Function detection device and method for servo driver

Abstract

The invention discloses a function detection device and method for a servo driver, and the device achieves the precise construction of a performance characteristic relation cluster of the servo driver through a performance relation cluster construction module, assists the subsequent function detection to quickly position a key performance index, improves the detection efficiency, and improves the detection precision. The servo driver structured matrix generation module converts hardware and software architecture into structured information, the detection process is simplified, the accuracy is enhanced, newly added or modified components are easy to manage, potential performance problems or fault points can be found in time through comprehensive function detection, measures are taken in advance for repair or improvement, and the detection efficiency is improved. The reliability and stability of the servo driver are improved, regular detection result output helps a user to know the long-term performance trend, servo driver detection and maintenance are optimized through a systematic method, it is ensured that the system operates efficiently and stably, user requirements are met, and the overall performance and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of servo drive detection, and particularly to a function detection device and method for a servo drive. Background Art

[0002] As an important part of modern motion control, servo drives are widely used in various automation equipment such as industrial robots, numerical control machine tools, printing equipment, textile machinery, and medical equipment. Its main function is to convert the instructions issued by the upper computer into signals that can be recognized by the servo motor, so as to achieve precise control of the servo motor, including position control, speed control, and torque control, etc. By precisely controlling the position and speed of the servo motor, the servo drive realizes precise tracking and replication of various complex motion trajectories, significantly improving production efficiency and product quality.

[0003] However, with the wide application of servo drives in the field of industrial automation, the stability and reliability of their performance become particularly important. During the production process of servo drives, as well as in their subsequent use and maintenance, it is necessary to comprehensively and accurately detect their functions. Traditional detection methods often rely on manual operation, which is not only inefficient but also prone to errors. In addition, due to the complex hardware and software architecture of servo drives, including multiple components and their interrelationships, traditional detection methods often have difficulty comprehensively covering all components and their functions. Summary of the Invention

[0004] In view of this, the present invention proposes a function detection device and method for a servo drive, which can effectively solve the defects of low efficiency, high error rate, and difficulty in comprehensively covering all components and their functions existing in the prior art.

[0005] The technical solution of the present invention is implemented as follows:

[0006] A function detection device for a servo drive, comprising:

[0007] A performance relationship cluster construction module, configured to construct a performance relationship cluster containing multiple performance indicators according to the operating parameters and historical data of the servo drive;

[0008] A servo drive structured matrix generation module, configured to generate a structured matrix containing all components and their interrelationships according to the hardware and software architecture of the servo drive. Each element in the structured matrix includes a pointer field and a data field pointing to the corresponding component. The pointer field is used to indicate the position of the component in the system, and the data field is used to store the performance indicators and status information of the component;

[0009] A function detection execution module, which is used to detect various functions of the servo drive by accessing the data fields of each component through a traversal pointer domain by using a performance relationship cluster and a servo drive structured matrix;

[0010] A result output module, which is used to output the function detection result through a visual interface or in the form of a report.

[0011] As a further optional solution of the function detection device for the servo drive, the performance relationship cluster construction module constructs a performance relationship cluster including multiple performance indicators according to the operating parameters and historical data of the servo drive, specifically including:

[0012] Define performance indicators and corresponding calculation formulas, where the performance indicators include a position accuracy index, a speed volatility rate, a response time, and an energy efficiency ratio. The position accuracy index is used to measure the accuracy of servo drive positioning, the speed volatility rate is used to evaluate the speed stability of the servo drive during operation, the response time is used to measure the time from the instruction issuance to the servo drive response, and the energy efficiency ratio is used to reflect the energy utilization efficiency of the servo drive;

[0013] Collect the position proportional gain, speed proportional gain, acceleration time constant of the servo drive, and the performance index records of the servo drive under different conditions;

[0014] Use statistical methods to analyze the correlation between operating parameters and performance indicators;

[0015] Based on the correlation analysis result, construct a multiple linear regression model;

[0016] Embed the calculation formulas corresponding to the performance indicators into the model to obtain a performance indicator prediction model;

[0017] Combine multiple performance indicators and their corresponding prediction models together. Each performance indicator corresponds to one or more operating parameters. Through the prediction model, the performance indicators under different parameter settings can be predicted, forming a performance relationship cluster including multiple performance indicators.

