Data collection method and device for servo parameter setting, servo system and storage medium

Abstract

The invention provides a data collection method and device for servo parameter setting, a servo system and a storage medium, and the method comprises the steps: collecting initial configuration parameters of the servo system after the connection with at least one servo system is determined, and setting the initial configuration parameters of the servo system after the servo system responds to a one-key setting instruction; setting the configuration parameters and the operation data after adjustment and optimization in a one-key setting process; and integrating the collected initial configuration parameters and feedback data to obtain a sample data set for servo parameter setting, and taking the sample data set as sample data for subsequent servo system parameter setting. According to the method and the device, the initial configuration parameters and the empirical data of the servo system and the feedback data obtained by means of the one-key setting function of the servo system are automatically collected, and the sample data set for servo parameter setting is finally obtained through integration, so that the sample basis of servo system parameter setting is enriched; and the stability and the precision of follow-up servo parameter setting can be improved.

Description

Technical Field

[0001] The present invention relates to the field of servo systems, in particular to the tuning of servo system control parameters. More specifically, the present invention relates to a data collection method, device, servo system, and storage medium for servo parameter tuning. Background Art

[0002] A servo system, also known as a follow-up system, can accurately control position, speed, and torque to achieve precise regulation of various mechanical movements. Specifically, according to the actual displacement of the moving part detected in real time, it is compared with the preset position command signal, and according to the difference between the two, through position adjustment, it is converted into various control signals such as position, orientation, and state; these control signals are used to control the driving device to move in the direction of eliminating the deviation at a specific speed until the difference between the command position and the actual feedback position is reduced to zero.

[0003] Due to its characteristics of high precision, high response speed, and high reliability, the servo system has been widely used in many fields such as industrial automation, aerospace, transportation, medical equipment, and robots. In these fields, the servo system is used for control to achieve precise position, speed, and torque control. In actual applications, different application scenarios have different performance requirements for the servo system, and the system will be affected by various factors during operation, resulting in its performance deviating from the optimal state. Therefore, in order to meet the diverse needs of different application scenarios, it is necessary to tune the parameters of the servo system to improve system performance such as control accuracy, flexibility, and stability of the servo system, ensure that the servo system operates with optimal parameters under various working conditions, improve production speed, reduce debugging time, and extend the service life of the equipment.

[0004] When the existing servo system drivers perform parameter tuning, most of them rely on empirical data, including historical debugging records, manufacturer recommended values, or personal experience of engineers, and the empirical data is usually based on a single working condition or a specific working condition. However, in practice, the results after parameter tuning based on empirical data, when facing more complex working conditions, can significantly limit the dynamic performance of the servo system and increase the steady-state accuracy deviation, and at the same time, it also leads to an extension of the engineer's debugging cycle, an increase in the difficulty of fault troubleshooting, and an increase in maintenance costs. Therefore, it is very necessary to collect and integrate parameter data and working condition data of various types and various working conditions for the servo parameter tuning process. Summary of the Invention

[0005] Based on this, the present application proposes a data collection method, device, servo system, and storage medium for servo parameter tuning to solve the technical problems that the data for servo system parameter tuning currently depends on empirical data, and single or specific empirical data leads to limited dynamic performance of the servo system, increased steady-state accuracy deviation, and increased maintenance costs.

[0006] In a first aspect, an embodiment of the present application provides a data collection method for servo parameter tuning, including: After determining the connection with the servo system, obtain the initial configuration parameters of the servo system; wherein, the initial configuration parameters include at least one of the type and rated current of the motor in the servo system, the rated speed and load inertia ratio, the encoder resolution, the position loop parameters, the speed loop parameters, and the current loop parameters; Output a one-key tuning instruction to the servo system, and collect the feedback data of the servo system in response to the one-key tuning instruction; wherein, the feedback data includes the configuration parameters and operation data adjusted and optimized during the one-key tuning process; the operation data includes at least one of position-related parameters, speed-related parameters, current-related parameters, and system performance and status parameters; Integrate the initial configuration parameters and the feedback data to obtain a sample data set for servo parameter tuning; the sample data set includes the initial configuration parameters and feedback data of at least one servo system.

[0007] In some embodiments, the outputting a one-key tuning instruction to the servo system and collecting the feedback data of the servo system in response to the one-key tuning instruction includes: In response to the test run instruction, output an instruction to control the servo system to run based on the initial configuration parameters to the servo system, and collect the initial operation data; After the servo system completes the initial operation, output a one-key tuning instruction to the servo system, and collect the configuration parameters adjusted and optimized during the one-key tuning process; the one-key tuning instruction is used to control the servo system to call a preset one-key tuning algorithm for one-key tuning; After the one-key tuning is completed, output an instruction to control the servo system to perform at least one complete operation again based on the adjusted and optimized configuration parameters to the servo system, and collect and integrate the adjusted and optimized operation data.

[0008] In some embodiments, the collecting the feedback data of the servo system in response to the one-key tuning instruction further includes: Send the real-time collected operation data to an externally connected interaction device, and monitor the system performance during the operation of the servo system through the interaction device; Output a repeated tuning instruction to the servo system until it is monitored that the performance of the servo system is in a stable state; the repeated tuning instruction is used to control the servo system to repeat the one-key tuning.

[0009] In some embodiments, the operation data further includes at least one of the state parameters, performance parameters, and alarm information in different states during the operation of the servo system.

