condition can be simulated more truly, all-around high-precision monitoring and precise evaluation are achieved, and powerful technical support is provided for research, development, production and quality control of the Mecanum wheel.

Description

Technical Field

[0001] This invention belongs to the field of testing equipment technology and relates to a wheel body testing method based on a high-precision wear-resistant testing platform. Background Technology

[0002] Mecanum wheels, as core components enabling omnidirectional movement, occupy an important position in modern automated equipment. Currently, while wear resistance testing methods for Mecanum wheels can assess their wear performance to some extent, they mostly employ single pressure or simple pressure increment modes, lacking accurate simulation of dynamic pressure changes and the coupling effects of multiple factors under complex actual working conditions. Furthermore, the means of monitoring the working state of the Mecanum wheel during testing are limited, making it difficult to grasp its performance changes in real time and comprehensively. This fails to meet the high standards required for the research and development and quality control of high-performance Mecanum wheels, necessitating innovative improvements to existing testing methods. Summary of the Invention

[0003] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A wheel body inspection method based on a high-precision wear resistance testing platform includes the following inspection steps: Test preparation: Select at least five brand-new Mecanum wheels of the same model and specifications as test samples and number them. Use a 3D scanner to obtain high-precision 3D models of the samples to record the initial geometric parameters. A high-precision wear resistance testing platform consisting of a test pressurization system, a multi-dimensional monitoring system, and an intelligent control system was constructed. The test simulation mechanism system includes: a processing machine table, a test pressurization mechanism and a test simulation mechanism installed on the processing machine table; the test pressurization mechanism and the test simulation mechanism are arranged in parallel structures; The test pressurization mechanism includes: a test wheel frame, a pressurization module for moving the test wheel frame towards one side of the test simulation mechanism, and a lateral movement module for moving the test wheel frame laterally. The test simulation mechanism includes: a road surface simulation wheel and a drive motor for driving the road surface simulation wheel to rotate; the surface of the road surface simulation wheel is provided with a replaceable composite friction material layer; The multi-dimensional monitoring system includes visual, mechanical, thermal, and attitude monitoring subsystems, and an intelligent control system that integrates test control software. A surface hardness tester, a surface roughness tester, and a high-precision electronic scale are used to measure and record the surface hardness of the sample rollers and hubs, the initial surface roughness of the rollers, and the sample mass. Initial contact and calibration: The Mecanum wheel to be tested is installed sequentially on the test wheel frame. The drive motor in the test simulation mechanism is started by the intelligent control system to drive the road simulation wheel to rotate. At the same time, the dynamic pressure module is controlled to drive the Mecanum wheel to move. When the two make contact, the position is recorded by the displacement sensor and calibrated as the initial position. The operation is maintained for 1 minute to stabilize the contact state. Multi-stage dynamic pressurization test: Starting from the initial position, the dynamic pressurization module applies multi-stage dynamic pressurization to each sample according to the pressure loading curve, which includes three stages: linear increase, cyclic fluctuation, and step increase. During the test, the multi-dimensional monitoring system collects data in real time at a frequency of 1000Hz. Every 5 minutes, the surface micro-morphology is photographed using a microscopic imaging lens. The test stops when the working posture of the Mecanum wheel is abnormal or the preset maximum pressure value is reached. The maximum bearing pressure value is calibrated and wear data is recorded. Data processing and analysis: The intelligent control system fuses and processes the multi-dimensional data of each sample to construct a multidimensional dataset; based on machine learning algorithms, the support vector regression algorithm is used to train the multidimensional dataset to establish a wear prediction model; and finite element analysis software is used to establish a dynamic wear simulation model for each sample based on the collected data. Comprehensive evaluation of wear resistance: A hierarchical wear resistance evaluation index system is constructed by integrating the dimensional wear, surface microstructure changes, mass loss, maximum bearing pressure, and wear prediction results of each sample under different pressure values. An improved analytic hierarchy process (AHP) is used to determine weights, and a comprehensive evaluation model is established based on grey relational analysis for quantitative scoring. Statistical analysis is performed on the evaluation results of multiple samples, and cluster analysis is used to summarize the characteristics and patterns of wear resistance. As a further aspect of the present invention: the multi-dimensional monitoring system includes a visual monitoring subsystem, a mechanical monitoring subsystem, a thermal monitoring subsystem, and an attitude monitoring subsystem; The visual monitoring subsystem uses a high-speed industrial camera and a microscope imaging lens in conjunction with an image recognition algorithm to automatically identify wear areas and measure wear depth and area. The mechanical monitoring subsystem has a multi-axial force sensor installed on the Mecanum axle and a thin-film strain gauge attached to the surface of the roller. The thermal monitoring subsystem uses an infrared thermal imager to monitor the temperature field distribution; the attitude monitoring subsystem uses an inertial measurement unit to monitor the tilt angle, rotational angular velocity and other working attitude parameters of the Mecanum wheel in real time.