[0018] As a further optional solution of the function detection device for the servo drive, the servo drive structured matrix generation module is used to generate a structured matrix including all components and their mutual relationships according to the hardware and software architecture of the servo drive. Each element in the structured matrix includes a pointer domain and a data domain pointing to the corresponding component. The pointer domain is used to indicate the position of the component in the system, and the data domain is used to store the performance indicators and status information of the component, specifically including:

[0019] Design a two-dimensional matrix, where the rows and columns respectively represent different components of the servo drive. Each element of the two-dimensional matrix includes a pointer domain and a data domain;

[0020] Identify all hardware and software components of the servo drive and assign a unique identifier to each component;

[0021] Evaluate the performance metrics of the components;

[0022] Use a graphical tool to draw a hardware and software architecture diagram of the servo drive, showing the connections and dependencies between components;

[0023] Identify the interaction methods of data flow and control signal transmission between components;

[0024] Create an empty matrix with a size matching the number of servo drive components;

[0025] According to the component relationship diagram, fill the pointer fields of each element of the matrix, where the pointer fields contain references or addresses to the corresponding components;

[0026] Use the collected component status information to fill the data fields, where the data fields contain the performance metrics and current status information of the components.

[0027] As a further optional solution for the function detection device for the servo drive, the function detection execution module uses the performance relationship cluster and the servo drive structured matrix to access the data fields of each component by traversing the pointer fields, and detects the various functions of the servo drive, specifically including:

[0028] Obtain the pre-constructed performance relationship cluster and structured matrix;

[0029] Traverse the pointer fields of the structured matrix and access the data fields of each component in turn;

[0030] For each accessed component, read the performance metrics and status information in its data field;

[0031] Use the calculation formulas in the performance relationship cluster to calculate the read performance metrics to obtain the performance evaluation results;

[0032] Compare the performance evaluation results with the predefined detection criteria to determine whether each component meets the function requirements, and record the performance metrics that do not meet the standards;

[0033] Generate a detailed detection report according to the detection results, listing all components that do not meet the standards and their performance metrics.

[0034] As a further optional solution for the function detection device for the servo drive, the result output module outputs the function detection results through a visual interface or in the form of a report, specifically including:

[0035] Obtain the various function detection results of the servo drive;

[0036] According to the user's requirements, select to output the detection results in the form of a visual interface or a generated report;

[0037] Fill the data of the detection results of each function into the visual interface or the report template.

[0038] A function detection method for a servo drive, specifically including:

[0039] Performance relationship cluster construction step: According to the operating parameters and historical data of the servo drive, construct a performance relationship cluster including multiple performance indicators;

[0040] Servo drive structured matrix generation step: According to the hardware and software architecture of the servo drive, generate a structured matrix, which includes all components of the servo drive and their interrelationships. Among them, each element of the structured matrix includes a pointer field and a data field. The pointer field is used to clearly indicate the specific position of the component in the servo drive system, and the data field is used to store the performance indicators and status information associated with the component;

[0041] Function detection execution step: Utilize the constructed performance relationship cluster and the generated servo drive structured matrix, and access the data fields of each component by traversing the pointer field, so as to comprehensively detect the various functions of the servo drive;

[0042] Result output step: Output the results of the function detection in the form of a visual interface or a generated report.

[0043] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-mentioned function detection method for a servo drive.

[0044] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps of the above-mentioned function detection method for a servo drive.

[0045] The beneficial effects of the present invention are as follows: Through the performance relationship cluster construction module, based on the actual operating parameters and historical data of the servo drive, a relationship cluster reflecting its performance characteristics can be accurately constructed, which helps to more quickly locate key performance indicators in subsequent function detection, thereby improving the detection efficiency. The servo drive structured matrix generation module, through a systematic approach, transforms the hardware and software architecture of the servo drive into structured information that is easy to manage and analyze. This structured representation method not only simplifies the detection process but also enhances the accuracy of detection because the location, performance indicators, and status information of each component are clearly recorded. The design of the structured matrix makes it relatively simple to add new components or modify existing components. Simply adding or updating the corresponding elements in the matrix can achieve flexible adjustment of the servo drive architecture. Through comprehensive function detection, this technical solution can timely discover potential performance problems or fault points in the servo drive, which helps to take measures in advance for repair or improvement, thereby enhancing the reliability and stability of the servo drive. At the same time, regular output of detection results also helps users understand the long-term performance trends of the servo drive. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in 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 in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0047] Figure 1 It is a schematic diagram of the composition of a function detection device for a servo drive according to the present invention;

