A performance testing method and system for a high-precision guide rail and lead screw

Abstract

The present application provides a performance testing method and system for a high-precision guide rail screw, relating to the technical field of mechanical performance testing. The method includes: receiving a performance testing task for the guide rail screw, randomly dividing multiple guide rail screws according to the first test sample division condition, performing multi-level static stiffness testing on the first guide rail screw group, performing load capacity testing on the second guide rail screw group, performing wear performance testing on the third guide rail screw group, and generating a performance testing report for the guide rail screw. By means of the present application, the technical problem in the prior art that the performance testing effect of the guide rail screw is poor due to high performance testing error of the guide rail screw can be solved. By receiving the testing task, randomly dividing the guide rail screws into three groups, respectively performing static stiffness, load capacity and wear performance testing, and finally integrating the testing results to generate a performance testing report, the technical effect of improving the performance testing accuracy of the guide rail screw is achieved.

Description

Technical Field

[0001] This application relates to the technical field of mechanical performance testing, and particularly to a performance testing method and system for a high-precision guide rail screw. Background Art

[0002] A guide rail screw is a precision mechanical component widely used in various industrial fields such as automation equipment and precision machine tools. Its main function is to convert rotational motion into linear motion while maintaining high precision and stability. Therefore, testing the performance of the guide rail screw is the key to ensuring that it can meet the design requirements in actual applications. Currently, there are errors in the performance testing of guide rail screws in the existing technology, resulting in poor performance testing effects of the guide rail screws.

[0003] In summary, there is a technical problem in the existing technology that due to the high performance testing error of the guide rail screw, the performance testing effect of the guide rail screw is poor. Summary of the Invention

[0004] The purpose of this application is to provide a performance testing method and system for a high-precision guide rail screw to solve the technical problem in the existing technology that due to the high performance testing error of the guide rail screw, the performance testing effect of the guide rail screw is poor.

[0005] In view of the above problems, this application provides a performance testing method and system for a high-precision guide rail screw.

[0006] In a first aspect, this application provides a performance testing method for a high-precision guide rail screw. The method is implemented through a performance testing system for a high-precision guide rail screw. Among them, the method includes: receiving a guide rail screw performance testing task, where the guide rail screw performance testing task includes multiple guide rail screws with the same production process information; obtaining a first test sample division condition; randomly dividing the multiple guide rail screws according to the first test sample division condition to obtain a first guide rail screw group, a second guide rail screw group, and a third guide rail screw group; performing multi-level static stiffness testing according to the first guide rail screw group to obtain a static stiffness testing result; performing load capacity testing according to the second guide rail screw group to obtain a load capacity testing result; performing wear performance testing according to the third guide rail screw group to obtain a wear performance testing result; integrating the static stiffness testing result, the load capacity testing result, and the wear performance testing result to generate a guide rail screw performance testing report.

[0007] Second aspect, the present application also provides a performance testing system for a high-precision guide rail screw, which is used to execute a performance testing method for a high-precision guide rail screw as described in the first aspect. Among them, the system includes: a receiving test task module, which is used to receive a guide rail screw performance test task, where the guide rail screw performance test task includes multiple guide rail screws with the same production process information; a determining division condition module, which is used to obtain a first test sample division condition; a random division module, which is used to randomly divide the multiple guide rail screws according to the first test sample division condition to obtain a first guide rail screw group, a second guide rail screw group, and a third guide rail screw group; a static stiffness testing module, which is used to perform multi-level static stiffness testing on the first guide rail screw group to obtain a static stiffness test result; a load capacity testing module, which is used to perform a load capacity test on the second guide rail screw group to obtain a load capacity test result; a wear performance testing module, which is used to perform a wear performance test on the third guide rail screw group to obtain a wear performance test result; a report generation module, which is used to integrate the static stiffness test result, the load capacity test result, and the wear performance test result to generate a guide rail screw performance test report.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] By receiving a guide rail screw performance test task, where the guide rail screw performance test task includes multiple guide rail screws with the same production process information; obtaining a first test sample division condition; randomly dividing the multiple guide rail screws according to the first test sample division condition to obtain a first guide rail screw group, a second guide rail screw group, and a third guide rail screw group; performing multi-level static stiffness testing on the first guide rail screw group to obtain a static stiffness test result; performing a load capacity test on the second guide rail screw group to obtain a load capacity test result; performing a wear performance test on the third guide rail screw group to obtain a wear performance test result; integrating the static stiffness test result, the load capacity test result, and the wear performance test result to generate a guide rail screw performance test report. That is to say, by receiving the test task, randomly dividing the guide rail screws into three groups, respectively performing static stiffness, load capacity, and wear performance tests, and finally integrating the test results to generate a performance test report, the technical effect of improving the performance test accuracy of the guide rail screw is achieved.

[0010] The above description is only an overview of the technical solution of the present application. In order to better understand the technical means of the present application, it can be implemented according to the content of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the specific embodiments of the present application are given below. It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understood through the following description. Description of the Drawings

[0011] In order to more clearly illustrate the technical solutions in the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings described below are only exemplary. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on the provided drawings.

[0012] Figure 1 It is a schematic flow diagram of a performance test method for a high-precision guide rail screw of the present application.

[0013] Figure 2 It is a schematic structural diagram of a performance test system for a high-precision guide rail screw of the present application.

[0014] Description of the reference numerals: receiving test task module 11, determining division condition module 12, random division module 13, static stiffness test module 14, load capacity test module 15, wear performance test module 16, report generation module 17. Detailed Embodiments

[0015] By providing a performance test method and system for a high-precision guide rail screw, the present application solves the technical problem in the prior art that due to the high performance test error of the guide rail screw, the performance test effect of the guide rail screw is poor. By receiving the test task, randomly dividing the guide rail screws into three groups, respectively performing static stiffness, load capacity and wear performance tests, and finally integrating the test results to generate a performance test report, the technical effect of improving the performance test accuracy of the guide rail screw is achieved.

