Testing method, system and equipment of multi-axis integrated servo driver and medium

Abstract

The invention relates to the technical field of driver testing, in particular to a testing method, system and device of a multi-axis integrated servo driver and a medium. The method comprises the following steps: firstly, synchronously collecting communication information such as an EtherCAT bus state and a connection state, and operating parameters such as a band-type brake signal, torque feedback and an IO state, and constructing a complete state data chain; then analyzing the collected data in real time to obtain a function test result; carrying out abnormity judgment and alarm triggering based on a test result; finally, the test process is intelligently adjusted according to the alarm information, the accuracy of fault diagnosis is improved through cross analysis of the information, meanwhile, self-adaptive adjustment of the detection process is achieved, and the test efficiency and reliability are remarkably improved.

Description

Technical Field

[0001] This application relates to the technical field of drive testing, and particularly to a testing method, system, device and medium for a multi-axis integrated servo drive. Background Art

[0002] With the continuous improvement of industrial automation level, as the core component of a precision motion control system, the performance detection of servo drives has become increasingly prominent. Especially in the field of multi-axis collaborative control, EtherCAT bus-type servo drives are widely used due to their advantages such as high precision and high synchronization, which poses higher requirements for detection technology.

[0003] Currently, the commonly used servo drive detection methods mainly use automated detection equipment to detect the basic functions of the drive through a preset program. Such equipment usually has a data acquisition module, which can collect the basic operating parameters of the drive and obtain the detection results through simple data analysis.

[0004] However, the existing detection methods lack real-time monitoring and abnormal warning mechanisms, and cannot detect and handle running abnormalities in a timely manner; at the same time, once an abnormality occurs, the test strategy cannot be flexibly adjusted according to the specific situation; this situation needs to be further improved. Summary of the Invention

[0005] In order to solve the problem that the existing detection methods lack real-time monitoring and abnormal warning mechanisms and cannot detect and handle running abnormalities in a timely manner, this application provides a testing method, system, device and medium for a multi-axis integrated servo drive, and adopts the following technical solutions: In a first aspect, this application provides a testing method for a multi-axis integrated servo drive, including the following steps: Obtain the communication status information and operating parameter information of the servo drive, where the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operating parameter information includes the brake signal status, torque feedback value, and IO signal status; According to the communication status information and the operating parameter information, test and analyze the functions of the servo drive to obtain a function test result; According to the function test result, judge whether the working state of the servo drive is abnormal, and if it is abnormal, trigger the corresponding alarm information; Determine the execution status of the test process according to the alarm information, and control the continuous operation or end of the test process.

[0006] By adopting the above technical solution, since there are problems such as inter-axis coupling interference and scattered state information in the multi-axis integrated servo driver under complex working conditions, its reliability detection faces major challenges. For example, in actual applications, when torque fluctuations occur in a certain axis, it may be caused by multiple factors such as communication anomalies, excessive load, or inter-axis interference. Traditional single detection methods are difficult to accurately diagnose the root cause of the fault. This application first synchronously collects communication information such as EtherCAT bus status and connection status, as well as operating parameters such as brake signals, torque feedback, and IO status, to construct a complete state data chain. Then, the collected data is analyzed in real time to obtain the functional test results. Subsequently, based on the test results, abnormal judgment and alarm triggering are performed. Finally, the test process is intelligently adjusted according to the alarm information. By cross-analyzing the information, the accuracy of fault diagnosis is improved, and at the same time, the adaptive adjustment of the detection process is realized, significantly improving the test efficiency and reliability.

[0007] Optionally, according to the communication status information and the operating parameter information, the functions of the servo driver are tested and analyzed to obtain functional test results, which specifically include the following steps: According to the EtherCAT bus status and the connection status of each axis, a communication function test is performed to detect the state machine switching process of the EtherCAT bus and judge the bus operating status of each axis. According to the brake signal status, a brake function test is performed to control each axis to enter the enabled state and open the brake, and the status of each axis is detected through the status word and the brake signal. According to the torque feedback value, a two-way load test is performed, where: The main control PLC controls each axis of the tested driver to run forward, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply a forward load, and collects the actual torque value to judge the forward load state. The main control PLC controls each axis of the tested driver to run backward, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply a reverse load, and collects the actual torque value to judge the reverse load state. The auxiliary PLC adjusts the load size in real time according to the torque feedback value transmitted by the main control PLC. According to the IO signal status, a digital input signal test is performed. The main PLC output port sends test signals to the digital input terminals of the servo driver in a preset order, and the response status of each digital input terminal is read and verified through the object dictionary.

[0008] By adopting the above technical solutions, the present application first has the master PLC detect the basic performance of EtherCAT communication and the brake function. Then, in the load test stage, the master PLC is responsible for the motion control of the drive under test, while the instruction auxiliary PLC provides an accurate load torque through the CAN bus servo system. Finally, the response test of the IO signals is carried out. The entire test process adopts the method of bidirectional load and real-time feedback regulation to ensure the comprehensiveness and accuracy of the test; through the real-time data interaction and collaborative cooperation of the master and auxiliary PLCs, not only the performance evaluation of the multi-axis servo system under real load conditions is realized, but also the test efficiency and reliability are improved, effectively guaranteeing the product quality.

[0009] Optionally, according to the function test result, determine whether the working state of the servo drive is abnormal. If it is abnormal, after triggering the corresponding alarm information, the method further includes the following steps: Obtain the basic operation parameters and load response characteristics of each axis of the servo drive. Among them, the basic operation parameters include the speed command value, position command value, and torque command value of each axis, and the load response characteristics include the actual operation data of each axis under load. According to the basic operation parameters and the corresponding load response characteristics, analyze the performance quality of the servo drive to obtain a performance quality analysis result. Among them, the performance quality analysis result includes speed response characteristic analysis, position accuracy analysis, torque followability analysis, and inter-axis synchronism analysis. According to the performance quality analysis result, perform parameter diagnosis on the servo drive, and conduct directional parameter compensation analysis on the axes with unqualified performance to obtain the corresponding compensation parameters. Adjust the operation parameters of the servo drive according to the compensation parameters, generate and send a correction instruction to the servo drive according to the adjusted operation parameters, so that the servo drive re-executes the test process.