[0048] Figure 2 It is a schematic flow diagram of a function detection method for a servo drive according to the present invention;

[0049] Figure 3 It is a schematic diagram of the composition of a computing device according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0051] Refer to Figures 1 to 3 , a function detection device for a servo drive, comprising:

[0052] A performance relationship cluster construction module, which is used to construct a performance relationship cluster containing multiple performance indicators according to the operating parameters and historical data of the servo drive;

[0053] A servo drive structured matrix generation module, which is used to generate a structured matrix containing all components and their interrelationships according to the hardware and software architecture of the servo drive. Each element in the structured matrix contains a pointer field and a data field pointing to the corresponding component. The pointer field is used to indicate the position of the component in the system, and the data field is used to store the performance indicators and status information of the component;

[0054] A function detection execution module, which is used to detect the various functions of the servo drive by traversing the data fields of each component through the performance relationship cluster and the servo drive structured matrix;

[0055] A result output module, which is used to output the function detection results in the form of a visual interface or a report.

[0056] In this embodiment, through the performance relationship cluster construction module, a relationship cluster reflecting the performance characteristics of the servo drive can be accurately constructed based on the actual operating parameters and historical data of the servo drive, which helps to more quickly locate key performance indicators in subsequent function detection, thereby improving the detection efficiency. The servo drive structured matrix generation module converts the hardware and software architecture of the servo drive into structured information that is easy to manage and analyze in a systematic way. This structured representation method not only simplifies the detection process but also enhances the accuracy of detection because the position, performance indicators, and status information of each component are clearly recorded. The design of the structured matrix makes it relatively simple to add new components or modify existing components. By simply adding or updating the corresponding elements in the matrix, flexible adjustment of the servo drive architecture can be achieved. Through comprehensive function detection, this technical solution can timely discover potential performance problems or fault points in the servo drive, which helps to take measures in advance for repair or improvement, thereby enhancing the reliability and stability of the servo drive. At the same time, regular output of detection results also helps users understand the long-term performance trend of the servo drive.

[0057] Preferably, the performance relationship cluster construction module constructs a performance relationship cluster containing multiple performance indicators according to the operating parameters and historical data of the servo drive, specifically including:

[0058] Define performance indicators and corresponding calculation formulas. Among them, the performance indicators include position accuracy index, speed volatility, response time, and energy efficiency ratio. The position accuracy index is used to measure the accuracy of servo drive positioning. The speed volatility is used to evaluate the stability of the servo drive speed during operation. The response time is used to measure the time from the instruction issuance to the servo drive response. The energy efficiency ratio is used to reflect the energy utilization efficiency of the servo drive;

[0059] Collect the position proportional gain, speed proportional gain, acceleration time constant of the servo drive, and the performance index records of the servo drive under different conditions;

[0060] Use statistical methods to analyze the correlation between operating parameters and performance indicators;

[0061] Based on the results of the correlation analysis, construct a multiple linear regression model;

[0062] Embed the calculation formula corresponding to the performance index into the model to obtain a performance index prediction model;

[0063] Combine multiple performance indicators and their corresponding prediction models together. Each performance indicator corresponds to one or more operating parameters. Through the prediction model, the performance indicators under different parameter settings can be predicted, forming a performance relationship cluster containing multiple performance indicators.