[0016] Next, the technical solutions in the present application will be clearly and completely described with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application. Additionally, it should be noted that for the sake of description, only the parts related to the present application are shown in the drawings rather than all of them.

[0017] Example 1

[0018] Please refer to the appendix Figure 1 , this application provides a performance testing method for a high-precision guide rail screw. Among them, the method is applied to a performance testing system for a high-precision guide rail screw, and the method specifically includes the following steps:

[0019] Step 1: Receive the guide rail screw performance testing task. Among them, the guide rail screw performance testing task includes multiple guide rail screws with the same production process information.

[0020] Specifically, understand the specific requirements of the testing task in detail, including testing standards, performance indicators, testing environmental conditions, etc., and confirm the production process information, including materials, processing techniques, heat treatment, etc. For example, different materials and processing techniques may lead to differences in aspects such as the hardness, wear resistance, and fatigue life of the guide rail screw. According to the testing requirements, prepare the corresponding testing equipment, such as drive motors, displacement sensors, data acquisition cards, etc. At the same time, ensure that the testing environment meets the requirements, such as factors affecting the accuracy of the testing results, such as temperature, humidity, and cleanliness. Receiving the testing task includes multiple guide rail screws, and all the guide rail screws to be tested are manufactured under the same production conditions, thus ensuring their basic consistency in aspects such as materials, dimensions, and processing processes. Ensure that all test samples come from the same production batch, reduce performance differences caused by production process differences, and improve the comparability of testing results.

[0021] Step 2: Obtain the first test sample division condition.

[0022] Specifically, obtaining the division condition includes determining key parameters such as the sample quantity, division ratio, and randomization method, etc. Determine that the sample quantity is large enough, considering the feasibility cost-benefit of actual operation. Based on the testing purpose and requirements, reasonably divide multiple guide rail screws into different test groups. The division conditions include the sample quantity, division ratio, randomization method, etc. For example, it can be divided according to an equal ratio, or the division ratio can be adjusted according to specific testing requirements. Through random division, reduce sample selection bias, so that each guide rail screw has the same chance of being assigned to different test groups, ensuring the fairness and unbiasedness of sample division.

[0023] Step 3: Randomly divide the multiple guide rail screws according to the first test sample division condition to obtain the first guide rail screw group, the second guide rail screw group, and the third guide rail screw group.

[0024] Specifically, the guideway ball screws are randomly divided into a first guideway ball screw group, a second guideway ball screw group, and a third guideway ball screw group. Each group of guideway ball screws will be used for different test purposes or stages. The division of these groups will be used for different performance tests, such as multi-level static stiffness tests, load capacity tests, and wear performance tests. By randomly dividing the guideway ball screws, it can be ensured that each guideway ball screw has an equal chance of being selected as a test sample, thereby improving the fairness and objectivity of the test results, helping to ensure the representativeness of the test samples, and improving the accuracy and reliability of the test results.

[0025] Step Four: Conduct a multi-level static stiffness test according to the first guideway ball screw group to obtain the static stiffness test results.

[0026] Specifically, conduct a static stiffness test on the first guideway ball screw group to test its deformation under different loads. The static stiffness test is to evaluate the ability of the guideway ball screw to resist deformation under static loads. It provides detailed information on the stiffness performance of the guideway ball screw under different working conditions, evaluates the ability of the guideway ball screw to resist deformation under static loads, and obtains the static stiffness performance index of the guideway ball screw.

[0027] Step Five: Conduct a load capacity test according to the second guideway ball screw group to obtain the load capacity test results.

[0028] Specifically, conduct a load capacity test on the second guideway ball screw group to evaluate its performance under the maximum load. It is necessary to conduct a rated load capacity test and an ultimate load capacity test. The rated load capacity refers to the ability of the guideway ball screw to operate for a long time without fatigue damage or permanent deformation under normal working conditions. It is usually determined by the manufacturer according to the product design and material characteristics. It is a safe working load that can ensure the reliability and lifespan of the product. The ultimate load capacity refers to the maximum load that the guideway ball screw can withstand in a short time without permanent deformation or damage. It is usually the strength limit of the guideway ball screw material, that is, the material will not break or undergo plastic deformation when subjected to the maximum force. The rated load capacity takes into account the fatigue life of the material and the reliability of long-term operation, and is a practical and usable value. The ultimate load capacity takes into account the strength limit of the material under the instantaneous maximum force and is a theoretical maximum value. The rated load capacity is usually less than or equal to the ultimate load capacity because sufficient safety margins need to be left to ensure the reliability of long-term operation. The load capacity test helps to evaluate the performance of the guideway ball screw under actual working conditions, ensures that the guideway ball screw can operate stably under the rated working load, and remains safe under extreme conditions.

[0029] Step Six: Conduct a wear performance test according to the third guideway ball screw group to obtain the wear performance test results.

[0030] Specifically, conduct wear performance tests on the third guide screw group to simulate the wear situation after long-term use. By constructing multiple different test scenarios that cover different working conditions and environments, comprehensively evaluate the wear performance of the guide screw. Identify the complexity of each test scenario to determine which test scenarios require more resources and attention, and how to optimize the test process. According to the total number of guide screws and the complexity of the test scenarios, reasonably allocate test samples to ensure that each test scenario has sufficient samples for effective wear tests. Evaluate the test results, including the degree of wear, wear rate, wear mode, etc. Combine the screw wear performance test scenarios and the corresponding scenario wear performance coefficients to form a complete set of wear performance test results. Predict the service life of the guide screw to provide important information for users regarding the maintenance cycle and replacement time.