[0010] By adopting the above technical solutions, in order to improve the performance quality of the multi-axis integrated servo drive, it is necessary to perform real-time performance diagnosis and parameter optimization during the test process; the present application first collects the basic operation parameters such as speed, position, and torque of each axis and the load response characteristics, then conducts performance quality analysis from multiple dimensions such as speed response, position accuracy, torque followability, and inter-axis synchronism, and finally performs directional parameter compensation based on the analysis results, and ensures the effectiveness of performance improvement through closed-loop verification; by establishing a performance index quantitative analysis model and an adaptive parameter compensation algorithm, the accurate evaluation and automatic optimization of the drive performance are realized, greatly improving the consistency and reliability of the product performance.

[0011] Optionally, analyze the performance quality of the servo driver according to the basic operating parameters and the corresponding load response characteristics to obtain a performance quality analysis result, which specifically includes the following steps: Calculate the dynamic response parameters of each axis according to the basic operating parameters and the load response characteristics, where the dynamic response parameters include response time, overshoot, and steady-state error; Calculate the performance index scores of each axis under different load conditions according to the dynamic response parameters; Analyze the deviation between the current performance index and the preset standard performance according to the performance index score to obtain the single-axis performance deviation value of the current axis; Estimate the comprehensive performance deviation value of the entire servo driver according to the single-axis performance deviation value, and perform performance quality analysis on the servo driver according to the comprehensive performance deviation value to obtain the performance quality analysis result.

[0012] By adopting the above technical solution, since traditional performance evaluation methods often rely on single indicators or subjective experience judgments and lack systematicness and quantification standards, it is impossible to comprehensively reflect the actual performance level of the driver; in this application, the basic performance characteristics of each axis are first reflected through dynamic response parameters such as response time, overshoot, and steady-state error; then performance index scoring is performed under different load conditions to establish a performance quantification standard; then, through comparative analysis with the preset standard, the single-axis performance deviation value is obtained; finally, through the calculation of the comprehensive performance deviation value, the systematic evaluation of the performance of the whole machine is realized; through the quantitative analysis and comprehensive evaluation of multi-level performance indicators, not only the objectification and standardization of performance evaluation are realized, but also an accurate basis for subsequent parameter optimization is provided, effectively ensuring the consistency and reliability of product performance.

[0013] Optionally, the method further includes: Obtain the performance index difference of adjacent test cycles, and obtain the performance change value and performance decay rate corresponding to the performance index score according to the performance index difference; Construct a performance change trend curve corresponding to the performance index difference according to the performance change value and the performance decay rate; Analyze the performance decay trend of the servo driver according to the performance change trend curve to obtain the performance warning value of the current servo driver; When the actual performance of the servo driver reaches the performance warning value, output maintenance processing information to the control system.

[0014] By adopting the above technical solution, the traditional maintenance method often adopts the mode of fixed-cycle maintenance or post-failure repair, lacking the ability to monitor and predict the changing trend of equipment performance in real time, resulting in the inability to detect potential performance degradation risks in a timely manner; this application first calculates the performance change value and decay rate by comparing the performance index differences of adjacent test cycles; then constructs a performance change trend curve based on these data; then predicts the performance decline trend by analyzing the trend curve and sets an early warning threshold; finally, when the performance reaches the warning value, actively sends out maintenance information; by establishing a performance trend prediction model, it can not only discover potential performance problems in advance, but also optimize the maintenance timing, realize the scientific and precise equipment maintenance, and effectively reduce the equipment failure rate and maintenance cost.

[0015] Optionally, adjusting the operating parameters of the servo drive according to the compensation parameters specifically includes the following steps: Obtain the control parameter correlation degree of mutually coupled axes, where the control parameters include the parameters of the speed loop, position loop, and torque loop; Calculate the parameter coupling influence coefficient between each axis according to the control parameter correlation degree; Based on the parameter coupling influence coefficient, perform collaborative optimization adjustment on the compensation parameters of each axis to generate a compensation parameter group considering the coupling influence between axes; Adjust the control parameters of each axis according to the compensation parameter group, and perform an inter-axis synchronous motion test to verify the compensation effect.

[0016] By adopting the above technical solution, the traditional parameter adjustment method often optimizes each axis as an independent system, ignoring the mutual influence between axes, resulting in problems such as inconsistent performance or mutual interference in actual operation; this application first analyzes the correlation degree between control parameters such as the speed loop, position loop, and torque loop; then calculates the parameter coupling influence coefficient between each axis; then performs collaborative optimization of the compensation parameters based on the coupling influence; finally, verifies the optimization effect through an inter-axis synchronous motion test; not only realizes the overall optimization considering the inter-axis coupling effect, but also improves the accuracy and reliability of parameter adjustment, and effectively improves the overall performance and stability of the system.

[0017] Optionally, based on the parameter coupling influence coefficient, perform collaborative optimization adjustment on the compensation parameters of each axis to generate a compensation parameter group considering the coupling influence between axes, specifically including the following steps: Determine the associated axis group according to the parameter coupling influence coefficient, and analyze the performance complementary characteristics of each axis within the associated axis group; Calculate the parameter compensation ratio of each axis within the associated axis group, and the parameter compensation ratio is used to balance the dynamic response characteristics of each axis; Generate a compensation parameter group considering the coupling influence between axes according to the performance complementary characteristics and the parameter compensation ratio.

[0018] By adopting the above technical solution, traditional parameter optimization methods often adopt a unified compensation strategy, failing to consider the performance differences and complementary effects of each axis, resulting in difficulty in achieving optimal system performance in practical applications. This application first divides associated axis groups according to the parameter coupling influence coefficient and analyzes the performance complementary characteristics of each axis within the group. Then, by calculating the parameter compensation ratio, a balance mechanism for the dynamic response characteristics of each axis is established. Finally, based on the performance complementary characteristics and compensation ratio, a differentiated compensation parameter group is generated. By establishing an inter-axis performance complementary mechanism and a differentiated compensation strategy, the dynamic response matching degree of the system is improved, and the overall coordination and processing accuracy of the system can be effectively enhanced.

