Automatic performance testing method and system for industrial robot

Abstract

The invention discloses an automatic performance test method for an industrial robot. The method comprises the following steps: S1, setting various test parameters; s2, the industrial robot runs to measure parameters; s3, the collected parameters are analyzed; s4, calculating the pose accuracy; s5, analyzing each parameter calculation; an automatic performance test system of an industrial robot comprises a control system; a detection module; a processing module; calculating and processing; calculating and analyzing the model; according to the method, the operation state of the industrial robot is detected, the pose coordinates and the attitude angle parameters of the industrial robot are obtained according to the multiple operation states, calculation analysis processing is carried out in combination with the set pose coordinates and the attitude angle parameters, and whether the operation state of the industrial robot is accurate or not is obtained; through calculation, processing and analysis of the data information, the accuracy of the data information can be improved, analysis and calculation of operation of the industrial robot are facilitated, and the accuracy of the data information is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robots, and in particular to an automated performance testing method and system for an industrial robot. Background Art

[0002] Industrial robots are multi-joint manipulators or multi-degree-of-freedom machine devices widely used in the industrial field. They have a certain degree of automation and can achieve various industrial processing and manufacturing functions by relying on their own power and control capabilities. Industrial robots are widely used in various industrial fields such as electronics, logistics, and chemicals.

[0003] With the continuous advancement of computer control technology, industrial robots will gradually be able to understand human language, and industrial robots can complete product assembly, which can exempt workers from complex operations. The welding robot system in industrial production can not only realize the automatic real-time tracking of space welds, but also realize the online adjustment of welding parameters and real-time control of weld quality, which can meet the urgent requirements of complex welding processes of technical products and their welding quality and efficiency. In addition, with the expansion of human exploration of space, industrial robots can also use their intelligence to successfully complete tasks in extreme environments such as space, deep water and nuclear environments.

[0004] Robotic process automation testing mainly includes several key steps: planning test cases, environment settings, test execution, verification of test results, monitoring and maintenance. Among these steps, test execution is the core link because it directly involves the operation of automation scripts and whether their interaction with business processes is correct.

[0005] Specifically, during the test execution phase, each step of the automated script in simulating real business operations should be closely monitored to ensure that each logical branch can work properly. At the same time, exceptions should be handled, including exception capture, logging, and error notification. In addition, attention should also be paid to the configuration of test data, as well as the time efficiency and resource consumption of the test process. Through meticulous test execution, the success rate of RPA deployment and the smoothness of business processes can be guaranteed.

[0006] The test of industrial robots mainly tests the precise movement of positions, so as to improve the stable operation of industrial robots and enable them to be easily and stably operated and used.

[0007] In the Chinese invention patent with application publication number CN112356071A, an automated performance test method for an industrial robot is disclosed. The reachable space domain of the robot is automatically generated by software, and then the position and side length of the space cube are determined, the position of the measured point is automatically generated, and then the robot performance test point program is automatically generated, wherein the performance test running program includes the function of interactive communication; the X, Y, Z coordinate values ​​and attitude angles Rx, Ry, Rz of the robot end are completely collected by means of Leica's laser tracker and automated tracking control detector; the performance results are automatically and accurately calculated by the host computer software, and finally a total of 14 performance test reports of the above industrial robots are output. The present invention has the advantages of high precision and strong adaptability, and industrial robots of various structures and various DH parameter values ​​can be subjected to automated performance testing.

[0008] However, in combination with the existing technology and the above application, there are still some problems in the existing technology, such as the inability to process the collected data signals, the inconvenience in calculating and processing the posture coordinates and posture angle parameters of the industrial robot, and the inconvenience in accurately determining whether the operating status of the industrial robot is accurate.

[0009] To this end, the present invention provides an automated performance testing method and system for an industrial robot. Summary of the invention

[0010] 1. Technical issues to be resolved

[0011] In view of the deficiencies in the prior art, the present invention provides an automated performance testing method and system for an industrial robot, which detects the operating status of the industrial robot and obtains the posture coordinates and attitude angle parameters of the industrial robot based on multiple operating statuses, and performs calculation and analysis based on the set posture coordinates and attitude angle parameters to determine whether the operating status of the industrial robot is accurate, thereby solving the technical problems recorded in the background technology.