[0031] Step Seven: Integrate the static stiffness test results, the load capacity test results, and the wear performance test results to generate a guide screw performance test report.

[0032] Specifically, collect and organize the static stiffness test results, the load capacity test results, and the wear performance test results, including the performance indicators of the guide screw under different conditions, such as stiffness, deformation, load capacity, wear amount, etc. Compare the correlations between different test results to determine the performance of the guide screw under different performance indicators. For example, the relationship between the static stiffness test results and the load capacity test results can be analyzed to evaluate the overall performance of the guide screw. Integrate the static stiffness test results, the load capacity test results, and the wear performance test results to provide a comprehensive and integrated evaluation of the guide screw performance. Organize the integrated test results into a report format, including test conditions, test data, analysis results, etc. Provide a comprehensive performance evaluation to help comprehensively understand the performance of the guide screw, making the test results more accurate and reliable.

[0033] Furthermore, Step Four of this application includes:

[0034] Obtain the second test sample division condition; randomly divide the first guide screw group according to the second test sample division condition to obtain the first guide screw partition and the second guide screw partition; conduct multi-level axial stiffness test evaluations based on the first guide screw partition to obtain axial stiffness test results; conduct multi-level radial stiffness test evaluations based on the second guide screw partition to obtain radial stiffness test results; add the axial stiffness test results and the radial stiffness test results to the static stiffness test results.

[0035] Specifically, based on the specific properties of the guide screw, such as size, material properties, etc., in the static stiffness test stage, the first guide screw group needs to be further subdivided for axial and radial stiffness testing. The first guide screw group is randomly divided using the second test sample division condition to ensure that each guide screw has an equal chance of being selected to obtain the first guide screw partition and the second guide screw partition.

[0036] The multi-level axial stiffness test is to evaluate the guide screw's ability to resist deformation under different axial loads. The first partition is subjected to a multi-level axial stiffness test and evaluation, and different levels of axial loads are applied to each sample to test the deformation of the guide screw when subjected to the axial load. According to the test results, the axial stiffness of the guide screw is evaluated, including indicators such as stiffness coefficient and deformation, which reflect the performance of the guide screw under axial load. The deformation data obtained from the test is processed and analyzed, such as calculating the stiffness value, drawing the stiffness curve, etc., and the test results are organized into a report form, including test conditions, test data, analysis results, etc. Similarly, the multi-level radial stiffness test is intended to evaluate the guide screw's ability to resist deformation under different radial loads. The second partition is subjected to a multi-level radial stiffness test, and different levels of radial loads are applied to each sample, and its deformation is measured. These load levels should cover the typical working load range in actual applications. According to the test results, the radial stiffness of the guide screw is evaluated, a multi-level radial stiffness test evaluation is obtained, radial stiffness test results are obtained, and a radial stiffness test report is generated. Axial stiffness and radial stiffness are two important aspects of the static stiffness performance of guide screws. Combining the two can more comprehensively evaluate the static stiffness of guide screws. The axial stiffness test results and radial stiffness test results are analyzed comprehensively to form the complete results of the static stiffness test. By comparing the test results of axial stiffness and radial stiffness, the overall performance balance of the guide screw can be evaluated.

[0037] Furthermore, the present application also includes the following steps:

[0038] Predict the axial load constraint interval of the guide screw according to the production process information; set the axial load test samples according to the axial load constraint interval of the guide screw to obtain the K-level axial load test samples, where K is a positive integer greater than 1; based on the K-level axial load test samples, conduct an axial stiffness test on the first partition of the guide screw to obtain multiple guide screw deformation monitoring data sets; activate the axial stiffness evaluation model, and combine the K-level axial load test samples and the multiple guide screw deformation monitoring data sets to conduct an axial stiffness evaluation to obtain multiple screw axial stiffness index sets, where each screw axial stiffness index set includes K screw axial stiffness indexes; calculate the median value of the same-level load stiffness evaluation set according to the multiple screw axial stiffness index sets to obtain the K-level load axial stiffness confidence coefficient; calculate the axial load ratio according to the K-level axial load test samples to obtain the K-level load weight coefficient; perform a weighted calculation on the K-level load axial stiffness confidence coefficient according to the K-level load weight coefficient to generate the axial stiffness test result.

[0039] Specifically, the production process information includes the material, design parameters, processing technology, etc. of the guide screw. According to the material characteristics of the guide screw, the axial load range that it may bear under normal working conditions is predicted through methods such as finite element analysis and mechanical calculation. The axial load constraint interval of the guide screw refers to the maximum and minimum axial loads determined according to factors such as its material, structure, manufacturing process, and expected use conditions when designing the guide screw. This interval can ensure that the guide screw will not be damaged due to overloading or underloading under normal working conditions. For example, if the guide screw is made of high-strength alloy steel and has undergone a specific heat treatment process, its axial load constraint interval may increase accordingly. According to the axial load constraint interval of the guide screw, the axial load can be divided into K levels. Each level corresponds to a specific axial load value, and these values should be evenly distributed within the axial load constraint interval of the guide screw. These samples should cover the predicted axial load constraint interval to ensure the comprehensiveness and accuracy of the test results.