[0019] In a second aspect, this application provides a test system for a multi-axis integrated servo driver, including: An information acquisition module, configured to acquire the communication status information and operating parameter information of the servo driver. Among them, the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operating parameter information includes the brake signal status, torque feedback value, and IO signal status; A function test module, configured to perform a test analysis on the functions of the servo driver according to the communication status information and the operating parameter information to obtain a function test result; An abnormal alarm module, configured to determine whether the working state of the servo driver is abnormal according to the function test result, and trigger corresponding alarm information if it is abnormal; An execution status determination module, configured to determine the execution status of the test process according to the alarm information and control the continuous operation or end of the test process.

[0020] In a third aspect, this application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned test method for a multi-axis integrated servo driver are implemented.

[0021] In a fourth aspect, this application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned test method for a multi-axis integrated servo driver are implemented.

[0022] In summary, this application includes at least one of the following beneficial technical effects: 1. The present application first synchronously collects communication information such as EtherCAT bus status and connection status, as well as operating parameters such as brake signals, torque feedback, and IO status, to construct a complete status data chain; then it performs real-time analysis on the collected data to obtain functional test results; then it makes abnormal judgments and triggers alarms based on the test results; finally, it intelligently adjusts the test process according to the alarm information, improving the accuracy of fault diagnosis through cross-analysis of information, and at the same time realizing the adaptive adjustment of the detection process, significantly enhancing the test efficiency and reliability. 2. The present application first detects the basic performance of EtherCAT communication and brake functions by the master PLC. Then, in the load test stage, the master PLC is responsible for the motion control of the drive under test, while the instruction auxiliary PLC provides accurate load torque through the CAN bus servo system. Finally, the response test of the IO signal is carried out. The entire test process adopts the method of two-way load and real-time feedback adjustment to ensure the comprehensiveness and accuracy of the test; through the real-time data interaction and collaborative cooperation of the master and auxiliary PLCs, not only the performance evaluation of the multi-axis servo system under real load conditions is realized, but also the test efficiency and reliability are improved, effectively ensuring the product quality. 3. To improve the performance quality of the multi-axis integrated servo drive, real-time performance diagnosis and parameter optimization need to be carried out during the test process; the present application first collects basic operating parameters such as speed, position, and torque of each axis and load response characteristics, then conducts performance quality analysis from multiple dimensions such as speed response, position accuracy, torque followability, and inter-axis synchronization, and finally performs directional parameter compensation based on the analysis results, and ensures the effectiveness of performance improvement through closed-loop verification; by establishing a quantitative analysis model of performance indicators and an adaptive parameter compensation algorithm, the accurate evaluation and automatic optimization of the drive performance are realized, greatly improving the consistency and reliability of the product performance. Description of the Drawings

[0023] Figure 1 is a schematic flowchart of the test method for the multi-axis integrated servo drive according to the embodiment of the present application; Figure 2 is a schematic flowchart of step S120 in the test method for the multi-axis integrated servo drive according to the embodiment of the present application; Figure 3 is a schematic flowchart of the operating parameter adjustment in the test method for the multi-axis integrated servo drive according to the embodiment of the present application; Figure 4 is a schematic flowchart of step S320 in the test method for the multi-axis integrated servo drive according to the embodiment of the present application; Figure 5 is a schematic flowchart of the performance decay trend analysis in the test method for the multi-axis integrated servo drive according to the embodiment of the present application; Figure 6It is a schematic flowchart of step S340 in the test method of the multi-axis integrated servo driver according to an embodiment of the present application; Figure 7 It is a schematic flowchart of step S630 in the test method of the multi-axis integrated servo driver according to an embodiment of the present application; Figure 8 It is a schematic diagram of the modules of the test system of the multi-axis integrated servo driver according to an embodiment of the present application; Figure 9 It is an internal structure diagram of an electronic device according to an embodiment of the present application. Detailed implementation manners

[0024] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular forms "a", "an", "the", "above-mentioned", "said", and "this" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations including one or more of the listed items.

[0025] Hereinafter, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as implying or suggesting relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "a plurality" is two or more.

[0026] The following further describes the embodiments of the present application in detail with reference to the accompanying drawings of the specification.

[0027] In a first aspect, the present application provides a test method for a multi-axis integrated servo driver. Referring to Figure 1 , the method includes the following steps: S110. Obtain the communication status information and operation parameter information of the servo driver.

[0028] Among them, the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operation parameter information includes the brake signal status, the torque feedback value, and the IO signal status.

[0029] In this embodiment, the system realizes the real-time monitoring of the servo drive status by establishing a communication mapping table between the EtherCAT master station and the slave station. This mapping table includes two types of data channels: PDO (Process Data Object) and SDO (Service Data Object). Among them, PDO is used for periodic data transmission, and SDO is used for non-periodic parameter access. The system pre-configures the object dictionary indexes of the communication parameters and operation parameters of each axis in the master station to establish a basic framework for data acquisition.

[0030] S120. According to the communication status information and operation parameter information, test and analyze the functions of the servo drive to obtain the function test results.

[0031] In this embodiment, the system establishes a complete function test and evaluation model. The model includes test indicators in four dimensions: communication function, brake function, load characteristics, and IO response. Corresponding judgment thresholds and evaluation rules are set for each indicator to quantify the test results. The system realizes the comprehensive test of the drive function by comparing the collected data with the preset standards in real time.

[0032] S130. According to the function test results, judge whether the working state of the servo drive is abnormal. If it is abnormal, trigger the corresponding alarm information.

[0033] In this embodiment, the system constructs a multi-level fault diagnosis model. The model analyzes the function test results based on a preset judgment rule library. The judgment rule library includes three levels: communication abnormality, function abnormality, and performance abnormality. Multiple specific judgment conditions are set under each level. The system realizes the rapid identification and positioning of abnormal states by comparing the test data with the standard thresholds in the rule library in real time.