[0012] (II) Technical solution

[0013] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0014] An automated performance testing method for an industrial robot comprises the following steps:

[0015] S1. Set the test parameters: When testing the industrial robot, first set the parameters to facilitate calculation and comparison when measuring the parameters later. The set parameters include the three-axis position parameters and the three-axis attitude angles;

[0016] The three-axis position parameters are x c ,y c 、zc is the command pose coordinate, the attitude angle parameter a of the three axes c , b c 、c c is the attitude angle of the command pose;

[0017] S2. Industrial robot operation measurement parameters: Control the industrial robot to operate, so that the industrial robot moves to a suitable position, and measure the robot's three-axis movement parameters through a laser rangefinder. The three-axis parameters obtained are the x, y, and z position coordinates, and the three-axis attitude angle parameters a, b, and c are obtained;

[0018] S3, analyzing the collected parameters: filtering the collected data information to improve the accuracy of the data information, and screening abnormal data to remove abnormal data in the data information, and normalizing the data information so that the data information is mapped within [0,1];

[0019] S4, posture accuracy calculation: calculate and analyze the collected posture coordinates and posture angle parameters and the set posture coordinates and posture angles;

[0020] Calculate the X-axis pose coordinate data based on the collected continuous detection data:

[0021] Calculate the Y-axis pose coordinate data:

[0022] Calculate the Z-axis pose coordinate data:

[0023] Deviation pose coordinate data of X axis:

[0024] Deviation pose coordinate data of the Y axis:

[0025] Deviation pose coordinate data of Z axis:

[0026] Then the position calculation of the three-axis pose coordinate deviation is:

[0027] Calculate the X-axis attitude angle data based on the collected continuous detection data:

[0028] Calculate the Y-axis attitude angle data:

[0029] Calculate the Z-axis attitude angle data:

[0030] Deviation attitude angle data of X axis:

[0031] Deviation position attitude angle data of Y axis:

[0032] Z-axis deviation attitude angle data:

[0033] Then the position calculation of the three-axis attitude angle deviation is:

[0034] S5. Analyze and calculate various parameters: Calculate and analyze by the following formula:

[0035] G=w1Q1+w2Q2+…+w n Q n =W T Q+b,

[0036] Where Qn represents the various detection calculations of the industrial robot, G is obtained by the LASSO linear regression model, and the value range is [0, 1]. That is, G represents the operation accuracy of the industrial robot. When the output value is 0, it means that the industrial robot operates inaccurately. When the output value is 1, it means that the industrial robot operates accurately. b is the operation deviation, and the set value is 0.05.

[0037] Furthermore, the test industrial robot is fully assembled and can be fully operated, and the necessary leveling operations, adjustment steps and functional tests should be successfully completed; except for the drift test of posture characteristics, which should be started from a cold state, the robot should be properly preheated before the rest of the tests. If the robot has equipment used by the user that may affect the measured characteristics, or if the equipment can only record the characteristics with special functions, the status in the test must be described in the test report and should remain unchanged in each test.

[0038] Furthermore, the test environment conditions for testing the industrial robot include temperature, relative humidity, electromagnetic field and electrostatic field, radio frequency interference, air pollution and altitude limit;

[0039] The test environment temperature should be 25℃, and the test temperature should be kept within ±2℃. In order to make the robot and measuring instruments in a thermally stable state before the test, they need to be placed in the test environment for a long enough time, and the test environment should be kept for 24 hours to prevent ventilation and external heat radiation.

[0040] The relative humidity is 25%-60%, and interference from electromagnetic and electrostatic fields, radio frequency interference, and air pollution is strictly prohibited. The altitude limit is set below 1000m.

[0041] Furthermore, the industrial robot in S2 collects various operating parameters of the industrial robot through continuous operation measurement, and stores and records each time the parameters are collected, and records the parameters in a storage module, and caches the data information collected first. After multiple collections, the collected data information is filtered, and the filtered data information is stored and calculated.

[0042] Furthermore, the analysis of the parameters in S3 includes acquisition processing, analog-to-digital conversion, filtering processing and amplification processing of the collected parameters;

[0043] The acquisition processing is used to receive detection data information from various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss.