[0064] In this embodiment, by clearly defining key performance indicators such as position accuracy index, speed volatility, response time, and energy efficiency ratio and their calculation formulas, it provides specific and quantifiable criteria for the performance evaluation of the servo drive. This not only helps to accurately measure the performance of the servo drive but also provides a clear direction for subsequent performance optimization and improvement; collecting key operating parameters such as the position proportional gain, speed proportional gain, and acceleration time constant of the servo drive, as well as the performance index records under different conditions, provides a rich data basis for constructing the performance relationship cluster. This systematic data collection method ensures the comprehensiveness and accuracy of the data, providing reliable support for subsequent analysis and modeling; using statistical methods to analyze the correlation between operating parameters and performance indicators can reveal the internal relationship between parameters and performance, providing a scientific basis for constructing the prediction model. The multiple linear regression model constructed based on the results of the correlation analysis can comprehensively consider the influence of multiple operating parameters on the performance indicators, improving the accuracy and reliability of the prediction; embedding the calculation formula of the performance index into the prediction model to form a performance index prediction model enables the model to directly output the performance index value without additional calculation. This not only simplifies the performance evaluation process but also improves the efficiency and accuracy of the evaluation. At the same time, the prediction model can predict the performance indicators according to different parameter settings, providing a powerful tool for the parameter optimization and performance adjustment of the servo drive; combining multiple performance indicators and their corresponding prediction models together to form a performance relationship cluster containing multiple performance indicators. This comprehensive evaluation method can comprehensively reflect the performance status of the servo drive, providing more comprehensive and in-depth guidance for performance optimization and improvement. At the same time, the construction of the performance relationship cluster also provides strong support for the performance monitoring and fault diagnosis of the servo drive.

[0065] It should be noted that the calculation formulas corresponding to the performance indicators specifically include:

[0066] Position accuracy index P_Index = (|Set position - Actual position| / Set position) × 100% + α * ΔT;

[0067] Where α is the temperature influence coefficient and ΔT is the temperature change;

[0068] Speed volatility V_Fluctuation = (σV / μV) × 100%;

[0069] Where σV is the speed standard deviation and μV is the speed average value;

[0070] Energy efficiency ratio E_Efficiency = (Pout / Pin) × 100% - β * (IRMS / Irated)^2;

[0071] Where β is the current influence coefficient, IRMS is the root mean square current, and Irated is the rated current.

[0072] Preferably, the servo drive structured matrix generation module is used to generate a structured matrix including all components and their interrelationships according to the hardware and software architectures of the servo drive. Each element in the structured matrix includes a pointer field and a data field pointing to the corresponding component. The pointer field is used to indicate the position of the component in the system, and the data field is used to store the performance indicators and status information of the component, specifically including:

[0073] Design a two-dimensional matrix, where the rows and columns represent different components of the servo drive respectively. Each element of the two-dimensional matrix includes a pointer field and a data field;

[0074] Identify all hardware and software components of the servo drive and assign a unique identifier to each component;

[0075] Evaluate the performance indicators of the components;

[0076] Use a graphical tool to draw the hardware and software architecture diagrams of the servo drive, showing the connections and dependencies between components;

[0077] Identify the interaction methods of data flow and control signal transmission between components;

[0078] Create an empty matrix with a size matching the number of servo drive components;

[0079] According to the component relationship diagram, fill the pointer field of each element of the matrix. The pointer field contains a reference or address pointing to the corresponding component;

[0080] Using the collected component status information, fill the data fields, which include the performance metrics and current status information of the components.

[0081] In this embodiment, by generating a structured matrix that includes all components and their interrelationships, technicians can more easily understand the overall architecture of the servo drive, thereby improving the transparency of the system; the pointer field and data field in the structured matrix provide the location information and performance metrics / status information of the components respectively, which enables quick identification of the problem component in case of a failure and reference to the performance metrics and historical status information for diagnosis and repair; the component performance metrics stored in the data field can be used for system performance evaluation, and potential performance bottlenecks can be identified through analysis of these metrics and then optimized. In addition, the real-time updated status information helps in dynamically managing the system performance; by assigning a unique identifier to each component and uniformly representing it in the structured matrix, it helps to promote the standardized and modular design of the components, which not only improves the maintainability of the system but also reduces the cost of replacing or upgrading components; the generation process of the structured matrix takes into account the connections and dependencies between components, making the system more flexible in design and configurable according to different application scenarios.

[0082] Preferably, the function detection execution module uses the performance relationship cluster and the structured matrix of the servo drive to detect the various functions of the servo drive by traversing the pointer field to access the data fields of each component, specifically including:

[0083] Obtain the pre-constructed performance relationship cluster and structured matrix;

[0084] Traverse the pointer field of the structured matrix and sequentially access the data fields of each component;

[0085] For each accessed component, read the performance metrics and status information in its data field;

[0086] Use the calculation formulas in the performance relationship cluster to calculate the read performance metrics to obtain the performance evaluation result;

[0087] Compare the performance evaluation result with the predefined detection criteria to determine whether each component meets the function requirements, and record the performance metrics that do not meet the standards;

[0088] Generate a detailed detection report based on the detection results, listing all components that do not meet the standards and their performance metrics.