[0040] According to the K-level axial load test sample, the corresponding level of axial load is applied to each sample in the first partition of the guide screw. The deformation of the guide screw is monitored using high-precision measuring equipment, including strain gauges, displacement sensors, etc., which can accurately measure the small deformation of the guide screw under the axial load. According to the measurement data, multiple guide screw deformation monitoring data sets are obtained, each of which contains the guide screw deformation data corresponding to different axial load levels. The axial stiffness evaluation model is an algorithm based on physical principles or statistical analysis, which can process test data and output stiffness index. This model needs to be able to adapt to different levels of axial load test samples and be able to process multiple data sets. The K-level axial load test sample and multiple guide screw deformation monitoring data sets are input into the axial stiffness evaluation model. The model calculates the stiffness performance of each guide screw under different axial loads based on these data, including determining the deformation of the guide screw, calculating the stiffness coefficient, etc. Output multiple screw axial stiffness index sets. Each index set includes K screw axial stiffness indexes, and each index corresponds to a specific axial load level. The evaluation model may use an algorithm based on physical principles or statistical analysis to convert the test data into a stiffness index that is easy to understand and compare. For example, the model calculates the ratio between the axial deformation of each guide screw and the applied axial load to obtain the axial stiffness index.

[0041] For each load level, all the screw axial stiffness indices are summarized, that is, the stiffness indices from different guide screws are grouped according to the load level, so as to compare the performance at the same level. Calculate the concentrated value of the stiffness evaluation at each load level by calculating the mean, median or other statistics. The mean can provide an overall performance trend, while the median can better reflect the intermediate performance level, especially when the data distribution is uneven. Calculate the confidence coefficient of the axial stiffness of the K-level load using the confidence interval method in statistics. The confidence coefficient is a statistical indicator that reflects the reliability and stability of the concentrated value of the stiffness evaluation. A high confidence coefficient means that the concentrated value of the stiffness evaluation has high reliability and stability, while a low confidence coefficient indicates that the data has large variability or instability.

[0042] Calculate the contribution of each load level throughout the test to obtain the K-level load weight coefficient. Determine the number of test samples for each axial load level. Ideally, each level should have the same number of samples to ensure the fairness and comparability of the test results. However, in practical applications, the number of samples may vary due to various reasons. Calculate the sample proportion of each axial load level by dividing the number of samples in each level by the total number of samples, which reflects the importance of each load level in the entire test. Calculate the K-level load weight coefficient based on the sample proportion by normalizing the sample proportion of each load level. The normalization process ensures that the sum of all weight coefficients is 1, enabling them to be used for weighted analysis. Among them, the K-level load weight coefficient reflects the importance of each load level in the entire test, while the K-level load axial stiffness confidence coefficient is a quantitative evaluation of the stiffness performance under each load level. Multiply the K-level load axial stiffness confidence coefficient by the corresponding K-level load weight coefficient to weight the stiffness performance under each load level. Sum the weighted K-level load axial stiffness confidence coefficients to generate the axial stiffness test result.

[0043] By predicting the axial load constraint interval, setting the axial load test samples, conducting the axial stiffness test, activating the axial stiffness evaluation model, calculating the centralized value of the stiffness evaluation of the same-level load, calculating the K-level load weight coefficient, and performing weighted calculation on the K-level load axial stiffness confidence coefficient, comprehensively evaluate the axial stiffness performance of the guide screw, ensuring that the axial stiffness of the guide screw is within the design expectation range and can be adjusted according to the actual working conditions.

[0044] Further, step five of the present application includes:

[0045] Predict the load characteristics of the guide screw according to the production process information to determine the expected rated load and the expected ultimate load of the screw; obtain the third test sample division condition; randomly divide the second guide screw group according to the third test sample division condition to obtain the third partition of the guide screw and the fourth partition of the guide screw; conduct a rated load capacity test analysis on the third partition of the guide screw based on the expected rated load of the screw to determine the qualified coefficient of the rated load capacity; conduct an ultimate load capacity test analysis on the fourth partition of the guide screw based on the expected ultimate load of the screw to determine the qualified coefficient of the ultimate load capacity; add the qualified coefficient of the rated load capacity and the qualified coefficient of the ultimate load capacity to the load capacity test result.

[0046] Specifically, analyze factors such as the material properties, design parameters, and machining processes of the guideway screw to predict the expected rated load and expected ultimate load of the guideway screw. The expected rated load refers to the maximum load that the guideway screw can withstand under normal working conditions, while the expected ultimate load refers to the maximum load that the guideway screw can withstand under extreme working conditions. According to the requirements of the load capacity test, subdivide the second guideway screw group to conduct the rated load capacity and ultimate load capacity tests, obtaining the third partition of the guideway screw and the fourth partition of the guideway screw. Conduct a rated load capacity test on the third partition of the guideway screw, collect the test data of multiple guideway screws under the rated load, and based on the expected rated load of the screw, conduct a deviation analysis on the rated load test data of each screw. The result of each deviation analysis can form a rated load deviation vector, conduct a qualified depth evaluation of the rated load capacity for multiple rated load deviation vectors, and calculate a qualified depth coefficient for the rated load capacity of each screw. Based on the central value of the calculated qualified depth coefficients, determine the rated load capacity qualification coefficient of the third partition of the guideway screw.

[0047] Test the samples in the fourth partition of the guideway screw under the expected ultimate load, analyze their performance, and determine the load capacity of the guideway screw under extreme working conditions. The ultimate load capacity refers to the maximum load that the guideway screw can withstand in a short period of time without permanent deformation or damage, which is usually the limit of the material strength of the guideway screw, that is, the material will not break or undergo plastic deformation when subjected to the maximum force. The ultimate load capacity is a theoretical maximum value and should not be exceeded in actual applications. According to the test results, calculate the ultimate load capacity qualification coefficient.