[0034] Specifically, the system first evaluates the communication quality, including indicators such as frame loss rate and synchronization deviation; then verifies the function test results, including parameters such as brake action timing, torque output range, and IO response time; when an abnormality is detected, the system extracts the corresponding alarm information from the alarm code database according to the type of abnormality. For example, when it is detected that the torque feedback value of a certain axis exceeds 150% of the rated value, the system triggers a torque overload alarm; when it is detected that the IO response times out, an IO abnormality alarm is triggered.

[0035] S140. Determine the execution status of the test process according to the alarm information, and control the continuous operation or end of the test process.

[0036] In this embodiment, the system designs a test process control mechanism to achieve precise control of the test process based on the state machine model. The state machine model defines multiple states such as test start, in execution, pause, continue, and end, and establishes the conversion conditions and processing logics between each state. The system automatically determines the execution state of the process by real-time monitoring the severity of alarm information.

[0037] Specifically, the system classifies alarm information into three levels: prompt information, warning information, and error information. When prompt information appears, the system records the log but continues to execute the test; when warning information appears, the system pauses the current test item and waits for the operator to confirm; when error information appears, the system immediately aborts the test process and saves the test data. For example, when a warning message is triggered due to a detected decrease in communication quality, the test can continue after the operator confirms; while when an error message is triggered due to a detected hardware failure, the system directly terminates the test and generates a failure report.

[0038] In one embodiment, referring to Figure 2 , in step S120, according to the communication status information and operation parameter information, the functions of the servo drive are tested and analyzed to obtain the function test results, which specifically include the following steps: S210. According to the EtherCAT bus status and the connection status of each axis, perform communication function tests, detect the state machine switching process of the EtherCAT bus, and judge the bus operation status of each axis.

[0039] In this embodiment, the system establishes an EtherCAT bus status monitoring model, which includes a state machine switching sequence table and a communication quality evaluation database. The state machine switching sequence table defines the standard switching process and timing requirements from the initialization to the operation stages, and the communication quality evaluation database stores the characteristic data of various abnormal states.

[0040] Specifically, during the communication test stage, the system first checks the connection status between the master station and the slave station and sequentially executes the state machine switching. By reading the status register to monitor the state changes during the switching process, when an abnormality is detected, the system will trigger a communication failure alarm. At the same time, the system will record the status information when the failure occurs for subsequent analysis and optimization.

[0041] S220. According to the brake signal status, perform brake function tests, control each axis to enter the enabled state and open the brake, and detect the status of each axis through the status word and the brake signal.

[0042] In this embodiment, the system constructs a brake control characteristic model, which includes a brake action timing table and a status monitoring rule library. The brake action timing table stipulates the standard timing relationship between the enable signal and the brake signal, and the status monitoring rule library defines the judgment criteria for various abnormal states. The system realizes reliable verification of the brake function through this model.

[0043] Specifically, the system controls each axis to enter the enabled state and open the brake in sequence according to the preset control timing. The execution process is monitored by reading the status word and the brake feedback signal. When an abnormal state is detected, the system will trigger a brake fault alarm. The status information of each test will be recorded in the characteristic database for quality tracking.

[0044] S230. Perform a two-way load test according to the torque feedback value.

[0045] Among them, step S230 includes: The main control PLC controls each axis of the drive under test to run forward, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply a forward load, and collects the actual torque value to judge the forward load state; The main control PLC controls each axis of the drive under test to run backward, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply a reverse load, and collects the actual torque value to judge the reverse load state; The auxiliary PLC adjusts the load size in real time according to the torque feedback value transmitted by the main control PLC.

[0046] In this embodiment, the system establishes a load test parameter mapping table and a torque response criterion database. The parameter mapping table defines the data exchange area between the master and slave PLCs, which is used to realize the coordinated control of the main control PLC and the auxiliary PLC. The torque response criterion database stores the torque limit values and response characteristic requirements under different working conditions. The system evaluates the load capacity of the drive by comparing the actual torque feedback value with the standard value in the criterion database.

[0047] Specifically, the system first controls each axis of the drive under test to run forward by the main control PLC, and at the same time controls the auxiliary PLC to control the CAN bus servo system to output a forward load through the data exchange area instruction. The main control PLC obtains the actual torque value by reading the object dictionary and compares it with the standard value in the torque response criterion database. When an abnormal torque feedback is detected, the system triggers an alarm for excessive torque feedback. Subsequently, the system performs a reverse load test in the same manner, controls the load motor to output a reverse torque through the auxiliary PLC, and makes corresponding state judgments. During the whole test process, the auxiliary PLC dynamically adjusts the load size according to the real-time torque feedback value transmitted by the main control PLC to ensure the smooth and controllable test process.

[0048] Furthermore, the system is configured with a human-machine interface for realizing human-machine interaction and controlling the system. During the load test, the human-machine interface real-time displays the torque feedback values and operating status of each axis. When abnormal situations such as excessive torque feedback occur, it can clearly display alarm information, enabling the operator to promptly understand the abnormal situation of the system. At the same time, the interface can also accurately display the test progress and results, providing intuitive test status feedback to the user. The system is configured with a counter-rotating platform, providing a mechanical connection basis for motor counter-rotation, and can firmly fix the motor controlled by the tested driver and the auxiliary load motor, ensuring the stable operation of the motor during the test and guaranteeing the accuracy of the test results.

[0049] S240. According to the IO signal status, perform digital input signal testing. Send test signals to the digital input terminals of the servo driver from the main PLC output port in a preset order, and read and verify the response status of each digital input terminal through the object dictionary.

[0050] In this embodiment, the system establishes an IO signal test model, including a signal test sequence generator and a response characteristic evaluator. The sequence generator can generate a standard test signal sequence according to preset rules, and the response characteristic evaluator is responsible for analyzing the timing characteristics and stability of the input signals.