[0004] As a further aspect of the present invention: in the linear increasing phase of the pressure loading curve, the pressure is uniformly increased from 0 to 50% of the rated load capacity of the Mecanum wheel at a loading rate of 50 N / min for 10 minutes; in the cyclic fluctuation phase, the pressure cyclically fluctuates sinusoidally between 50% and 80% of the rated load capacity at a frequency of 0.5 Hz for 30 minutes; in the step-increasing phase, the pressure is increased progressively in increments of 5% of the rated load capacity, with each pressure increment maintained for 5 minutes. The beneficial effects of this invention are as follows: It employs a multi-level dynamic loading mode encompassing linear increment, cyclic fluctuation, and step-increment stages. Compared to traditional single or simple increment modes, this mode more realistically simulates the complex pressure changes during actual operation of the Mecanum wheel, fully stimulating its wear characteristics. In terms of monitoring and analysis, a multi-dimensional monitoring system is constructed to achieve real-time, high-precision acquisition of visual, mechanical, thermal, and attitude information during the wear process of the Mecanum wheel. This allows for a comprehensive evaluation of the wear resistance and load-bearing capacity of the Mecanum wheel under different pressure conditions, providing a more comprehensive and reliable scientific basis for product development, quality control, and application selection. Attached Figure Description

[0005] Figure 1 This is a schematic diagram of the structure of the present invention. Detailed Implementation

[0006] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. It should be understood that this application is not limited to the exemplary embodiments disclosed herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0007] In the description of this invention, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0008] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0009] In the embodiments of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0010] This invention provides reference to [the relevant document]. Figure 1 In this embodiment of the invention, a wheel body testing method based on a high-precision wear-resistant testing platform includes: a high-precision wear-resistant testing platform; The high-precision wear resistance testing platform consists of a test pressurization system, a multi-dimensional monitoring system, and an intelligent control system. The test pressurization system includes a processing machine 1, a test pressurization mechanism 3, and a test simulation mechanism 2. The test pressurization mechanism 3 and the test simulation mechanism 2 are arranged in parallel. The test pressurization mechanism 3 is equipped with a test wheel frame 33, a pressurization module 31, and a lateral movement module 32. The test wheel frame 33 is used to securely mount the Mecanum wheel to be tested. The pressurization module 31 can drive the test wheel frame 33 to move and feed to one side of the test simulation mechanism 2, thereby applying pressure to the Mecanum wheel and simulating its state of bearing heavy objects in actual work. The lateral movement module 32 can drive the test wheel frame 33 to move laterally, which facilitates precise adjustment of the relative position of the Mecanum wheel and the road surface simulation wheel 21 to ensure uniform pressure distribution.

[0011] The test simulation mechanism 2 mainly includes a road surface simulation wheel 21 and a drive motor 22. The drive motor 22 is used to drive the road surface simulation wheel 21 to rotate. The surface of the road surface simulation wheel 21 is provided with a replaceable composite friction material layer. By changing the friction layer of different materials, various actual working road surface conditions such as cement floors in factory workshops and wooden floors in warehouses can be simulated, making the test more in line with real use scenarios.

[0012] The multi-dimensional monitoring system encompasses visual, mechanical, thermal, and attitude monitoring subsystems. The visual monitoring subsystem utilizes high-speed industrial cameras and microscopic imaging lenses, combined with advanced image recognition algorithms, to identify wear areas on the surface of the Mecanum wheel in real time and automatically, and to accurately measure the wear depth and area. The mechanical monitoring subsystem installs multi-axial force sensors on the Mecanum wheel axle and attaches thin-film strain gauges to the roller surface to monitor in real time the axial force, radial force, torque and stress distribution on the roller surface of the Mecanum wheel during the test. The thermal monitoring subsystem uses an infrared thermal imager to monitor the temperature field distribution of the Mecanum wheel in real time and explores the intrinsic relationship between temperature changes and wear by analyzing temperature changes. The attitude monitoring subsystem uses an inertial measurement unit (IMU) to monitor the tilt angle, rotational angular velocity and other working attitude parameters of the Mecanum wheel in real time. When the attitude change exceeds the preset threshold, the system will automatically alarm to ensure test safety and data accuracy.