[0048] The rated load capacity qualification coefficient reflects whether the load capacity of the guideway screw under normal working conditions meets the design requirements, taking into account the fatigue life of the material and the reliability of long-term operation. The ultimate load capacity qualification coefficient reflects the load capacity of the guideway screw under extreme conditions, that is, the safety under overload conditions, taking into account the strength limit of the material under the instantaneous maximum force. Usually, the rated load capacity is a practically available value, while the ultimate load capacity is a theoretical maximum value. The rated load capacity needs to be less than or equal to the ultimate load capacity because sufficient safety margins are required to ensure the reliability of long-term operation. Add the rated load capacity qualification coefficient and the ultimate load capacity qualification coefficient to the load capacity test results. By determining the rated load capacity qualification coefficient and the ultimate load capacity qualification coefficient, the load capacity of the guideway screw under different working conditions can be comprehensively evaluated to ensure its stability and safety under normal and extreme conditions.

[0049] Furthermore, the present application further includes the following steps:

[0050] Perform a rated load test according to the third partition of the guide screw, and obtain multiple rated load test data of the screw; based on the expected rated load of the screw, perform deviation analysis on the multiple rated load test data of the screw respectively to obtain multiple rated load deviation vectors; perform a qualified depth evaluation of the rated load capacity according to the multiple rated load deviation vectors to obtain multiple qualified depth coefficients of the rated load capacity; calculate the central value of the multiple qualified depth coefficients of the rated load capacity to generate the qualified coefficient of the rated load capacity.

[0051] Specifically, for the samples in the third partition of the guide screw, perform a test load test under the expected rating, record its performance data, and collect the test data of multiple guide screws under the rated load. Based on the expected rated load of the screw, perform deviation analysis on the rated load test data of each screw to calculate the difference between the actual load and the expected load. The result of each deviation analysis can form a rated load deviation vector, indicating the difference between the actual load and the expected load of each screw. These differences can be absolute deviations or relative deviations. Perform a qualified depth evaluation of the rated load capacity on the multiple rated load deviation vectors. The rated load refers to the maximum load that the guide screw can withstand under normal working conditions, which is determined by factors such as its design specifications, material properties, and processing technology. The qualified depth evaluation can be based on specific evaluation criteria, such as the maximum allowable value of the deviation, to determine whether the load capacity of each screw is qualified. The qualified depth of the rated load capacity refers to the degree to which the performance of the guide screw meets the design requirements under the rated load, which is determined based on the difference between the actual test performance index and the design specification requirements. Obtain multiple qualified depth coefficients of the rated load capacity. The qualified depth coefficient is a quantitative representation of the qualified depth of the rated load capacity, usually a value between 0 and 1. The closer the qualified depth coefficient is to 1, the closer the rated load capacity of the test sample is to the design requirements, and the better the performance. Perform statistical analysis on the multiple qualified depth coefficients of the rated load capacity and calculate their central value, such as the average value, median, or other statistics. The average value can provide an overall performance trend, while the median can better reflect the intermediate performance level, especially when the data distribution is uneven. Use the calculated central value of the qualified depth coefficient as the qualified coefficient of the rated load capacity to reflect the qualified degree of the performance of the guide screw under the rated load. Through the rated load test, the performance of the guide screw under the expected rated load can be comprehensively evaluated.

[0052] Furthermore, step six of the present application includes:

[0053] Construct Q lead screw wear performance test scenarios, where Q is a positive integer greater than 1; perform complexity identification based on the Q lead screw wear performance test scenarios to obtain a test scenario complexity identification result; based on the total number of guide screws in the third guide screw group, combine the test scenario complexity identification result to perform test sample allocation on the Q lead screw wear performance test scenarios to obtain Q allocated guide screw sample sets; perform wear test evaluation on the Q allocated guide screw sample sets based on the Q lead screw wear performance test scenarios to obtain Q scenario wear performance coefficients; add the Q lead screw wear performance test scenarios and the Q scenario wear performance coefficients to the wear performance test results.

[0054] Specifically, select Q representative wear performance test scenarios that cover various wear conditions that the guide screw may encounter in actual use. Each test scenario may include different parameters such as load, speed, temperature, humidity, etc. to simulate different usage environments. According to the analysis results, perform complexity identification on each test scenario. Complexity identification is an important technique in the guide screw wear performance test, used to evaluate the difficulty and complexity of the test scenario. It can be based on the characteristics and conditions of the test scenario, or on the operation difficulty and risk during the test process, such as the working environment, load conditions, movement speed, etc. These factors will affect the wear degree of the guide screw. For example, high load, high speed, or harsh working environment will increase the complexity and severity of wear. Through complexity identification, the complexity level of each test scenario, as well as the required test equipment and operator skill level, can be determined.

[0055] Determine the total number of guideway ball screws for testing. According to the recognition results of the test scenario complexity, allocate test samples for Q guideway ball screw wear performance test scenarios. High-complexity test scenarios may require more test samples to ensure the reliability and accuracy of the results, while low-complexity test scenarios may require fewer samples. Conduct wear tests on the Q allocated guideway ball screw sample sets according to the Q guideway ball screw wear performance test scenarios. Apply loads and motion conditions simulating actual applications to each sample and record its wear situation. These wear situations can be evaluated by measuring indicators such as the wear degree, wear rate, and wear mode of the guideway ball screw. Compare the wear performance of the guideway ball screws under different test scenarios to determine their durability and wear performance under different working conditions. Through analysis, the advantages and disadvantages of the durability and wear performance of the guideway ball screws in certain application scenarios, as well as possible problems, can be found. According to the evaluation results, obtain Q scenario wear performance coefficients, which reflect the wear performance of the guideway ball screws under different test scenarios. Combine the Q guideway ball screw wear performance test scenarios and the corresponding Q scenario wear performance coefficients to form a complete wear performance test result set. By constructing multiple test scenarios simulating actual applications, the wear performance of the guideway ball screws under different working conditions can be comprehensively evaluated.