[0010] In some embodiments, the data collection method for servo parameter tuning further includes: Collecting the empirical parameters manually input and matching the servo system as part of the sample data set for servo parameter tuning.

[0011] In some embodiments, after obtaining the sample data set for servo parameter tuning, the data collection method further includes: Judging whether it is currently connected to the Internet; After determining to establish a connection to the Internet, in response to the online upload instruction, uploading and storing the sample data set to a specified location on the Internet.

[0012] In some embodiments, after obtaining the sample data set for servo parameter tuning, the data collection method further includes: After determining that it is not connected to the Internet, judging whether it is connected to a local storage device; After determining to be connected to the local storage device, in response to the offline transmission instruction, transmitting the sample data set to a specified location of the local storage device.

[0013] In a second aspect, an embodiment of the present application provides a data collection device for servo parameter tuning, including: A first interface module for connecting to the servo system to be tuned; A second interface module for connecting to the Internet and / or a local storage device; A memory for storing computer execution programs or instructions; A processor for executing the computer execution programs or instructions to implement the data collection method for servo parameter tuning as described in any embodiment of the first aspect; An interactive display module for monitoring the state of the servo system during data collection, inputting corresponding interactive instructions according to the state of the servo system, and manually inputting empirical parameters matching the servo system. <http: / / www.sipo.gov.cn / sipo2008 / zljs / zljs.jsp?action=show&id=

[0014] In a third aspect, an embodiment of the present application provides a servo system, at least including: A communication module for establishing a connection with the data collection device for servo parameter tuning as described in the second aspect, or establishing a connection with a host computer storing an application program implementing the data collection method for servo parameter tuning as described in any embodiment of the first aspect; A data acquisition module for obtaining the sample data set for servo parameter tuning from the servo parameter tuning device through offline transmission, or obtaining the sample data set for servo parameter tuning from the host computer through online download; A parameter tuning module, configured to call a parameter tuning algorithm to perform parameter tuning according to the obtained sample data set, so as to enable the system to achieve the best performance; A servo control module, configured to output control instructions; A servo motor module, configured to operate according to the control instructions output by the servo control module.

[0015] In some embodiments, the parameter tuning module is further configured to: Input the sample data set into a pre-constructed AI training model, train the input sample data according to a preset algorithm, and calculate and obtain the optimal configuration parameters of the servo system; perform parameter tuning according to the optimal configuration parameters, so as to enable the system to achieve the best performance.

[0016] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a program or instruction executed by a computer is stored, and when the program or instruction executed by the computer is executed by a processor, it is used to implement the data collection method for servo parameter tuning as described in any embodiment of the first aspect.

[0017] The data collection method, device, servo system and storage medium for servo parameter tuning provided by the embodiments of the present application include, after determining the connection with at least one servo system, collecting the initial configuration parameters of the servo system and the configuration parameters and operation data adjusted and optimized during the one-key tuning process after the servo system responds to the one-key tuning instruction; integrating the collected initial configuration parameters and feedback data to obtain a sample data set for servo parameter tuning, which is used as the sample data for subsequent servo system parameter tuning, in order to obtain a set of optimal servo system parameters that can keep the servo system in the best performance. The present application realizes the automatic collection of the initial configuration parameters, empirical data of the servo system and the feedback data obtained by means of the one-key tuning function of the servo system itself. The finally integrated sample data set for servo parameter tuning enriches the sample basis for servo system parameter tuning, helps to improve the stability and accuracy of subsequent servo parameter tuning and debugging, and shortens the tuning and debugging cycle.

[0018] In addition, the present application also provides a computer-readable storage medium, a computer program product and a chip, which have the same beneficial effects as the above temperature compensation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings here are incorporated into the specification and form a part of the specification, showing the embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0020] Figure 1 It is a flowchart of the data collection method for servo parameter tuning provided by an embodiment of the present application.

[0021] Figure 2 Flow chart for collecting feedback data provided by an embodiment of the present application.

[0022] Figure 3 Flow chart for collecting feedback data provided by another embodiment of the present application.

[0023] Figure 4 Flow chart for a data collection method for servo parameter tuning provided by another embodiment of the present application.

[0024] Figure 5 Flow chart for a data collection method for servo parameter tuning provided by yet another embodiment of the present application.

[0025] Figure 6 Schematic structural diagram of a servo parameter tuning device provided by an embodiment of the present application.

[0026] Figure 7 Schematic structural diagram of a servo system provided by an embodiment of the present application.

[0027] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of the Embodiments

[0028] The present invention will be further described in detail below in conjunction with the accompanying drawings through specific embodiments. Similar elements in different embodiments are denoted by related similar element numbers. In the following embodiments, many details are described to enable a better understanding of the present application. However, those skilled in the art can readily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present application are not shown or described in the specification to avoid overwhelming the core part of the present application with excessive descriptions. For those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the descriptions in the specification and general technical knowledge in the art.

[0029] In addition, the features, operations, or characteristics described in the specification can be combined in any appropriate manner to form various embodiments. At the same time, the steps or actions in the method description can also be reordered or adjusted in a manner obvious to those skilled in the art. Therefore, the various sequences in the specification and drawings are only for clearly describing a certain embodiment and do not mean a necessary sequence unless it is stated that a certain sequence must be followed.

[0030] The terms "first", "second", etc. in the description and claims of this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same category, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the description and claims means at least one of the connected objects, and the character " / " generally means that the related objects before and after are in an "or" relationship. And the "connection" and "coupling" mentioned in this application, unless otherwise specified, both include direct and indirect connection (coupling).