[0051] Specifically, the system sends test signals to each input terminal according to the preset test sequence. Obtain the input status by reading the object dictionary, and compare and analyze the response characteristics of the signals. When an abnormal response is detected, the system will record relevant information and trigger an alarm prompt. The test data is saved in the response characteristic database for continuous improvement.

[0052] In one embodiment, referring to Figure 3 , according to the functional test results, determine whether the operating status of the servo driver is abnormal. If it is abnormal, after triggering the corresponding alarm information, the method further includes the following steps: S310. Obtain the basic operating parameters and load response characteristics of each axis of the servo driver.

[0053] Among them, the basic operating parameters include the speed command value, position command value, and torque command value of each axis, and the load response characteristics include the actual operating data of each axis under load.

[0054] In this embodiment, the system establishes a basic sampling period rule, such as recording data every 100 ms, and records the basic operating parameters and load response data.

[0055] Specifically, directly read the command values and actual values of speed, position, and torque from the driver object dictionary. At the same time, record the actual operating data under load conditions to form a basic timing data table. Perform simple mean filtering on the collected data to remove obvious outliers.

[0056] S320. Analyze the performance quality of the servo drive based on the basic operating parameters and the corresponding load response characteristics to obtain the performance quality analysis result.

[0057] Among them, the performance quality analysis result includes speed response characteristic analysis, position accuracy analysis, torque followability analysis, and inter-axis synchronism analysis.

[0058] In this embodiment, the system constructs a performance index evaluation matrix and a quality characteristic analyzer. The evaluation matrix defines the evaluation criteria for various indicators such as speed, position, torque, and synchronism, and the quality characteristic analyzer is responsible for performing multi-dimensional analysis on the collected data.

[0059] Specifically, the system inputs the collected operating data into the evaluation model to perform speed response characteristic, position accuracy, torque followability, and inter-axis synchronism analysis respectively. For speed response characteristics, mainly look at the percentage of following error; for position accuracy, focus on the maximum error value; for torque followability, check the overshoot; for inter-axis synchronism, compare the phase difference. By comparing with the preset standards, generate the evaluation results of various performance indicators, and generate a performance evaluation report according to the compliance of each indicator.

[0060] S330. According to the performance quality analysis result, perform parameter diagnosis on the servo drive, and perform directional parameter compensation analysis on the axes with unqualified performance to obtain the corresponding compensation parameters.

[0061] In this embodiment, the system pre-establishes a fault-symptom comparison table to record common performance problems and their corresponding possible causes and solutions.

[0062] Specifically, according to the performance evaluation result, look up the comparison table to determine the type of parameters that need to be adjusted. Use the preset compensation rules to calculate the parameter adjustment amount, such as "when the position overshoot is greater than 10%, reduce the position loop gain by 20%", etc.

[0063] S340. Adjust the operating parameters of the servo drive according to the compensation parameters, generate and send a correction instruction to the servo drive according to the adjusted operating parameters, so that the servo drive re-executes the test process.

[0064] In this embodiment, the system pre-establishes a parameter modification safety check list to ensure that the parameter adjustment is within a reasonable range.

[0065] Specifically, the system directly modifies the relevant parameters of the drive according to the calculated compensation value. Write the new parameters into the drive through the standard communication instruction and start the test program to verify the adjustment effect. If the effect is not ideal, perform fine-tuning according to the preset step size.

[0066] In one embodiment, refer to Figure 4, in step S320, according to the basic operating parameters and the corresponding load response characteristics, analyze the performance quality of the servo drive to obtain the performance quality analysis result, which specifically includes the following steps: S410. Calculate the dynamic response parameters of each axis according to the basic operating parameters and the load response characteristics.

[0067] Among them, the dynamic response parameters include response time, overshoot, and steady-state error.

[0068] In this embodiment, the system records the operating data of each axis under standard test conditions.

[0069] Specifically, the system calculates dynamic response parameters such as response time, overshoot, and steady-state error by comparing the time series data of the command value and the actual response value.

[0070] S420. Calculate the performance index scores of each axis under different load conditions according to the dynamic response parameters.

[0071] In this embodiment, the system designs a multi-dimensional scoring model and a load condition mapping table. The scoring model includes the weight coefficients and score calculation rules of each performance index, and the load condition mapping table defines the scoring criteria under different load conditions.

[0072] Specifically, the system calculates the single scores of each performance index according to the dynamic response parameters and in combination with the current load condition. Through the weighted calculation of the scoring model, the comprehensive performance scores of each axis under different load conditions are obtained.

[0073] S430. Analyze the deviation between the current performance index and the preset standard performance according to the performance index score to obtain the single-axis performance deviation value of the current axis.

[0074] In this embodiment, the system constructs a performance deviation analysis model and a standard performance feature library. The deviation analysis model includes deviation calculation methods and tolerance range definitions, and the standard performance feature library stores the preset standard values of performance indicators.

[0075] Specifically, the system compares the actual performance index score with the reference value in the standard performance feature library to calculate the performance deviation value. Through the processing of the deviation analysis model, the single-axis performance deviation characteristics of each axis are obtained.

[0076] S440. Estimate the comprehensive performance deviation value of the entire servo drive according to the single-axis performance deviation value, and perform performance quality analysis on the servo drive according to the comprehensive performance deviation value to obtain the performance quality analysis result.

[0077] In this embodiment, the system establishes a comprehensive evaluation model and a performance quality criterion database. The comprehensive evaluation model includes multi-axis coupling influence factors and a comprehensive performance calculation method, and the performance quality criterion database defines performance quality standards at different levels.

[0078] Specifically, based on the single-axis performance deviation values of each axis, the system calculates the comprehensive performance deviation value of the entire driver through the comprehensive evaluation model. By matching the deviation value with the standards in the performance quality criterion database, the final performance quality analysis result is generated.

[0079] In one embodiment, referring to Figure 5 , the method further includes: S510. Obtain the difference in performance indicators between adjacent test cycles, and obtain the performance change value and performance decay rate corresponding to the performance indicator score according to the difference in performance indicators.