[0056] Furthermore, the present application further includes the following steps:

[0057] Load the guideway ball screw application scenario record set; perform trigger frequency statistics according to the guideway ball screw application scenario record set to obtain multiple application scenario trigger coefficients; sort the guideway ball screw application scenario record set in descending order according to the multiple application scenario trigger coefficients to generate a guideway ball screw application scenario sequence set; establish the Q guideway ball screw wear performance test scenarios according to the guideway ball screw application scenario sequence set.

[0058] Specifically, collect the performance data of the guideway ball screws in different application scenarios, which can be obtained through on-site tests, simulation experiments, historical records, or user feedback, etc. Each application scenario includes key parameters such as the working environment, load conditions, and motion speed of the guideway ball screw. Organize and classify the collected data, and divide the data into different categories or subsets according to different application scenarios. For example, the data can be divided into different categories such as heavy-load applications, high-speed applications, and frequent start-stop applications. Perform trigger frequency statistics on the data under each application scenario. The trigger frequency refers to the number of times or the time ratio of the guideway ball screw used in a specific application scenario. Through statistical analysis, the trigger frequency data of each application scenario can be obtained. Calculate the trigger coefficient for each application scenario according to the trigger frequency statistics results, and this coefficient reflects the usage frequency of the guideway ball screw in this scenario.

[0059] According to the calculated trigger coefficients, the application scenario record set is sorted in descending order to generate a guide rail screw application scenario sequence set. This sequence set is arranged from high to low according to the trigger frequencies of the application scenarios, reflecting the priorities of the guide rail screws in different application scenarios. The sorted application scenario sequence set reflects the importance or frequency of different application scenarios, where the ones ranked in the front are the most common or important application scenarios. According to the guide rail screw application scenario sequence set, Q of the most important application scenarios are selected as the wear performance test scenarios. Each test scenario should include key parameters such as the working environment, load conditions, and movement speed of the guide rail screw, as well as the contact mode simulated in actual applications. The trigger frequency statistics and the calculation of the application scenario trigger coefficients help identify which scenarios have the greatest impact on screw wear, can better simulate the wear situation of the screw in actual use, and improve the accuracy of the test.

[0060] In summary, the performance test method for a high-precision guide rail screw provided by this application has the following technical effects:

[0061] By receiving a guide rail screw performance test task, where the guide rail screw performance test task includes multiple guide rail screws with the same production process information; obtaining a first test sample division condition; randomly dividing the multiple guide rail screws according to the first test sample division condition to obtain a first guide rail screw group, a second guide rail screw group, and a third guide rail screw group; performing a multi-level static stiffness test according to the first guide rail screw group to obtain a static stiffness test result; performing a load capacity test according to the second guide rail screw group to obtain a load capacity test result; performing a wear performance test according to the third guide rail screw group to obtain a wear performance test result; integrating the static stiffness test result, the load capacity test result, and the wear performance test result to generate a guide rail screw performance test report. That is to say, by receiving the test task, randomly dividing the guide rail screws into three groups, respectively performing static stiffness, load capacity, and wear performance tests, and finally integrating the test results to generate a performance test report, the technical effect of improving the performance test accuracy of the guide rail screw is achieved.

[0062] Embodiment 2

[0063] Based on the same inventive concept as the performance test method for a high-precision guide rail screw in the foregoing embodiment, this application also provides a performance test system for a high-precision guide rail screw. Please refer to the appendix Figure 2 , the system includes:

[0064] A receiving test task module 11, which is used to receive a guide rail screw performance test task, where the guide rail screw performance test task includes multiple guide rail screws with the same production process information.

[0065] Determine the partitioning condition module 12, and the determine partitioning condition module 12 is used to obtain the first test sample partitioning condition.

[0066] Random partitioning module 13, and the random partitioning module 13 is used to randomly partition the multiple guide screws according to the first test sample partitioning condition to obtain a first guide screw group, a second guide screw group, and a third guide screw group.

[0067] Static stiffness test module 14, and the static stiffness test module 14 is used to perform multi-level static stiffness tests on the first guide screw group to obtain static stiffness test results.

[0068] Load capacity test module 15, and the load capacity test module 15 is used to perform load capacity tests on the second guide screw group to obtain load capacity test results.

[0069] Wear performance test module 16, and the wear performance test module 16 is used to perform wear performance tests on the third guide screw group to obtain wear performance test results.

[0070] Report generation module 17, and the report generation module 17 is used to integrate the static stiffness test results, the load capacity test results, and the wear performance test results to generate a guide screw performance test report.

[0071] Furthermore, the static stiffness test module 14 in the system is further used for:

[0072] Obtain the second test sample partitioning condition; randomly partition the first guide screw group according to the second test sample partitioning condition to obtain a first guide screw partition and a second guide screw partition; perform multi-level axial stiffness test evaluations on the first guide screw partition to obtain axial stiffness test results; perform multi-level radial stiffness test evaluations on the second guide screw partition to obtain radial stiffness test results; add the axial stiffness test results and the radial stiffness test results to the static stiffness test results.

[0073] Furthermore, the static stiffness test module 14 in the system is further used for:

[0074] Predict the axial load constraint interval of the guide screw according to the production process information; set the axial load test samples according to the axial load constraint interval of the guide screw to obtain the K-level axial load test samples, where K is a positive integer greater than 1; perform axial stiffness tests on the first partition of the guide screw based on the K-level axial load test samples to obtain multiple guide screw deformation monitoring data sets; activate the axial stiffness evaluation model, and combine the K-level axial load test samples and the multiple guide screw deformation monitoring data sets to perform axial stiffness evaluation to obtain multiple screw axial stiffness index sets, where each screw axial stiffness index set includes K screw axial stiffness indices; calculate the median value of the same-level load stiffness evaluation set according to the multiple screw axial stiffness index sets to obtain the K-level load axial stiffness confidence coefficient; calculate the axial load ratio according to the K-level axial load test samples to obtain the K-level load weight coefficient; perform weighted calculation on the K-level load axial stiffness confidence coefficient according to the K-level load weight coefficient to generate the axial stiffness test result.