[0031] The following uses specific embodiments to elaborate in detail on the technical solution of this application and how the technical solution of this application solves the above technical problems. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will be described below in conjunction with the accompanying drawings.

[0032] Figure 1 It is a flowchart of a data collection method for servo parameter tuning provided for an embodiment of this application. As Figure 1 shown, the purpose of the data collection method for servo parameter tuning provided by the embodiment of this application is to collect and integrate the data sources for servo parameter tuning, and provide data support for optimizing the performance of the servo system subsequently, so that it can accurately, quickly, and stably respond to control instructions and meet the requirements of various industrial applications. The data collection method for servo parameter tuning is stored in a computer-executable software program product or an electronic device. The data collection method provided in this embodiment specifically includes the following steps: Step S110: After determining the connection with the servo system, obtain the initial configuration parameters of the servo system.

[0033] In this embodiment, before performing servo parameter tuning on the servo system, it is necessary to ensure that the connection of hardware devices such as servo drivers, motors, encoders, and sensors is correct without looseness or poor contact, so as to avoid data deviation during subsequent data collection. In some scenarios, it is also necessary to check the parameter settings of the servo driver to ensure its compatibility with the motor and load. For example, parameters such as motor type, rated power, and rated speed should match the actual equipment to provide good conditions for parameter tuning. At the same time, it is also necessary to prepare necessary test equipment, such as oscilloscopes, multimeters, position detection devices, etc., for collecting and analyzing the operating data of the servo system.

[0034] In this embodiment, obtaining the initial configuration parameters can comprehensively understand the current settings and performance status of the servo system, providing a basis for subsequent tuning work. Analyzing the initial parameters can identify possible performance bottlenecks or unreasonable settings, thereby determining the direction and focus of tuning. For example, specific performance indicators that are expected to be achieved through parameter tuning, such as improving position accuracy, reducing speed fluctuations, and enhancing system stability. Further, combined with the working conditions and load characteristics of the servo system in actual applications, the range and focus of the tuning parameters are determined to more specifically formulate a tuning strategy, reduce the number of trial-and-errors, and improve the tuning efficiency. Therefore, before tuning the servo parameters, collecting the initial configuration parameters can avoid the situation where the tuning work is carried out blindly, resulting in poor tuning effects or failure to achieve the expected goals. On the premise of fully understanding the servo system, it can also avoid problems such as system instability, excessive overshoot, slow response, and even damage to hardware devices caused by random adjustment due to lack of understanding of the initial parameters.

[0035] In some embodiments, the initial configuration parameters include at least one of the type and rated current of the motor in the servo system, the rated speed and load inertia ratio, the encoder resolution, the position loop parameters, the speed loop parameters, the current loop parameters, and the integral time constant.

[0036] The type and rated current of the motor, the rated speed and load inertia ratio, and the encoder resolution belong to the data related to the motor and load of the servo system. Specifically, understanding the motor type and rated power helps determine appropriate control strategies and parameter ranges. The rated speed determines the maximum operating speed of the motor, and the load inertia ratio reflects the inertia matching degree between the motor and the load, which has an important impact on the dynamic performance of the system. The encoder resolution determines the accuracy of position feedback. A higher resolution can provide more accurate position information, helping to improve the positioning accuracy of the system.

[0037] The position loop parameters, speed loop parameters, current loop parameters, and integral time constant belong to the basic control parameters of the servo system. Specifically, the position loop parameters are the key parameters for controlling the position accuracy of the servo system, such as the position loop gain (Kp), etc. The position loop gain determines the response speed of the servo system to position errors. A higher gain can improve the response speed of the system, but may cause system instability; a lower gain may make the system response slow.

[0038] The speed loop parameters are the key parameters for controlling the speed stability of the servo system, such as the speed loop gain (Kv), integral time constant (Ti), etc. They determine the system's ability to correct speed errors and suppress speed fluctuations. The speed loop gain affects the servo system's ability to correct speed errors. An appropriate speed loop gain can ensure that the system maintains a stable operating speed under different loads. The integral time constant is used to eliminate the steady-state error of the system. A smaller integral time constant can accelerate the elimination of errors, but may increase the overshoot of the system; a larger integral time constant may slow down the system response.

[0039] The current loop parameters are the key parameters for controlling the current and torque of the servo system, such as the current loop gain (Ki), current limit (I_max), etc. They determine the system's control accuracy of the motor current and dynamic response ability. The current loop gain determines the response speed of the current loop to current errors. A higher gain can accelerate the current regulation speed, but may cause oscillations; a lower gain results in a sluggish response. The current limit is the maximum allowable value for limiting the motor current, which is used to protect the motor and power devices from overcurrent damage.

[0040] It should be noted that when tuning the servo system, according to different usage scenarios and load characteristics, the parameter ranges and focuses to be tuned are different. When specifying the tuning strategy, the configuration parameters of the servo system can be selectively obtained according to actual needs.

[0041] Step S120: Output a one-key tuning instruction to the servo system and collect the feedback data of the servo system in response to the one-key tuning instruction; among them, the feedback data includes the configuration parameters and operation data adjusted and optimized during the one-key tuning process.