[0044] Furthermore, the filtering process is calculated using a mean filter, and the calculation formula of the mean filter is as follows:

[0045]

[0046] in, Identifies the output data set after mean filtering, m represents the size of the window, v(n) j Represents the jth data information in the input data set;

[0047] The mean filter specifies a window with an odd length, uses the average value of all the data in the window to replace the value in the middle, and then translates the window with a step size of 1. The above operation is repeated until it slides to the end of the time series data.

[0048] Furthermore, the abnormal data screening adopts a clustering algorithm for calculation processing, and the calculation formula of the clustering algorithm is as follows:

[0049] Divide the collected data into z clusters.

[0050]

[0051] Among them, F is the outlier factor, D is the data information set by the robot, |z j | is the number of samples in the jth cluster group, d(p,z j ) is the distance between sample p and the jth cluster center, z jis the jth cluster center. Data information far away from the cluster center is judged as abnormal data information and is removed.

[0052] Furthermore, after the abnormal data information is eliminated, the abnormal data screening supplements the data information of the eliminated positions through an averaging algorithm;

[0053] Assume that the data to be removed is X j , then the data information on both sides are X j-1 and X j+1 , then the average value is calculated as follows:

[0054]

[0055] in, That is, it is the average value that needs to be inserted into the position of the eliminated data, and is obtained by averaging the data on both sides of the eliminated data.

[0056] Furthermore, the normalization process performs linear normalization on the posture coordinates and posture angle parameters, and maps the corresponding data values ​​to the interval [0,1];

[0057] That is, the calculation formula is as follows:

[0058]

[0059] Where g is the result of weight normalization calculated by Gaussian function, and the output range is between 0 and 1. G is the weight calculated by Gaussian function. If the data output weight is between 0 and 1, it means that the data is normal. If the data output weight is outside 0-1, it means that the data is abnormal. min is the minimum value among the weights calculated by the Gaussian function, G max It is the maximum value among the weights calculated by the Gaussian function. Through normalization, the data information is reduced in dimension and abnormal data information can be detected.

[0060] An automated performance testing system for an industrial robot, comprising:

[0061] The control system is used to control the detection system of the industrial robot and to control the operation of the industrial robot so that the industrial robot can operate stably and the detection system can collect various detection information in real time;

[0062] The detection module is used to detect the operating position of the industrial robot, collect the position coordinates and attitude angle parameters, and transmit the collected data information to facilitate the performance measurement of the industrial robot;

[0063] The processing module is used to process various data information of the industrial robot, including acquisition processing, analog-to-digital conversion, filtering processing and amplification processing; the acquisition processing is used to receive detection data information of various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss;

[0064] Calculation and processing: Calculation and processing of the collected data information, including abnormal detection, removal of abnormal data, replacement of abnormal data and normalization of the data information, and calculation of the deviation of the posture coordinates and attitude angle parameters based on the processed and analyzed data information, so as to facilitate the calculation and analysis of the data information;

[0065] Model calculation analysis: The LASSO linear regression model is used to calculate various detection calculations of the industrial robot. When the output value is 0, it means that the industrial robot is not running accurately. When the output value is 1, it means that the industrial robot is running accurately.

[0066] (III) Beneficial effects

[0067] The present invention provides an automated performance testing method and system for an industrial robot, which has the following beneficial effects:

[0068] The present invention detects the running state of the industrial robot, obtains the posture coordinates and attitude angle parameters of the industrial robot according to multiple running states, and performs calculation and analysis processing in combination with the set posture coordinates and attitude angle parameters to obtain whether the running state of the industrial robot is accurate;

[0069] That is, by setting the three-axis position parameters to x c ,y c 、z c , the attitude angle parameter a of the three axes c , b c 、c c , and the three-axis parameters obtained by the laser rangefinder are the posture coordinates of x, y, and z, and the three-axis posture angle parameters a, b, and c are obtained for calculation and analysis. Before the analysis and processing, the data information is analyzed and processed to improve the accuracy of the data information, and the collected posture coordinates and posture angle parameters are calculated and analyzed with the set posture coordinates and posture angles, and then the operation of the industrial robot is calculated based on the analysis of various parameters.