[0089] In this embodiment, by traversing the pointer fields of the structured matrix to access the data fields of each component, the function detection execution module can quickly and accurately obtain the performance indicators and status information of all components. This systematic detection method avoids the omissions and errors that may be caused by manual detection, thereby improving the detection efficiency and accuracy. This technical solution realizes the automation of the detection process and reduces manual intervention. The automated detection not only improves the detection speed but also reduces the errors caused by human factors, making the detection results more reliable. Using the calculation formulas in the performance relationship cluster, the read performance indicators are calculated in real time to obtain the performance evaluation results. This real-time evaluation ability helps to detect performance problems in a timely manner and take corresponding measures for repair or optimization. By comparing the performance evaluation results with the predefined detection standards, it can be determined whether each component meets the functional requirements. This standardized detection method ensures the consistency and fairness of the detection and helps to improve the quality and reliability of the overall system. The detailed detection report generated based on the detection results lists all the components that do not meet the standards and their performance indicators. This not only provides a clear repair direction for technicians but also provides strong data support for subsequent system improvement and optimization. The automated detection process reduces the need for manual detection, thereby reducing the maintenance cost. At the same time, the detailed detection report also provides technicians with a method to quickly locate and solve problems, further shortening the maintenance cycle.

[0090] Preferably, the result output module outputs the function detection results in the form of a visual interface or a report, specifically including:

[0091] Obtain the function detection results of each item of the servo drive;

[0092] According to the user's needs, select to output the detection results in the form of a visual interface or generate a report;

[0093] Fill the function detection result data of each item into the visual interface or the report template.

[0094] In this embodiment, the result output module provides two output forms, namely a visual interface and a report, according to the user's needs, enhancing the flexibility and user-friendliness of the system. Users can choose the most suitable output method according to their preferences and actual needs, thereby improving the user experience. The visual interface displays the detection results in intuitive forms such as charts and dashboards, enabling users to quickly understand the functional status of each item of the servo drive. This intuitive display method helps users quickly identify potential problems and take corresponding solutions. The generated report form details the function detection results of each item of the servo drive, including performance indicators, status information, and components that do not meet the standards, etc. This detailed recording method helps technicians for subsequent analysis and filing, providing strong data support for the maintenance and optimization of the system.

[0095] A functional detection method for a servo drive, specifically including:

[0096] Performance relationship cluster construction step: Construct a performance relationship cluster containing multiple performance indicators based on the operating parameters and historical data of the servo drive;

[0097] Servo drive structured matrix generation step: Generate a structured matrix according to the hardware and software architectures of the servo drive. The matrix contains all components of the servo drive and their interrelationships. Each element of the structured matrix includes a pointer field and a data field. The pointer field is used to clearly indicate the specific position of the component in the servo drive system, and the data field is used to store the performance indicators and status information associated with the component;

[0098] Functional detection execution step: Utilize the constructed performance relationship cluster and the generated servo drive structured matrix to access the data fields of each component by traversing the pointer field, thereby comprehensively detecting the various functions of the servo drive;

[0099] Result output step: Output the results of the functional detection in the form of a visual interface or a generated report.

[0100] A computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned functional detection method for the servo drive are implemented.

[0101] 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 functional detection method for the servo drive are implemented.

[0102] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A functional detection device for a servo driver, characterized in that, Including: A performance relationship cluster construction module, which is used to construct a performance relationship cluster including multiple performance indicators according to the operating parameters and historical data of the servo drive; A servo drive structured matrix generation module, which is used to generate a structured matrix including all components and their interrelationships according to the hardware and software architecture of the servo drive. Each element in the structured matrix includes a pointer field and a data field pointing to the corresponding component. The pointer field is used to indicate the position of the component in the system, and the data field is used to store the performance indicators and status information of the component; A function detection execution module, which is used to detect various functions of the servo drive by traversing the data fields of each component through the pointer field by using the performance relationship cluster and the servo drive structured matrix; A result output module, which is used to output the function detection result in the form of a visual interface or a report.