[0080] In this embodiment, the system establishes a performance tracking database for recording performance indicator data of consecutive test cycles to achieve quantitative analysis of performance differences. By comparing the performance indicators of adjacent test cycles, the performance indicator difference and performance decay rate are calculated as the basic data for trend analysis.

[0081] S520. Construct a performance change trend curve corresponding to the performance indicator difference according to the performance change value and performance decay rate.

[0082] In this embodiment, the system uses the performance change value and decay rate to perform data fitting through a modeling engine to generate a characteristic curve reflecting performance changes.

[0083] S530. Analyze the performance decay trend of the servo driver according to the performance change trend curve to obtain the performance warning value of the current servo driver.

[0084] In this embodiment, the system presets a set of warning thresholds based on experience, including the warning lines for the performance decline amplitude and rate.

[0085] Specifically, perform simple extrapolation calculations according to the trend curve to predict the performance state in the next time period. When the predicted value approaches or exceeds the warning threshold, determine the current performance warning value.

[0086] S540. When the actual performance of the servo driver reaches the performance warning value, output maintenance processing information to the control system.

[0087] In this embodiment, the system pre-establishes basic maintenance prompt rules. When the actual performance reaches the warning value, the system automatically generates maintenance suggestions in a standard format.

[0088] Specifically, the system compares the current performance state with the warning value. When the warning condition is met, a prompt message containing information such as the type of performance anomaly and recommended maintenance measures is sent to the control system.

[0089] In one embodiment, referring to Figure 6 , in step S340, the operating parameters of the servo drive are adjusted according to the compensation parameters, which specifically include the following steps: S610. Obtain the correlation degree of the control parameters of the mutually coupled axes.

[0090] Among them, the control parameters include the parameters of the speed loop, position loop, and torque loop.

[0091] In this embodiment, the system pre-establishes a three-loop parameter correspondence table, which records the basic parameter combinations of the speed loop, position loop, and torque loop.

[0092] Specifically, by recording the changes in the three-loop parameters of each axis during operation under standard working conditions and using the correlation coefficient calculation method, the basic correlation relationship between the parameters is obtained. For example, when the speed loop gain changes, record the change amplitudes of the position loop and torque loop parameters.

[0093] S620. Calculate the parameter coupling influence coefficients between the axes according to the correlation degree of the control parameters.

[0094] In this embodiment, when the parameter change of one axis causes other axes to exceed the preset change amount, the corresponding influence coefficient is recorded.

[0095] Specifically, the system calculates the coupling influence coefficients of the parameters between the axes based on the control parameter correlation matrix and combines the physical coupling characteristics of each axis.

[0096] S630. Based on the parameter coupling influence coefficients, perform collaborative optimization adjustment on the compensation parameters of each axis to generate a compensation parameter group considering the coupling influence between the axes.

[0097] In this embodiment, an incremental adjustment method is adopted. First, the parameters of the main influencing axis are adjusted, and then the associated axes are compensated accordingly according to the actual operation effect.

[0098] Specifically, according to the magnitudes of the coupling influence coefficients, the parameters of each axis are gradually modified according to the preset adjustment step size. Observe the system response after each adjustment until a better operation effect is achieved.

[0099] S640. Adjust the control parameters of each axis according to the compensation parameter group and perform an inter-axis synchronous motion test to verify the compensation effect.

[0100] Specifically, the system uses the optimized compensation parameter group to adjust the parameters of the servo drive and starts the inter-axis synchronous motion test program. By analyzing the position error, speed error, and phase error during the synchronous motion, the effectiveness of the compensation effect is evaluated.

[0101] In one embodiment, referring to Figure 7 , in step S630, based on the parameter coupling influence coefficient, the compensation parameters of each axis are collaboratively optimized and adjusted to generate a compensation parameter group considering the inter-axis coupling influence, which specifically includes the following steps: S710. Determine the associated axis group according to the parameter coupling influence coefficient and analyze the performance complementary characteristics of each axis within the associated axis group.

[0102] In this embodiment, the system has pre-established a simple coupling coefficient threshold table. The coupling coefficient threshold table sets a reference value for judging the strength of the inter-axis coupling relationship based on actual operation experience.

[0103] Specifically, when the coupling influence coefficient between two axes exceeds the preset threshold, they are classified into the same associated axis group. At the same time, by comparing the basic parameters of each axis (such as response time, stiffness coefficient, etc.), the performance complementary relationship within the axis group is determined.

[0104] S720. Calculate the parameter compensation ratio of each axis within the associated axis group, and the parameter compensation ratio is used to balance the dynamic response characteristics of each axis.

[0105] In this embodiment, the system sets a group of benchmark compensation ratios based on empirical data for quickly adjusting the parameters of each axis.

[0106] Specifically, the system compares the current dynamic response parameters of each axis (such as overshoot, response time) with the preset target value and calculates the required compensation ratio according to the linear proportional relationship to achieve the initial balance of the performance within the axis group.

[0107] S730. Generate a compensation parameter group considering the inter-axis coupling influence according to the performance complementary characteristics and the parameter compensation ratio.

[0108] In this embodiment, the system uses the look-up table method and interpolation calculation. A set of basic compensation parameter tables has been formulated in advance, which contains reference parameter values under common working conditions.

[0109] Specifically, the system searches for the closest reference parameter according to the current working condition, makes a simple adjustment in combination with the calculated compensation ratio, and obtains a compensation parameter group suitable for the current situation. When necessary, a small-range trial adjustment is carried out to ensure the applicability of the parameters.

[0110] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0111] In a second aspect, the present application provides a test system for a multi-axis integrated servo driver. The test system for the multi-axis integrated servo driver of the present application will be described below in combination with the above test method for the multi-axis integrated servo driver.