[0070] In addition, the calculation, processing and analysis of data information can improve the accuracy of data information, facilitate the analysis and calculation of the operation of industrial robots, and improve the accuracy of data information. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a schematic diagram of the steps of the automated performance testing method of the industrial robot in the present invention;

[0072] Figure 2 It is a structural schematic diagram of the automated performance testing system for an industrial robot in the present invention. DETAILED DESCRIPTION

[0073] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0074] See also Figure 1 The present invention provides an automated performance testing method for an industrial robot, comprising the following steps:

[0075] S1. Set the test parameters: When testing the industrial robot, first set the parameters to facilitate calculation and comparison when measuring the parameters later. The set parameters include the three-axis position parameters and the three-axis attitude angles;

[0076] The three-axis position parameters are x c ,y c 、z c is the command pose coordinate, the attitude angle parameter a of the three axes c , b c 、c c is the attitude angle of the command pose;

[0077] S2. Industrial robot operation measurement parameters: Control the industrial robot to operate, so that the industrial robot moves to a suitable position, and measure the robot's three-axis movement parameters through a laser rangefinder. The three-axis parameters obtained are the x, y, and z position coordinates, and the three-axis attitude angle parameters a, b, and c are obtained;

[0078] S3, analyzing the collected parameters: filtering the collected data information to improve the accuracy of the data information, and screening abnormal data to remove abnormal data in the data information, and normalizing the data information so that the data information is mapped within [0,1];

[0079] S4, posture accuracy calculation: calculate and analyze the collected posture coordinates and posture angle parameters and the set posture coordinates and posture angles;

[0080] Calculate the X-axis pose coordinate data based on the collected continuous detection data:

[0081] Calculate the Y-axis pose coordinate data:

[0082] Calculate the Z-axis pose coordinate data:

[0083] Deviation pose coordinate data of X axis:

[0084] Deviation pose coordinate data of the Y axis:

[0085] Deviation pose coordinate data of Z axis:

[0086] Then the position calculation of the three-axis pose coordinate deviation is:

[0087] Calculate the X-axis attitude angle data based on the collected continuous detection data:

[0088] Calculate the Y-axis attitude angle data:

[0089] Calculate the Z-axis attitude angle data:

[0090] Deviation attitude angle data of X axis:

[0091] Deviation position attitude angle data of Y axis:

[0092] Z-axis deviation attitude angle data:

[0093] Then the position calculation of the three-axis attitude angle deviation is:

[0094] S5. Analyze and calculate various parameters: Calculate and analyze by the following formula:

[0095] G=w1Q1+w2Q2+…+w n Q n =W T Q+b,

[0096] Where Qn represents the various detection calculations of the industrial robot, G is obtained by the LASSO linear regression model, and the value range is [0, 1]. That is, G represents the operation accuracy of the industrial robot. When the output value is 0, it means that the industrial robot operates inaccurately. When the output value is 1, it means that the industrial robot operates accurately. b is the operation deviation, and the set value is 0.05.

[0097] In order to improve the operating stability of the industrial robot and maintain the stability of the operating state of the industrial robot during continuous monitoring, in this embodiment, preferably, the test industrial robot is assembled and can be fully operated, and the necessary leveling operations, adjustment steps and functional tests should be successfully completed; except that the drift test of posture characteristics should be started from a cold state, the robot should be properly preheated before the remaining tests. If the robot has a device used by the user that may affect the measured characteristics, or if the characteristics can only be recorded using special functions, the status in the test must be described in the test report and should remain unchanged in each test.

[0098] In order to prevent environmental interference from affecting the operating state of the industrial robot, in this embodiment, preferably, the test environment conditions for testing the industrial robot include temperature, relative humidity, electromagnetic field and electrostatic field, radio frequency interference, air pollution and altitude limit;

[0099] The test environment temperature should be 25℃, and the test temperature should be kept within ±2℃. In order to make the robot and measuring instruments in a thermally stable state before the test, they need to be placed in the test environment for a long enough time, and the test environment should be kept for 24 hours to prevent ventilation and external heat radiation.

[0100] The relative humidity is 25%-60%, and interference from electromagnetic and electrostatic fields, radio frequency interference, and air pollution is strictly prohibited. The altitude limit is set below 1000m.

[0101] In order to realize continuous detection of industrial robots and continuous collection of various data information, in this embodiment, preferably, the industrial robot in S2 collects various operating parameters of the industrial robot through continuous operation measurement, and stores and records each time the parameters are collected, and records the parameters in a storage module, and caches the data information collected first, and after multiple collections, filters the collected data information, and stores and calculates the filtered data information.