[0013] The intelligent control system integrates professional test control software, based on industrial computers and programmable logic controllers (PLCs), to achieve automated control of the entire test process, real-time acquisition and processing of multi-dimensional monitoring data, and precise adjustment of test parameters according to preset programs.

[0014] The specific implementation steps of the Mecanum wheel wear resistance test method based on the above test platform are as follows: S1: Test preparation: Select at least five Mecanum wheels of the same model and specifications that are in brand new condition as test samples, number and mark them one by one, use a 3D scanner to obtain a high-precision 3D model of each sample, record its initial geometric parameters in detail, and ensure the consistency between samples.

[0015] The high-precision wear-resistant testing platform was built and debugged on the processing machine 1. According to the target test conditions, the surface of the road surface simulation wheel 21 was replaced with the corresponding composite friction material layer. At the same time, a surface hardness tester, a surface roughness tester, and a high-precision electronic scale were used to measure the surface hardness, initial surface roughness of the roller, and sample mass of each sample roller and hub, and detailed records were made to provide basic data for subsequent tests.

[0016] S2: Initial Contact and Calibration: The numbered Mecanum wheels to be tested are sequentially installed onto the test wheel frame 33. The drive motor 22 in the test simulation mechanism 2 is started through the intelligent control system, causing the road surface simulation wheel 21 to rotate at a speed of 100 r / min. At the same time, the pressure module 31 is controlled to slowly move the test wheel frame 33 towards the test simulation mechanism 2. When the Mecanum wheel contacts the road surface simulation wheel 21, the contact position is accurately recorded by the displacement sensor and calibrated as the initial position. This state is maintained for 1 minute to stabilize the contact state between the two, laying the foundation for subsequent tests.

[0017] S3: Multi-stage dynamic pressurization test: Starting from the initial position, the pressurization module 31 strictly follows the preset pressure loading curve, which includes three stages: linear increase, cyclic fluctuation and step increase, to conduct multi-stage dynamic pressurization tests on each test sample.

[0018] In the linear increment phase, the pressure increases uniformly from 0 to 50% of the Mecanum wheel's rated load capacity, with a loading rate set at 50 N / min. This phase lasts for 10 minutes, simulating the light-load start-up process of the Mecanum wheel. In the cyclic fluctuation phase, the pressure cyclically fluctuates between 50% and 80% of the rated load capacity in a sinusoidal form, with a fluctuation frequency of 0.5 Hz, for 30 minutes, simulating the pressure fluctuations caused by load changes during normal operation of the Mecanum wheel. In the step increment phase, the pressure is increased step by step in increments of 5% of the rated load capacity, with each pressure level maintained for 5 minutes, until the Mecanum wheel exhibits abnormal working posture (such as a tilt angle exceeding 5° or a rotational angular velocity fluctuation exceeding 20%) or reaches the preset maximum pressure value, simulating the working state of the Mecanum wheel under heavy load or overload conditions.

[0019] Throughout the testing process, the multi-dimensional monitoring system acquired real-time data on vision, mechanics, thermal properties, and attitude at a high frequency of 1000Hz. Every 5 minutes, a high-resolution image of a specific area on the Mecanum wheel surface was taken using a microscopic imaging lens to record changes in the surface microstructure. The test was immediately stopped if the Mecanum wheel's working posture became abnormal or if the preset maximum pressure value was reached. The maximum load-bearing pressure value was accurately calibrated, and the wear data at that moment was recorded in detail.

[0020] S4: Data Processing and Analysis: The intelligent control system performs in-depth fusion processing on the multi-dimensional data of each test sample, uses digital filtering algorithms to remove noise interference, and uses time synchronization technology to accurately align different types of data, constructing a multi-dimensional dataset for each sample containing information such as pressure, wear, stress distribution, temperature field, and working posture.