2. The functional detection device for a servo driver according to claim 1, characterized in that, The performance relationship cluster construction module constructs a performance relationship cluster including multiple performance indicators according to the operating parameters and historical data of the servo drive, specifically including: Defining performance indicators and corresponding calculation formulas. Among them, the performance indicators include position accuracy index, speed volatility, response time, and energy efficiency ratio. The position accuracy index is used to measure the positioning accuracy of the servo drive, the speed volatility is used to evaluate the speed stability of the servo drive during operation, the response time is used to measure the time from the instruction issuance to the response of the servo drive, and the energy efficiency ratio is used to reflect the energy utilization efficiency of the servo drive; Collecting the position proportional gain, speed proportional gain, acceleration time constant of the servo drive, and the performance index records of the servo drive under different conditions; Using statistical methods to analyze the correlation between operating parameters and performance indicators; Based on the correlation analysis results, constructing a multiple linear regression model; Embedding the calculation formula corresponding to the performance indicator into the model to obtain a performance indicator prediction model; Combining multiple performance indicators and their corresponding prediction models together. Each performance indicator corresponds to one or more operating parameters, and the performance indicators under different parameter settings can be predicted through the prediction model, forming a performance relationship cluster including multiple performance indicators.

3. The functional detection device for a servo driver according to claim 2, characterized in that, The servo drive structured matrix generation module is used to generate a structured matrix including all components and their interrelationships according to the hardware and software architecture of the servo drive. Each element in the structured matrix includes a pointer field and a data field pointing to the corresponding component. The pointer field is used to indicate the position of the component in the system, and the data field is used to store the performance indicators and status information of the component, specifically including: Designing a two-dimensional matrix, where the rows and columns respectively represent different components of the servo drive. Each element of the two-dimensional matrix includes a pointer field and a data field; Identifying all hardware and software components of the servo drive and assigning a unique identifier to each component; Evaluating the performance indicators of the components; Using a graphical tool to draw the hardware and software architecture diagrams of the servo drive to show the connections and dependencies between components; Identifying the interaction methods of data flow and control signal transmission between components; Creating an empty matrix with a size matching the number of servo drive components; According to the component relationship diagram, fill the pointer field for each element of the matrix, where the pointer field contains a reference or address pointing to the corresponding component; Use the collected component status information to fill the data field, where the data field contains the performance metrics and current status information of the component.

4. The functional detection device for a servo driver according to claim 3, characterized in that, The function detection execution module uses the performance relationship cluster and the servo drive structured matrix to access the data fields of each component by traversing the pointer field, and detects the various functions of the servo drive, specifically including: Obtain the pre-constructed performance relationship cluster and structured matrix; Traverse the pointer field of the structured matrix and access the data fields of each component in turn; For each accessed component, read the performance metrics and status information in its data field; Use the calculation formula in the performance relationship cluster to calculate the read performance metrics to obtain a performance evaluation result; Compare the performance evaluation result with the predefined detection criteria to determine whether each component meets the function requirements, and record the performance metrics that do not meet the criteria; Generate a detailed detection report based on the detection results, listing all components that do not meet the standards and their performance metrics.

5. The functional detection device for a servo driver according to claim 4, characterized in that, The result output module outputs the function detection results in the form of a visual interface or a report, specifically including: Obtain the detection results of various functions of the servo drive; According to the user's needs, select to output the detection results in the form of a visual interface or generate a report; Fill the data of the detection results of various functions into the visual interface or report template.

6. A functional detection method for a servo drive, characterized in that, Specifically include: Performance relationship cluster construction step: Construct a performance relationship cluster containing multiple performance metrics according to the operating parameters and historical data of the servo drive; Servo drive structured matrix generation step: Generate a structured matrix according to the hardware and software architecture of the servo drive, where the matrix contains all components of the servo drive and their mutual relationships. Each element of the structured matrix contains a pointer field and a data field. The pointer field is used to clearly indicate the specific position of the component in the servo drive system, and the data field is used to store the performance metrics and status information associated with the component; Function detection execution step: Use the constructed performance relationship cluster and the generated servo drive structured matrix to access the data fields of each component by traversing the pointer field, so as to comprehensively detect the various functions of the servo drive; Result output step: Output the results of the function detection in the form of a visual interface or generate a report.

7. A computing device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the function detection method for the servo drive described in claim 6.

8. A computer-readable storage medium, characterized in that, A computer program is stored on the storage medium. When the computer program is executed by the processor, it implements the steps of the function detection method for the servo drive described in claim 6.

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