[0042] For the parameter tuning of the servo system, not only configuration parameters but also operation data are required. Only by combining the two can more optimal configuration parameters be obtained to make the performance of the servo system reach a better level. For some servo systems, they have the function of parameter tuning themselves. The process of one-key tuning of the servo system includes: ensuring that the servo system is in the startup state, running according to the initial configuration parameters in response to the one-key tuning instruction, and during the running process, real-time collecting the operation data of the servo system through sensors or the built-in detection function of the servo driver, and adjusting and optimizing the configuration parameters.

[0043] In this embodiment, based on the functions of the servo system itself, a one-key tuning command is output to it. After receiving this command, the servo system starts its own one-key tuning function, that is, the servo system starts parameter tuning in response to the one-key tuning command, and then collects the configuration parameters and operation data during the parameter tuning process of the servo through the connection interface. Collecting the actual operation performance of the servo system under the current configuration parameters can more intuitively understand the performance bottleneck and improvement direction of the servo system, providing a basis for subsequent AI model training to find a better parameter configuration.

[0044] In some embodiments, the operation data includes at least one of position-related parameters, speed-related parameters, current-related parameters, and system performance and status parameters.

[0045] The position-related parameters include the actual position and the position error, etc. The actual position reflects the actual position during the operation of the servo system and is used to evaluate the following situation of the system to the position command, which is a key indicator for judging the positioning accuracy and stability of the system. The position error reflects the difference between the commanded position and the actual position and is used to quantify the positioning accuracy of the system. By monitoring the position error, the parameters can be adjusted in time to reduce the error and improve the system accuracy.

[0046] The speed-related parameters include the actual speed, speed fluctuation, and speed error, etc. The actual speed reflects the current actual operating speed of the servo system and is used to evaluate the response situation of the system to the speed command, which is an important indicator for judging the speed control performance and stability of the system. The speed fluctuation reflects the change amount of the speed during the operation and is used to evaluate the speed stability of the system. Excessive speed fluctuation will affect the operation smoothness and accuracy of the system, and the parameters need to be adjusted in time to reduce the fluctuation. The speed error reflects the difference between the commanded speed and the actual speed and is used to quantify the tracking accuracy of the system to the speed command. By monitoring the speed error, the speed loop parameters can be optimized to improve the response accuracy of the system to the speed command.

[0047] The current-related parameters include the motor current and the output torque, etc. The motor current reflects the actual current value of the motor during the operation and is used to evaluate the load condition and energy consumption of the motor. Excessive current may cause the motor to overheat or be damaged, and the parameters need to be adjusted in time to control the current within a reasonable range. The output torque represents the torque value output by the motor and is used to evaluate the dynamic performance of the system. By monitoring the output torque, the load capacity and dynamic response situation of the system can be understood, providing a basis for parameter tuning.

[0048] System performance and status parameters include response time, overshoot, steady-state error, and system status word, etc. Response time represents the time required for the system to receive an instruction, start execution, and reach a stable state, which is used to evaluate the rapidity of the system. A shorter response time can improve the dynamic performance of the system and meet the requirement of rapid response. Overshoot represents the maximum deviation of the system from the instruction value during the response process, which is used to evaluate the stability of the system. Importance: Excessive overshoot may cause the system to be unstable or damaged, and parameters need to be adjusted in time to reduce the overshoot. Steady-state error represents the difference between the instruction value and the actual value of the system in the stable state, which is used to evaluate the steady-state accuracy of the system. A smaller steady-state error can improve the steady-state accuracy and stability of the system. The system status word contains an encoded word of various status information of the system, such as whether there is overcurrent, overvoltage, overheating, etc., which is used to monitor the operating state of the system. By monitoring the system status word, abnormal conditions of the system can be detected and processed in time to ensure the safe operation of the system.

[0049] The collection of any of the above operating parameters includes collection through monitoring with an oscilloscope, multimeter, and position detection device, reading through a servo drive, and reading through dedicated debugging software.

[0050] In some embodiments, if the servo system has been operated before, during the tuning operation test, it also includes collecting historical operation data for understanding the performance of the system under different parameter configurations when training samples for the subsequent AI model.

[0051] In some embodiments, the operation data further includes at least one of status parameters, performance parameters, and alarm information in different states during the operation of the servo system.

[0052] In some embodiments, the display form of the operation data includes parameter values and waveform diagrams.

[0053] Step S130: Integrate the initial configuration parameters and feedback data to obtain a sample data set for servo parameter tuning; wherein, the sample data set includes the initial configuration parameters and feedback data of at least one servo system.

[0054] In this embodiment, after collecting the initial configuration parameters of at least one servo system and the feedback data under at least one working condition, they are integrated to obtain a sample data set, which is used for subsequent parameter tuning of one or more servo systems.

[0055] In some embodiments, the sample data set for servo parameter tuning further includes: empirical parameters manually input and matching the servo system.

[0056] The empirical parameters are a summary based on past successful tuning cases, including effective parameter settings for specific servo systems or application scenarios. The empirical parameters reflect the parameter setting rules under different servo systems, load conditions, and motion tasks. Incorporating these parameters into the sample data collection increases the parameter basis under specific working conditions. During the subsequent servo system parameter tuning process, it can provide a wider range of parameter adjustment and optimization strategies, improving the adaptability to different scenarios. At the initial stage of parameter tuning, by introducing empirical parameters, the tuning process can be guided towards a better parameter combination, reducing the uncertainty of parameter adjustment, improving the accuracy of tuning, enhancing system performance, shortening the tuning cycle, and avoiding unnecessary trial-and-error processes.