[0112] Referring to Figure 8 , a test system for a multi-axis integrated servo driver includes: An information acquisition module, configured to acquire the communication status information and operation parameter information of the servo driver, where the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operation parameter information includes the brake signal status, the torque feedback value, and the IO signal status; A function test module, configured to perform a test analysis on the functions of the servo driver according to the communication status information and the operation parameter information, and obtain a function test result; An abnormal alarm module, configured to determine whether the working state of the servo driver is abnormal according to the function test result, and trigger corresponding alarm information if it is abnormal; An execution status determination module, configured to determine the execution status of the test process according to the alarm information, and control the continuous operation or end of the test process.

[0113] In one embodiment, the function test module includes: A communication test unit, configured to perform a communication function test according to the EtherCAT bus status and the connection status of each axis, detect the state machine switching process of the EtherCAT bus, and judge the bus operation status of each axis; A brake test unit, configured to perform a brake function test according to the brake signal status, control each axis to enter the enabled state and open the brake, and detect the status of each axis through the status word and the brake signal; A load test unit, configured to perform a two-way load test according to the torque feedback value, including: Controlling each axis of the tested driver to run forward, and at the same time controlling the auxiliary PLC to drive the CAN bus servo system to apply a forward load, and collecting the actual torque value to judge the forward load state; Controlling each axis of the tested driver to run in reverse, and at the same time controlling the auxiliary PLC to drive the CAN bus servo system to apply a reverse load, and collecting the actual torque value to judge the reverse load state; Adjusting the load size in real time according to the torque feedback value transmitted by the main control PLC; The IO test unit is used to perform digital input signal tests according to the IO signal status, send test signals to the digital input terminals of the servo drive through the main PLC output port in a preset order, and read and verify the response status of each digital input terminal through the object dictionary.

[0114] In one embodiment, it further includes: The parameter acquisition module is used to acquire the basic operation parameters and load response characteristics of each axis of the servo drive. Among them, the basic operation parameters include the speed command value, position command value, and torque command value of each axis, and the load response characteristics include the actual operation data of each axis under load; The performance analysis module is used to analyze the performance quality of the servo drive according to the basic operation parameters and the corresponding load response characteristics, and obtain the performance quality analysis result. Among them, the performance quality analysis result includes speed response characteristic analysis, position accuracy analysis, torque followability analysis, and inter-axis synchronism analysis; The parameter diagnosis module is used to perform parameter diagnosis on the servo drive according to the performance quality analysis result, and perform directional parameter compensation analysis on the axes with unqualified performance to obtain the corresponding compensation parameters; The parameter adjustment module is used to adjust the operation parameters of the servo drive according to the compensation parameters, generate and send a correction command to the servo drive according to the adjusted operation parameters, so that the servo drive re-executes the test process.

[0115] In one embodiment, the performance analysis module includes: The dynamic response calculation unit is used to calculate the dynamic response parameters of each axis according to the basic operation parameters and the load response characteristics. Among them, the dynamic response parameters include response time, overshoot, and steady-state error; The performance score calculation unit is used to calculate the performance index scores of each axis under different load conditions according to the dynamic response parameters; The deviation analysis unit is used to analyze the deviation between the current performance index and the preset standard performance according to the performance index score, and obtain the single-axis performance deviation value of the current axis; The comprehensive evaluation unit is used to estimate the comprehensive performance deviation value of the entire servo drive according to the single-axis performance deviation value, and perform performance quality analysis on the servo drive according to the comprehensive performance deviation value to obtain the performance quality analysis result.

[0116] In one embodiment, it further includes: The performance difference analysis module is used to obtain the performance index difference between adjacent test cycles, and obtain the performance change value and performance decay rate corresponding to the performance index score according to the performance index difference; The trend analysis module is used to construct a performance change trend curve corresponding to the performance index difference according to the performance change value and the performance decay rate; An early warning analysis module, which is used to analyze the performance decay trend of the servo driver according to the performance change trend curve, and obtain the performance early warning value of the current servo driver; A maintenance prompt module, which is used to output maintenance processing information to the control system when the actual performance of the servo driver reaches the performance early warning value.

[0117] In one embodiment, the parameter adjustment module includes: A correlation analysis unit, which is used to obtain the control parameter correlation of mutually coupled axes, where the control parameters include the parameters of the speed loop, position loop, and torque loop; A coupling coefficient calculation unit, which is used to calculate the parameter coupling influence coefficient between each axis according to the control parameter correlation; A parameter optimization unit, which is used to synergistically optimize and adjust the compensation parameters of each axis based on the parameter coupling influence coefficient, and generate a compensation parameter group considering the inter-axis coupling influence; A compensation verification unit, which is used to adjust the control parameters of each axis according to the compensation parameter group, and perform an inter-axis synchronous motion test to verify the compensation effect.

[0118] In one embodiment, the parameter optimization unit includes: An axis group analysis subunit, which is used to determine the associated axis group according to the parameter coupling influence coefficient, and analyze the performance complementary characteristics of each axis within the associated axis group; A compensation ratio calculation subunit, which is used to calculate the parameter compensation ratio of each axis within the associated axis group, and the parameter compensation ratio is used to balance the dynamic response characteristics of each axis; A parameter generation subunit, which is used to generate a compensation parameter group considering the inter-axis coupling influence according to the performance complementary characteristics and the parameter compensation ratio.

[0119] In one embodiment, the present application provides an electronic device, which may be a server, and its internal structure diagram may be as Figure 9 shown. The electronic device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the electronic device is used to store data. The network interface of the electronic device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a test method for a multi-axis integrated servo driver.

[0120] Those skilled in the art can understand, Figure 9The structure shown is only a block diagram of some of the structures related to the solution of this application, and does not constitute a limitation on the electronic device to which the solution of this application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0121] In one embodiment, an electronic device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0122] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The above computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0123] The above are all the preferred embodiments of this application. The protection scope of this application is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. A method for testing a multi-axis integrated servo drive, characterized in that: The steps include: Acquire the communication status information and operation parameter information of the servo drive, wherein the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operation parameter information includes the brake signal status, torque feedback value and IO signal status; According to the communication status information and the operating parameter information, the function of the servo drive is tested and analyzed to obtain a function test result; According to the functional test result, determine whether the working state of the servo drive is abnormal, and if abnormal, trigger corresponding alarm information; The execution status of the test process is determined according to the alarm information, and the continuation or termination of the test process is controlled.