[0075] Further, the load capacity test module 15 in the system is further configured to:

[0076] Predict the load characteristics of the guide screw according to the production process information, and determine the expected rated load and the expected ultimate load of the screw; obtain the third test sample division condition; randomly divide the second guide screw group according to the third test sample division condition to obtain the third partition and the fourth partition of the guide screw; perform rated load capacity test analysis on the third partition of the guide screw based on the expected rated load of the screw to determine the rated load capacity qualification coefficient; perform ultimate load capacity test analysis on the fourth partition of the guide screw based on the expected ultimate load of the screw to determine the ultimate load capacity qualification coefficient; add the rated load capacity qualification coefficient and the ultimate load capacity qualification coefficient to the load capacity test result.

[0077] Further, the load capacity test module 15 in the system is further configured to:

[0078] Perform a rated load test on the third partition of the guide screw to obtain multiple screw rated load test data; perform deviation analysis on the multiple screw rated load test data respectively based on the expected rated load of the screw to obtain multiple rated load deviation vectors; perform a qualified depth evaluation of the rated load capacity according to the multiple rated load deviation vectors to obtain multiple rated load capacity qualified depth coefficients; calculate the median value of the multiple rated load capacity qualified depth coefficients to generate the rated load capacity qualification coefficient.

[0079] Further, the wear performance test module 16 in the system is further configured to:

[0080] Construct Q lead screw wear performance test scenarios, where Q is a positive integer greater than 1; identify the complexity based on the Q lead screw wear performance test scenarios to obtain a test scenario complexity identification result; based on the total number of guide screws in the third guide screw group, combine the test scenario complexity identification result to allocate test samples for the Q lead screw wear performance test scenarios to obtain Q allocated guide screw sample sets; evaluate the wear of the Q allocated guide screw sample sets based on the Q lead screw wear performance test scenarios to obtain Q scenario wear performance coefficients; add the Q lead screw wear performance test scenarios and the Q scenario wear performance coefficients to the wear performance test results.

[0081] Further, the wear performance test module 16 in the system is further configured to:

[0082] Load a record set of guide screw application scenarios; count the trigger frequencies according to the record set of guide screw application scenarios to obtain multiple application scenario trigger coefficients; sort the record set of guide screw application scenarios in descending order according to the multiple application scenario trigger coefficients to generate a sequence set of guide screw application scenarios; establish the Q lead screw wear performance test scenarios according to the sequence set of guide screw application scenarios.

[0083] The various embodiments in this specification are described in a progressive manner, and the key point of each embodiment is the difference from other embodiments. The Figure 1 A performance test method and specific example of a high-precision guide screw in the first embodiment are equally applicable to the performance test system of a high-precision guide screw in this embodiment. Through the detailed description of the performance test method of a high-precision guide screw above, those skilled in the art can clearly know the performance test system of a high-precision guide screw in this embodiment. Therefore, for the sake of simplicity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0084] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0085] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of this application and its equivalent technologies, this application is also intended to cover these changes and modifications.

Claims

1. A performance testing method for a high-precision guide rail screw, characterized in that: The method comprises: Receiving a guide rail and lead screw performance test task, wherein the guide rail and lead screw performance test task includes a plurality of guide rails and lead screws having the same production process information; Obtaining a first test sample partitioning condition; Randomly divide the plurality of guide rails and lead screws according to the first test sample division condition to obtain a first guide rail and lead screw group, a second guide rail and lead screw group, and a third guide rail and lead screw group; Performing a multi-stage static stiffness test on the first guide rail and screw assembly to obtain a static stiffness test result; Perform a load capacity test on the second guide rail and lead screw assembly to obtain a load capacity test result; Perform a wear performance test on the third guide rail and lead screw assembly to obtain a wear performance test result; The static stiffness test results, the load capacity test results and the wear performance test results are integrated to generate a guide rail and screw performance test report.

2. A performance testing method for a high-precision guide rail screw as claimed in claim 1, characterized in that: Performing a multi-stage static stiffness test on the first guide rail and screw assembly to obtain a static stiffness test result includes: Obtaining a second test sample division condition; Randomly divide the first guide rail and screw group according to the second test sample division condition to obtain a first guide rail and screw partition and a second guide rail and screw partition; Perform a multi-stage axial stiffness test and evaluation on the first partition of the guide rail and screw to obtain an axial stiffness test result; Perform a multi-stage radial stiffness test and evaluation on the second partition of the guide rail and screw to obtain a radial stiffness test result; The axial stiffness test result and the radial stiffness test result are added to the static stiffness test result.