[0057] In summary, for the data collection method for servo parameter tuning provided in this embodiment, after determining the connection to at least one servo system, first collect the initial configuration parameters of the servo system; secondly, output a one-key tuning instruction to the servo system and collect the feedback data of the servo system in response to the one-key tuning instruction, including the configuration parameters and operation data adjusted and optimized during the one-key tuning process; finally, integrate the collected initial configuration parameters and feedback data to obtain a sample data collection for servo parameter tuning, which is used as the sample data for subsequent servo system parameter tuning, with the expectation of obtaining a set of optimal servo system parameters that can keep the servo system in the best performance. The data collection method of this embodiment realizes the automatic collection of the initial configuration parameters of the servo system, empirical data, and feedback data obtained by means of the one-key tuning function of the servo system itself. The finally integrated sample data collection for servo parameter tuning enriches the sample basis for servo system parameter tuning, helps to improve the stability and accuracy of subsequent servo parameter tuning and debugging, and shortens the tuning and debugging cycle.

[0058] Figure 2 It is a flowchart for collecting feedback data provided by an embodiment of this application. As Figure 2 shown, in the data collection method for servo parameter tuning provided in any of the above embodiments, in step S120, output a one-key tuning instruction to the servo system and collect the feedback data of the servo system in response to the one-key tuning instruction, which specifically includes the following steps: Step S201, in response to the test run instruction, output an instruction to control the servo system to run based on the initial configuration parameters to the servo system, and collect the initial operation data.

[0059] Step S202, after the servo system completes the initial operation, output a one-key tuning instruction to the servo system and collect the configuration parameters adjusted and optimized during the one-key tuning process; wherein, the one-key tuning instruction is used to make the servo system call a preset one-key tuning algorithm for one-key tuning.

[0060] Step S203: After the one-key tuning is completed, output an instruction to the servo system to control it to perform at least one complete run again based on the adjusted and optimized configuration parameters, and collect the operation data after adjustment and optimization.

[0061] One-key tuning of servo system parameters refers to the process of automatically completing the adjustment and optimization of servo system parameters by simply clicking a button through specific software or tools. The one-key tuning function usually calculates the optimal parameter combination automatically based on preset algorithms and models, combined with the initial configuration parameters and operation data of the servo system. These algorithms may include the Ziegler-Nichols method, model predictive control, AI optimization algorithms, etc. The one-key tuning function, with parameter adjustment based on preset algorithms and real-time operation data, ensures the accuracy of the tuning results, greatly shortens the parameter adjustment time, and improves work efficiency.

[0062] In this embodiment, the process of collecting the feedback data of the servo system in response to the one-key tuning instruction is as follows: After starting the servo system, in response to the test run instruction, ensure that the initial configuration parameters have been written into the servo drive, and further output an instruction to control the servo system to run based on the initial configuration parameters. For the servo system, in response to this run instruction, control the servo system to perform a preset typical motion task and run at least once completely to ensure that the system covers typical working conditions and collect the operation data during the initial operation process; then output the one-key tuning instruction to the servo system. At this time, the servo system will respond to this one-key tuning instruction, call the preset one-key tuning algorithm, and automatically adjust the initial configuration parameters according to the real-time collected operation data (such as position error, speed fluctuation, current response, etc.) to calculate the adjusted and optimized configuration parameters; after the one-key tuning adjustment and optimization, output an instruction to the servo system again to control it to perform at least one complete run again based on the adjusted and optimized configuration parameters. The servo system responds to this instruction and runs again. At this time, collect the new round of operation data, and finally integrate the initial operation data and the optimized operation data to obtain the sample data.

[0063] The purpose of this is as follows: Although the one-key tuning of servo system parameters is an efficient and automated method for parameter adjustment and optimization, with the advantages of high accuracy, adaptability, efficiency, and intelligence, the effect of one-key tuning highly depends on the accuracy of the initial configuration parameters, and the tuning algorithm is usually based on preset models or empirical formulas. These models may not fully cover all actual application scenarios. For complex or special servo systems, the models may not accurately predict the effect of parameter adjustment and optimization. That is to say, the one-key tuning algorithm may fall into a local optimal solution and fail to find the global optimal parameter combination. In some cases, one-key tuning may only achieve limited performance improvement, which may lead to insufficient improvement of system performance. For application scenarios with extremely high requirements for system performance, further manual adjustment and optimization may be required.

[0064] Therefore, in this embodiment, the operation data collected based on one-key tuning is used as part of the sample data for subsequent servo system parameter tuning, and combined with the initial configuration parameters and / or empirically determined parameters manually input and matching the servo system, so as to achieve higher accuracy and adaptability of the configuration parameters obtained based on the integrated sample data set, and further improve the performance of the servo system.

[0065] Figure 3 It is a flowchart for collecting feedback data provided in another embodiment of this application. As Figure 3 shown, in the data collection method for servo parameter tuning provided in any of the above embodiments, in step S120, an instruction for one-key tuning is output to the servo system, and the feedback data of the servo system in response to the one-key tuning instruction is collected, which specifically includes the following steps: Step S301: In response to the test run instruction, an instruction for controlling the servo system to run based on the initial configuration parameters is output to the servo system, and the initial operation data is collected.

[0066] Step S302: After the servo system completes the initial operation, an instruction for one-key tuning is output to the servo system, and the adjusted and optimized configuration parameters during the one-key tuning process are collected; among them, the one-key tuning instruction is used to enable the servo system to call the preset one-key tuning algorithm for one-key tuning.