2. The method for testing a multi-axis integrated servo driver according to claim 1, characterized in that: According to the communication status information and the operating parameter information, the function of the servo drive is tested and analyzed to obtain a function test result, which specifically includes the following steps: According to the EtherCAT bus status and the connection status of each axis, a communication function test is performed to detect the state machine switching process of the EtherCAT bus and determine the bus operation status of each axis; According to the brake signal status, the brake function test is performed, each axis is controlled to enter the enabled state and the brake is opened, and the state of each axis is detected through the status word and the brake signal; According to the torque feedback value, a bidirectional load test is performed, wherein: The main control PLC controls each axis of the tested drive to run in the forward direction, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply a forward load, and collects the actual torque value to judge the forward load state; The main control PLC controls the axes of the tested drive to run in reverse, and at the same time controls the auxiliary PLC to drive the CAN bus servo system to apply reverse load, and collects the actual torque value to judge the reverse load state; The auxiliary PLC adjusts the load size in real time according to the torque feedback value transmitted by the main PLC; According to the IO signal status, a digital input signal test is performed, and a test signal is sent to the digital input terminal of the servo drive through the main PLC output port in a preset order, and the response status of each digital input terminal is verified by reading the object dictionary.

3. The testing method of the multi-axis integrated servo driver according to claim 1, characterized in that: According to the functional test result, it is determined whether the working state of the servo drive is abnormal. If abnormal, the corresponding alarm information is triggered, and the method further comprises the following steps: Obtaining basic operating parameters and load response characteristics of each axis of the servo drive, wherein the basic operating parameters include speed command values, position command values, and torque command values ​​of each axis, and the load response characteristics include actual operating data of each axis under load; Analyze the performance quality of the servo drive according to the basic operating parameters and the corresponding load response characteristics to obtain a performance quality analysis result, wherein the performance quality analysis result includes a speed response characteristic analysis, a position accuracy analysis, a torque followability analysis, and an inter-axis synchronization analysis; According to the performance quality analysis result, parameter diagnosis is performed on the servo drive, and directional parameter compensation analysis is performed on the axis whose performance does not meet the standard to obtain corresponding compensation parameters; The operating parameters of the servo driver are adjusted according to the compensation parameters, and a correction instruction is generated and sent to the servo driver according to the adjusted operating parameters, so that the servo driver re-executes the test process.

4. The method for testing a multi-axis integrated servo driver according to claim 3, characterized in that: According to the basic operating parameters and the corresponding load response characteristics, the performance quality of the servo drive is analyzed to obtain a performance quality analysis result, which specifically includes the following steps: Calculating the dynamic response parameters of each axis according to the basic operating parameters and load response characteristics, wherein the dynamic response parameters include response time, overshoot and steady-state error; Calculating the performance index scores of each axis under different load conditions according to the dynamic response parameters; Analyze the deviation between the current performance index and the preset standard performance according to the performance index score to obtain the single-axis performance deviation value of the current axis; The comprehensive performance deviation value of the entire servo drive is estimated according to the single-axis performance deviation value, and the performance quality analysis of the servo drive is performed according to the comprehensive performance deviation value to obtain the performance quality analysis result.

5. The method for testing a multi-axis integrated servo driver according to claim 4, characterized in that: The method further comprises: Obtaining a performance indicator difference between adjacent test cycles, and obtaining a performance change value and a performance decay rate corresponding to the performance indicator score according to the performance indicator difference; Constructing a performance change trend curve corresponding to the performance indicator difference according to the performance change value and the performance decay rate; Analyze the performance attenuation trend of the servo drive according to the performance change trend curve to obtain a performance warning value of the current servo drive; When the actual performance of the servo drive reaches the performance warning value, maintenance processing information is output to the control system.

6. The method for testing a multi-axis integrated servo driver according to claim 3, characterized in that: Adjusting the operating parameters of the servo drive according to the compensation parameters specifically includes the following steps: Obtaining a correlation degree of control parameters of mutually coupled axes, wherein the control parameters include parameters of a speed loop, a position loop, and a torque loop; Calculating the parameter coupling influence coefficient between the axes according to the control parameter correlation degree; Based on the parameter coupling influence coefficient, the compensation parameters of each axis are collaboratively optimized and adjusted to generate a compensation parameter group that takes into account the influence of inter-axis coupling; The control parameters of each axis are adjusted according to the compensation parameter group, and an inter-axis synchronous motion test is performed to verify the compensation effect.

7. The method for testing a multi-axis integrated servo driver according to claim 6, characterized in that: Based on the parameter coupling influence coefficient, the compensation parameters of each axis are collaboratively optimized and adjusted to generate a compensation parameter group that considers the influence of inter-axis coupling, which specifically includes the following steps: Determine an associated axis group according to the parameter coupling influence coefficient, and analyze the performance complementary characteristics of each axis in the associated axis group; Calculating a parameter compensation ratio of each axis in the associated axis group, wherein the parameter compensation ratio is used to balance the dynamic response characteristics of each axis; A compensation parameter group considering the influence of inter-axis coupling is generated according to the performance complementary characteristic and the parameter compensation ratio.

8. A test system for a multi-axis integrated servo drive, characterized in that: include: An information acquisition module, used to acquire communication status information and operating parameter information of the servo drive, wherein the communication status information includes the EtherCAT bus status and the connection status of each axis, and the operating parameter information includes the brake signal status, torque feedback value and IO signal status; A function test module, used to test and analyze the function of the servo drive according to the communication status information and the operating parameter information to obtain a function test result; An abnormal alarm module is used to determine whether the working state of the servo drive is abnormal according to the functional test result, and trigger corresponding alarm information if abnormal; The execution status determination module is used to determine the execution status of the test process according to the alarm information and control the continuation or termination of the test process.

9. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for testing a multi-axis integrated servo drive according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for testing a multi-axis integrated servo drive according to any one of claims 1 to 7 are implemented.

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