[0021] Based on machine learning algorithms, a support vector regression (SVR) algorithm is used to train a multidimensional dataset to establish a high-precision wear prediction model, which can accurately predict the wear of Mecanum wheels under different pressure conditions, and deeply analyze the influence weight of each factor on wear performance.

[0022] Using finite element analysis software, dynamic wear simulation models were established for each sample based on the collected geometric parameters, mechanical data, and wear conditions. These models simulated the stress-strain distribution and wear evolution of the Mecanum wheel under different pressure loading processes, verifying the accuracy and reliability of the test results.

[0023] S5: Comprehensive evaluation of wear resistance performance: Taking into account various factors such as the dimensional wear, surface microstructure changes, mass loss, maximum bearing pressure, and wear prediction results of each Mecanum wheel sample under different pressure values, a hierarchical wear resistance performance evaluation index system is constructed.

[0024] An improved analytic hierarchy process (AHP) was used to scientifically determine the weights of each evaluation index, and a comprehensive evaluation model based on grey relational analysis was established to quantitatively score the wear resistance performance of each Mecanum wheel sample. A comprehensive statistical analysis was conducted on the evaluation results of multiple test samples, and cluster analysis was used to classify the wear characteristics of different samples. The wear resistance performance characteristics of this type of Mecanum wheel under different pressure conditions were summarized and generalized, providing a scientific and reliable basis for the optimized design and practical application of Mecanum wheel products.

[0025] The present application is further illustrated below with reference to embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the present application.

[0026] Wear resistance tests were conducted on a Mecanum wheel of a certain model used in industrial handling robots. Five brand-new samples were selected and numbered M1-M5. A high-precision wear resistance testing platform was prepared, and the surface of the road surface simulation wheel 21 was replaced with a composite friction material layer simulating the cement floor of a factory workshop. A 3D scanner was used to obtain a 3D model of each sample, and the initial geometric parameters were recorded. The initial surface hardness of each sample roller was measured to be 60 HRC, the initial roughness Ra was 0.2 μm, and the initial mass was 1.2 kg.

[0027] Sample M1 was mounted on test wheel frame 33, and the test procedure was initiated. The test was conducted according to the pressure loading curve: In the first stage, the pressure was uniformly increased from 0 to 150N (50% of the rated load capacity of 300N) over 10 minutes; in the second stage, the pressure fluctuated sinusoidally between 150N and 240N at a frequency of 0.5Hz for 30 minutes; in the third stage, the pressure was increased incrementally in increments of 15N, each increment held for 5 minutes. When the pressure reached 360N (120% of the rated load capacity), the tilt angle of sample M1 exceeded 5°, the intelligent control system stopped the test, and this pressure value was recorded as the maximum load pressure value of sample M1.

[0028] Following the same procedure, samples M2-M5 were tested sequentially. During the testing process, the multi-dimensional monitoring system collected data for each sample in real time. After the test, the data was processed and analyzed, and the specific experimental data generated are as follows: Sample number Roller diameter wear (mm) Surface roughness (Ra / μm) Mass loss (kg) Maximum bearing pressure (N) Maximum stress (MPa) Maximum temperature (°C) Maximum tilt angle (°) M1 0.60 0.40 0.008 360 85.2 58.3 5.2 M2 0.58 0.38 0.007 375 82.1 56.5 4.8 M3 0.62 0.42 0.009 345 88.6 60.1 5.5 M4 0.55 0.35 0.006 390 79.8 54.2 4.5 M5 0.57 0.37 0.0075 365 83.4 57.0 5.0 Analysis using a wear prediction model revealed that, under rated load capacity, the expected operating time for this model of Mecanum wheel to reach the critical wear value (1.0 mm roller diameter wear) is: M1 780 hours, M2 820 hours, M3 750 hours, M4 850 hours, M5 800 hours, with an average of 800 hours. Using a comprehensive evaluation model, the wear resistance score was calculated as follows: Sample M1 82 points, Sample M2 81 points, Sample M3 80 points, Sample M4 83 points, and Sample M5 82 points. Cluster analysis of the evaluation results for the five samples showed that the wear resistance of the roller material and the structural design had the most significant impact on the wear resistance and load capacity of the Mecanum wheel.