[0067] Step S303: After the one-key tuning is completed, an instruction for controlling the servo system to perform at least one complete operation again based on the adjusted and optimized configuration parameters is output to the servo system, and the adjusted and optimized operation data is collected.

[0068] In this embodiment, the implementation manners of steps S301 - S303 are the same as or similar to those of steps S201 - S203 in the above embodiment, and have the same technical effects. To avoid repetition, they will not be elaborated here.

[0069] Step S304: Send the operation data collected in real time to the externally connected interaction device, and monitor the system performance during the operation of the servo system through the interaction device in real time.

[0070] Step S305: Output a repeated tuning instruction to the servo system until it is monitored that the performance of the servo system is in a stable state; wherein, the repeated tuning instruction is used to control the servo system to repeat one-key tuning.

[0071] In this embodiment, during the process that the servo system responds to the one-key tuning instruction, calls the preset one-key tuning algorithm to perform parameter tuning, and runs again based on the configured parameters after one-key tuning, continuously collect the latest configured parameters and corresponding operation data of the servo system. At the same time, transmit the collected operation data to the externally connected interaction device, and monitor the system performance during the operation of the servo system through the interaction device. When it is monitored that the performance of the servo system is unstable or does not meet the requirements, output a repeated tuning instruction to the servo system. The servo system responds to the repeated tuning instruction and repeats the above steps S301 - S303 until it is monitored that the performance of the servo system is in a stable state, and no longer output a repeated tuning instruction to the servo system, ending the process of collecting feedback data.

[0072] Figure 4 It is a flowchart of a data collection method for servo parameter tuning provided by another embodiment of the present application. As Figure 4 shown, the data collection method for servo parameter tuning provided by this embodiment specifically includes the following steps: Step S410: After determining the connection with the servo system, obtain the initial configured parameters of the servo system.

[0073] Step S420: Output a one-key tuning instruction to the servo system, and collect the feedback data after the servo system responds to the one-key tuning instruction; wherein, the feedback data includes the configured parameters and operation data adjusted and optimized during the one-key tuning process.

[0074] Step S430: Integrate the initial configured parameters and the feedback data to obtain a sample data set for servo parameter tuning; wherein, the sample data set includes the initial configured parameters and feedback data of at least one servo system.

[0075] Step S440: Determine whether there is an Internet connection currently.

[0076] Step S450: After determining the connection with the Internet, in response to the online upload instruction, upload and store the sample data set to the specified location on the Internet.

[0077] In this embodiment, steps S410 - S430 are the same as or similar to steps S110 - S130 in the above embodiment and their specific implementation manners, and have the same technical effects. To avoid repetition, they will not be elaborated here.

[0078] In this embodiment, after integrating the feedback data obtained by one - key tuning based on the initial configuration parameters of the servo system and the self - parameters of the servo system and the empirical data manually input to obtain a sample data set with rich data, in order to facilitate the subsequent call of servo system parameter tuning in different scenarios, after integration, it will be determined whether it is currently connected to the Internet. After determining that a connection to the Internet is established, in response to an online upload instruction, the integrated sample data set is uploaded and stored at a specified location on the Internet, that is, the online storage of the sample data set is realized. For example, for users who have purchased an old - model servo system, they can obtain the updated sample data set through the online address provided by the merchant and perform servo tuning on their own servo system to obtain better configuration parameters and improve the system's performance.

[0079] In some embodiments, the online storage platform can be a cloud platform.

[0080] Figure 5 It is a flowchart of a data collection method for servo parameter tuning provided in another embodiment of the present application. As Figure 4 shown, the data collection method for servo parameter tuning provided in this embodiment, on the basis of any of the above embodiments, includes the following steps: Step S510: After determining the connection to the servo system, obtain the initial configuration parameters of the servo system.

[0081] Step S520: Output an one - key tuning instruction to the servo system and collect the feedback data of the servo system in response to the one - key tuning instruction; wherein, the feedback data includes the configuration parameters and operation data adjusted and optimized during the one - key tuning process.

[0082] Step S530: Integrate the initial configuration parameters and the feedback data to obtain a sample data set for servo parameter tuning; wherein, the sample data set includes the initial configuration parameters and feedback data of at least one servo system.

[0083] Step S540: Determine whether it is currently connected to the Internet.

[0084] Step S550: After determining that it is not connected to the Internet, determine whether it is connected to a local storage device.

[0085] Step S560: After determining the connection to the local storage device, in response to an offline transmission instruction, transmit the sample data set to a specified location on the local storage device.

[0086] In this embodiment, steps S510 - S540 are the same as or similar to steps S410 - S440 in the above embodiment and their specific implementation manners, and have the same technical effects. To avoid repetition, they will not be elaborated here.

[0087] In this embodiment, after the integration of the sample data collection set is completed, it is judged whether there is a connection to the Internet currently. In the case where the judgment result is that there is no connection established to the Internet, it is further judged whether there is a connection to the local storage device. When it is determined that there is a connection to the local storage device, in response to the offline transmission instruction, the integrated sample data collection set is transmitted to a specified location of the local storage device for storage, that is, the offline storage of the integrated sample data collection set is realized.