3. A performance testing method for a high-precision guide rail screw as claimed in claim 2, characterized in that: A multi-stage axial stiffness test evaluation is performed on the first partition of the guide rail and screw to obtain axial stiffness test results, including: Predicting the axial load constraint range of the guide rail and screw according to the production process information; An axial load test sample is set according to the guide rail screw axial load constraint interval to obtain a K-level axial load test sample, wherein K is a positive integer greater than 1; Based on the K-level axial load test sample, an axial stiffness test is performed on the first partition of the guide rail and screw to obtain a plurality of guide rail and screw deformation monitoring data sets; Activate the axial stiffness evaluation model, perform axial stiffness evaluation in combination with the K-level axial load test sample and the plurality of guide rail screw deformation monitoring data sets, and obtain a plurality of screw axial stiffness index sets, wherein each screw axial stiffness index set includes K screw axial stiffness indexes; Calculating the concentrated value of the stiffness evaluation under the same load level according to the multiple sets of axial stiffness indexes of the screws to obtain the confidence coefficient of the axial stiffness under the K-level load, wherein calculating the concentrated value of the stiffness evaluation under the same load level according to the multiple sets of axial stiffness indexes of the screws comprises: for each load level, aggregating all the axial stiffness indexes of the screws, that is, grouping the stiffness indexes from different guide screws according to the load level, so as to compare the performance under the same level, and calculating the concentrated value of the stiffness evaluation under each load level, which is achieved by calculating the average value or the median, wherein the average value can provide an overall performance trend, and the median can better reflect the intermediate performance level; Calculate the axial load ratio according to the K-level axial load test sample to obtain the K-level load weight coefficient; The K-level load axial stiffness confidence coefficient is weightedly calculated according to the K-level load weight coefficient to generate the axial stiffness test result.

4. A performance testing method for a high-precision guide rail screw as claimed in claim 1, characterized in that: Performing a load capacity test on the second guide rail and screw assembly to obtain a load capacity test result includes: Predicting the guide rail and lead screw load characteristics based on the production process information to determine the expected rated load and the expected limit load of the lead screw; Obtaining a third test sample division condition; Randomly divide the second guide rail and screw group according to the third test sample division condition to obtain a third guide rail and screw division and a fourth guide rail and screw division; Based on the expected rated load of the screw, a rated load capacity test analysis is performed on the third partition of the guide rail screw to determine a qualified coefficient of the rated load capacity; Based on the expected limit load of the screw, the fourth partition of the guide rail screw is tested and analyzed to determine the limit load capacity qualification coefficient; The rated load capacity qualification factor and the ultimate load capacity qualification factor are added to the load capacity test result.

5. A performance testing method for a high-precision guide rail screw as claimed in claim 4, characterized in that: Based on the expected rated load of the screw, the rated load capacity test analysis is performed on the third partition of the guide rail screw to determine the qualified coefficient of the rated load capacity, including: Perform a rated load test on the third partition of the guide rail and lead screw to obtain a plurality of lead screw rated load test data; Based on the expected rated load of the screw, respectively performing deviation analysis on the plurality of screw rated load test data to obtain a plurality of rated load deviation vectors; Performing a rated load capacity qualified depth evaluation according to the multiple rated load deviation vectors to obtain multiple rated load capacity qualified depth coefficients; Calculate the concentrated value of the multiple rated load capacity qualified depth coefficients to generate the rated load capacity qualified coefficient. The calculation of the concentrated value of the multiple rated load capacity qualified depth coefficients includes: obtaining multiple rated load capacity qualified depth coefficients, the qualified depth coefficient is a quantitative representation of the rated load capacity qualified depth, and is a value between 0 and 1; perform statistical analysis on the multiple rated load capacity qualified depth coefficients and calculate their concentrated value, which is achieved by calculating the average value or median. The average value can provide an overall performance trend, and the median can better reflect the intermediate performance level.

6. A performance testing method for a high-precision guide rail screw as claimed in claim 1, characterized in that: A wear performance test is performed according to the third guide rail and lead screw assembly to obtain a wear performance test result, including: Construct Q screw wear performance test scenarios, where Q is a positive integer greater than 1; Performing complexity identification according to the Q screw wear performance test scenarios to obtain a test scenario complexity identification result; Based on the total number of guide rails and screws of the third guide rail and screw group, test samples are allocated to the Q screw wear performance test scenarios in combination with the test scenario complexity identification result to obtain Q allocated guide rail and screw sample sets; Perform wear test evaluation on the Q allocated guide rail screw sample sets based on the Q screw wear performance test scenarios to obtain Q scenario wear performance coefficients; The Q screw wear performance test scenarios and the Q scenario wear performance coefficients are added to the wear performance test results.

7. A performance testing method for a high-precision guide rail screw as claimed in claim 6, characterized in that: Construct Q screw wear performance test scenarios, including: Load the guide rail and screw application scenario record set; Perform trigger frequency statistics according to the guide rail and lead screw application scenario record set to obtain multiple application scenario trigger coefficients; Arrange the guide rail and screw application scenario record sets in descending order according to the multiple application scenario trigger coefficients to generate a guide rail and screw application scenario sequence set; According to the guide rail and screw application scenario sequence set, the Q screw wear performance test scenarios are established.

8. A high-precision guide rail and screw performance testing system, characterized in that: Steps for implementing a performance testing method for a high-precision guide rail screw as described in any one of claims 1 to 7, the system comprising: A test task receiving module, wherein the test task receiving module is used to receive a guide rail and screw performance test task, wherein the guide rail and screw performance test task includes a plurality of guide rails and screws having the same production process information; A partitioning condition determination module, wherein the partitioning condition determination module is used to obtain a first test sample partitioning condition; A random division module, the random division module is used to randomly divide the plurality of guide rails and screws according to the first test sample division condition to obtain a first guide rail and screw group, a second guide rail and screw group, and a third guide rail and screw group; A static stiffness test module, the static stiffness test module is used to perform a multi-stage static stiffness test on the first guide rail and lead screw assembly to obtain a static stiffness test result; A load capacity testing module, the load capacity testing module is used to perform a load capacity test according to the second guide rail and lead screw assembly to obtain a load capacity test result; A wear performance testing module, wherein the wear performance testing module is used to perform a wear performance test according to the third guide rail screw assembly to obtain a wear performance test result; A report generation module, wherein the report generation module is used to integrate the static stiffness test results, the load capacity test results and the wear performance test results to generate a guide rail and screw performance test report.

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