[0029] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0030] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A wheel body inspection method based on a high-precision wear resistance testing platform, characterized in that, Includes the following testing steps Test preparation: Select at least five brand-new Mecanum wheels of the same model and specifications as test samples and number them. Use a 3D scanner to obtain high-precision 3D models of the samples to record the initial geometric parameters. A high-precision wear resistance testing platform consisting of a test pressurization system, a multi-dimensional monitoring system, and an intelligent control system was constructed. The test simulation mechanism system includes: a processing machine table, a test pressurization mechanism and a test simulation mechanism installed on the processing machine table; the test pressurization mechanism and the test simulation mechanism are arranged in parallel structures; The test pressurization mechanism includes: a test wheel frame, a pressurization module for moving the test wheel frame towards one side of the test simulation mechanism, and a lateral movement module for moving the test wheel frame laterally. The test simulation mechanism includes: a road surface simulation wheel and a drive motor for driving the road surface simulation wheel to rotate; the surface of the road surface simulation wheel is provided with a replaceable composite friction material layer; The multi-dimensional monitoring system includes visual, mechanical, thermal, and attitude monitoring subsystems, and an intelligent control system that integrates test control software. A surface hardness tester, a surface roughness tester, and a high-precision electronic scale are used to measure and record the surface hardness of the sample rollers and hubs, the initial surface roughness of the rollers, and the sample mass. Initial contact and calibration: The Mecanum wheel to be tested is installed sequentially on the test wheel frame. The drive motor in the test simulation mechanism is started by the intelligent control system to drive the road simulation wheel to rotate. At the same time, the dynamic pressure module is controlled to drive the Mecanum wheel to move. When the two make contact, the position is recorded by the displacement sensor and calibrated as the initial position. The operation is maintained for 1 minute to stabilize the contact state. Multi-stage dynamic pressurization test: Starting from the initial position, the dynamic pressurization module applies multi-stage dynamic pressurization to each sample according to the pressure loading curve, which includes three stages: linear increase, cyclic fluctuation, and step increase. During the test, the multi-dimensional monitoring system collects data in real time at a frequency of 1000Hz. Every 5 minutes, the surface micro-morphology is photographed using a microscopic imaging lens. The test stops when the working posture of the Mecanum wheel is abnormal or the preset maximum pressure value is reached. The maximum bearing pressure value is calibrated and wear data is recorded. Data processing and analysis: The intelligent control system fuses and processes the multi-dimensional data of each sample to construct a multidimensional dataset; based on machine learning algorithms, the support vector regression algorithm is used to train the multidimensional dataset to establish a wear prediction model; and finite element analysis software is used to establish a dynamic wear simulation model for each sample based on the collected data. Comprehensive evaluation of wear resistance: By combining the dimensional wear, surface microstructure changes, mass loss, maximum bearing pressure, and wear prediction results of each sample under different pressure values, a hierarchical wear resistance evaluation index system is constructed. The weights are determined by an improved hierarchical analysis method, and a comprehensive evaluation model is established based on grey relational analysis for quantitative scoring. Statistical analysis is performed on the evaluation results of multiple samples, and cluster analysis is used to summarize the wear resistance characteristics.

2. The wheel body inspection method based on a high-precision wear resistance testing platform according to claim 1, characterized in that, The multi-dimensional monitoring system includes a visual monitoring subsystem, a mechanical monitoring subsystem, a thermal monitoring subsystem, and an attitude monitoring subsystem; The visual monitoring subsystem uses a high-speed industrial camera and a microscope imaging lens in conjunction with an image recognition algorithm to automatically identify wear areas and measure wear depth and area. The mechanical monitoring subsystem has a multi-axial force sensor installed on the Mecanum axle and a thin-film strain gauge attached to the surface of the roller. The thermal monitoring subsystem uses an infrared thermal imager to monitor the temperature field distribution; the attitude monitoring subsystem uses an inertial measurement unit to monitor the tilt angle, rotational angular velocity and other working attitude parameters of the Mecanum wheel in real time.

3. The wheel body inspection method based on a high-precision wear resistance testing platform according to claim 1, characterized in that, In the linear increasing phase of the pressure loading curve, the pressure is uniformly increased from 0 to 50% of the rated load capacity of the Mecanum wheel at a loading rate of 50 N / min for 10 minutes. During the cyclic fluctuation phase, the pressure cyclically fluctuates at a frequency of 0.5Hz between 50% and 80% of the rated load capacity for 30 minutes. In the stepped increase phase, the pressure is increased step by step in increments of 5% of the rated load capacity, and each pressure level is maintained for 5 minutes.

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