[0088] The above embodiment provides two storage methods, online and offline, for the finally integrated sample data collection set after the collection of sample data using the data collection method for servo parameter tuning, which can balance data security and subsequent efficient collaboration. Online storage provides scalability, remote collaboration, and automated backup capabilities, supporting multi-team collaboration and long-term archiving; offline storage ensures low-latency access, data sovereignty, and privacy protection, and is suitable for real-time debugging and sensitive data management.

[0089] In some embodiments, if necessary, the two methods can also be combined, along with an automated synchronization and permission encryption mechanism, to achieve a balance of data security, cost optimization, and flexible access, so as to adapt to industrial scenarios with strict requirements for real-time performance, privacy, and collaboration.

[0090] Figure 6 It is a schematic structural diagram of a servo parameter tuning device provided by an embodiment of the present application. As Figure 6 shown, the servo parameter tuning device 600 provided in this embodiment includes a first interface module 610, a second interface module 620, a memory 630, a processor 640, and an interactive display module 650.

[0091] In this embodiment, the first interface module 610 is used to connect to the servo system to be tuned. The second interface module 620 is used to connect to the Internet and / or the local storage device. The memory 630 is used to store computer execution programs or instructions. The processor 640 is used to execute the computer execution programs or instructions to implement the data collection method for servo parameter tuning as described in any of the above embodiments. The interactive display module 650 is used to monitor the state of the servo system during the data collection process, input corresponding interactive instructions according to the state of the servo system, and manually input empirical parameters matching the servo system.

[0092] The memory 630 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 630 can store an operating system and other application programs. When implementing the technical solutions provided by any of the above method embodiments through software or firmware, the relevant program codes are stored in the memory 630 and are called and executed by the processor 640 to perform the data collection method for servo parameter tuning in the embodiments of the present application.

[0093] The processor 640 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided by this embodiment.

[0094] The specific implementation manner of the servo parameter tuning device in this embodiment is basically the same as that of the specific embodiment of the data collection method for servo parameter tuning in any of the above embodiments, and will not be elaborated here. On the premise of meeting the requirements of this embodiment, other functional modules can also be set in the servo parameter tuning device to implement the data collection method for servo parameter tuning in the above embodiments.

[0095] Figure 7 It is a schematic structural diagram of a servo system provided by an embodiment of the present application. As Figure 7 shown, the servo system 700 provided by this embodiment at least includes a communication module 710, a data acquisition module 720, a parameter tuning module 730, a servo control module 740, and a servo motor module 750.

[0096] In this embodiment, the communication module 710 is used to establish a connection with the data collection device for servo parameter tuning described in the above embodiment, or establish a connection with a host computer that stores an application program corresponding to the data collection method for servo parameter tuning described in any of the above embodiments. The data acquisition module 720 is used to obtain a sample data set for servo parameter tuning from the data collection device in an offline manner, or obtain a sample data set for servo parameter tuning from the host computer in an online manner. The parameter tuning module 730 is used to call a parameter tuning algorithm to perform parameter tuning according to the obtained sample data set so that the system reaches the best performance. The servo control module 740 is used to output control instructions. The servo motor module 750 is used to operate according to the control instructions output by the servo control module 740.

[0097] In some embodiments, when the parameter tuning module 730 performs parameter tuning, it specifically includes inputting the sample data set into a pre-constructed AI training model, training the input sample data according to a preset algorithm, and calculating to obtain the optimal configuration parameters of the servo system; performing parameter tuning according to the optimal configuration parameters to enable the system to achieve the best performance.

[0098] In this embodiment, an AI training model is pre-constructed to calculate the optimal configuration parameters of the servo system. This model can receive the initial configuration parameters, the adjusted and optimized configuration parameters, and the operation data as input sample data, and use a preset algorithm, such as a machine learning or deep learning algorithm, to train the input sample data. During the training process, the model will learn the relationship between the input parameters and the output performance, and try to find the optimal parameter configuration, continuously adapting to different working conditions and load changes. Through the continuous iterative optimization of the AI model, the AI training model will finally output a set of optimal servo system configuration parameters. The finally calculated optimal configuration parameters and control instructions are sent to the servo system, and the servo system responds to the optimal tuning instruction and completes the parameter tuning according to the optimal configuration parameters, so that the servo system reaches the optimal or most adaptable performance.

[0099] This tuning process combines the initial configuration parameters, the data obtained from the self-parameter tuning of the servo system as sample data, and the empirical data, ensuring the accuracy and reliability of the tuning result; using AI technology to perform multiple iterative optimizations on the sample data to obtain better configuration parameters, realizing the automatic tuning of the servo parameters. The obtained configuration parameters also have higher precision, enabling the servo system to achieve the best performance. At the same time, the AI training model also improves the prediction accuracy and generalization ability during multiple trainings; compared with the prior art, the parameter tuning process improves the precision and efficiency, reducing the manual intervention and trial-and-error costs.

[0100] On the premise of meeting the requirements of this embodiment, other functional modules can also be set for the servo system, which are not specifically limited in this embodiment.

[0101] The embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it realizes each process of the above-mentioned arbitrary embodiment for data collection for servo parameter tuning, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0102] As a non-transitory computer-readable storage medium, the memory can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory optionally includes a memory remotely provided relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0103] Those skilled in the art can understand that all or part of the functions of the above methods can be implemented in a hardware manner or in a computer program manner. When all or part of the functions in the above embodiments are implemented in a computer program manner, the program can be stored in a computer-readable storage medium, and the storage medium may include: read-only memory, random access memory, magnetic disk, optical disk, hard disk, etc. The above functions are implemented by a computer executing the program. For example, the program is stored in the memory of the device, and when the processor executes the program in the memory, the above all or part of the functions can be implemented. In addition, when all or part of the functions in the above embodiments are implemented in a computer program manner, the program can also be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash drive, or a mobile hard disk, and saved to the memory of the local device by downloading or copying, or the system of the local device is updated in version. When the processor executes the program in the memory, all or part of the functions in the above embodiments can be implemented.

[0104] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can make several simple deductions, deformations, or substitutions without departing from the spirit of the present application and the scope protected by the claims. For those skilled in the art of the present invention, according to the idea of the present invention, it still belongs to the protection scope of the present application.

Claims

1. A data collection method for servo parameter tuning, characterized in that: include: After confirming the connection with the servo system, obtaining initial configuration parameters of the servo system; wherein the initial configuration parameters include at least one of the type and rated current of the motor in the servo system, the rated speed and load inertia ratio, the encoder resolution, the position loop parameters, the speed loop parameters, and the current loop parameters; outputting a one-button tuning instruction to the servo system, and collecting feedback data after the servo system responds to the one-button tuning instruction; wherein the feedback data includes configuration parameters and operating data adjusted and optimized during the one-button tuning process; and the operating data includes at least one of position-related parameters, speed-related parameters, current-related parameters, and system performance and status parameters; The initial configuration parameters and feedback data are integrated to obtain a sample data set for servo parameter tuning; the sample data set includes the initial configuration parameters and feedback data of at least one servo system.

2. The data collection method for servo parameter tuning according to claim 1, characterized in that The step of outputting a one-key tuning instruction to the servo system and collecting feedback data after the servo system responds to the one-key tuning instruction includes: In response to a test operation instruction, outputting an instruction to the servo system for controlling the servo system to operate based on the initial configuration parameters, and collecting initial operation data; After the servo system completes initial operation, a one-button tuning instruction is output to the servo system, and configuration parameters adjusted and optimized during the one-button tuning process are collected; the one-button tuning instruction is used to control the servo system to call a preset one-button tuning algorithm for one-button tuning; After the one-button tuning is completed, an instruction is output to the servo system to control the servo system to perform at least one complete operation again based on the adjusted and optimized configuration parameters, and the adjusted and optimized operation data are collected and integrated.

3. The data collection method for servo parameter tuning according to claim 2, wherein The collecting of feedback data after the servo system responds to the one-key tuning instruction further includes: Sending the real-time collected operating data to an externally connected interactive device, and monitoring the system performance of the servo system in real time during operation through the interactive device; Output a repeated tuning instruction to the servo system until the performance of the servo system is monitored to be in a stable state; the repeated tuning instruction is used to control the servo system to repeat one-button tuning.

4. The data collection method for servo parameter tuning according to claim 3, wherein The operation data also includes at least one of state parameters, performance parameters and alarm information in different states during the operation of the servo system.

5. The data collection method for servo parameter tuning according to any one of claims 1-4, characterized in that, Also includes: Manually input empirical parameters matching the servo system are collected as part of a sample data collection for servo parameter tuning.

6. The data collection method for servo parameter tuning according to claim 5, characterized in that, After obtaining the sample data set for servo parameter tuning, the method further includes: Determine whether the device is currently connected to the Internet; After determining that a connection is established with the Internet, in response to an online upload instruction, the sample data collection is uploaded and stored to a designated location on the Internet.

7. The data collection method for servo parameter tuning according to claim 6, characterized in that, After obtaining the sample data set for servo parameter tuning, the method further includes: After confirming that the device is not connected to the Internet, determine whether the device is connected to the local storage device; After determining to be connected to the local storage device, in response to an offline transmission instruction, the sample data collection is transmitted to a designated location of the local storage device.

8. A data collection device for servo parameter tuning, characterized in that, include: A first interface module, used for connecting to a servo system to be tuned; A second interface module, used for connecting to the Internet and / or a local storage device; Memory, used to store computer execution programs or instructions; a processor, configured to execute the computer-executable program or instruction to implement the data collection method for servo parameter tuning according to any one of claims 1 to 7; The interactive display module is used to monitor the status of the servo system during data collection, input corresponding interactive instructions according to the status of the servo system, and manually input empirical parameters that match the servo system.

9. A servo system, characterized in that, At least: a communication module for establishing a connection with the data collection device for servo parameter tuning according to claim 8, or establishing a connection with a host computer storing an application program for the data collection method for servo parameter tuning according to claims 1 to 7; A data acquisition module, configured to acquire a collection of sample data for servo parameter tuning from the servo parameter tuning device by offline transmission, or to acquire a collection of sample data for servo parameter tuning from the host computer by online download; A parameter tuning module is used to call a parameter tuning algorithm to perform parameter tuning based on the acquired sample data set so as to achieve optimal system performance; Servo control module, used for outputting control instructions; The servo motor module is used to operate according to the control instructions output by the servo control module.

10. The servo system according to claim 9, characterized in that, The parameter setting module is also used for: The sample data collection is input into a pre-built AI training model, the input sample data is trained according to a preset algorithm, and the optimal configuration parameters of the servo system are calculated; according to the optimal configuration parameters, the parameters are adjusted to enable the system to achieve optimal performance.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer-executable program or instruction, and when the computer-executable program or instruction is executed by a processor, it is used to implement the data collection method for servo parameter tuning according to any one of claims 1 to 7.

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