[0102] In order to analyze and process the collected data, improve the accuracy of the data information, and facilitate subsequent calculation and processing, in this embodiment, preferably, the analysis of the parameters in S3 includes acquisition processing, analog-to-digital conversion, filtering processing, and amplification processing of the collected parameters;

[0103] The acquisition processing is used to receive detection data information from various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss.

[0104] In order to filter out the noise in the data information and improve the accuracy of the data information, in this embodiment, preferably, the filtering process uses a mean filter for calculation, and the calculation formula of the mean filter is as follows:

[0105]

[0106] in, Identifies the output data set after mean filtering, m represents the size of the window, v(n) j Represents the jth data information in the input data set;

[0107] The mean filter specifies a window with an odd length, uses the average value of all the data in the window to replace the value in the middle, and then translates the window with a step size of 1. The above operation is repeated until it slides to the end of the time series data.

[0108] In order to filter out abnormal data in the data information and improve the accuracy of the data, in this embodiment, preferably, the abnormal data screening adopts a clustering algorithm for calculation processing, and the calculation formula of the clustering algorithm is as follows:

[0109] Divide the collected data into z clusters.

[0110]

[0111] Among them, F is the outlier factor, D is the data information set by the robot, |z j | is the number of samples in the jth cluster group, d(p,z j ) is the distance between sample p and the jth cluster center, z j is the jth cluster center. Data information far away from the cluster center is judged as abnormal data information and is removed.

[0112] In order to compensate for the removed abnormal data information and maintain the integrity of the data, in this embodiment, preferably, after removing the abnormal data information, the abnormal data screening supplements the data information of the removed position by an averaging algorithm;

[0113] Assume that the data to be removed is X j , then the data information on both sides are X j-1 and X j+1 , then the average value is calculated as follows:

[0114]

[0115] in, That is, it is the average value that needs to be inserted into the position of the eliminated data, and is obtained by averaging the data on both sides of the eliminated data.

[0116] In order to reduce the operating pressure of data information and improve the efficiency of calculation, the data information is normalized. In this embodiment, preferably, the normalization process performs linear normalization on the posture coordinates and posture angle parameters, and maps the corresponding data values ​​to the interval [0,1];

[0117] That is, the calculation formula is as follows:

[0118]

[0119] Where g is the result of weight normalization calculated by Gaussian function, and the output range is between 0 and 1. G is the weight calculated by Gaussian function. If the data output weight is between 0 and 1, it means that the data is normal. If the data output weight is outside 0-1, it means that the data is abnormal. min is the minimum value among the weights calculated by the Gaussian function, G max It is the maximum value among the weights calculated by the Gaussian function. Through normalization, the data information is reduced in dimension and abnormal data information can be detected.

[0120] refer to Figure 2 , an automated performance testing system for an industrial robot, comprising:

[0121] The control system is used to control the detection system of the industrial robot and to control the operation of the industrial robot so that the industrial robot can operate stably and the detection system can collect various detection information in real time;

[0122] The detection module is used to detect the operating position of the industrial robot, collect the position coordinates and attitude angle parameters, and transmit the collected data information to facilitate the performance measurement of the industrial robot;

[0123] The processing module is used to process various data information of the industrial robot, including acquisition processing, analog-to-digital conversion, filtering processing and amplification processing; the acquisition processing is used to receive detection data information of various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss;

[0124] Calculation and processing: Calculation and processing of the collected data information, including abnormal detection, removal of abnormal data, replacement of abnormal data and normalization of the data information, and calculation of the deviation of the posture coordinates and attitude angle parameters based on the processed and analyzed data information, so as to facilitate the calculation and analysis of the data information;

[0125] Model calculation analysis: The LASSO linear regression model is used to calculate various detection calculations of the industrial robot. When the output value is 0, it means that the industrial robot is not running accurately. When the output value is 1, it means that the industrial robot is running accurately.

[0126] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0127] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0128] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0129] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only some logical function divisions. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0130] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0132] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0133] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0134] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. An automated performance testing method for an industrial robot, characterized in that: The following steps are included: S1. Set the test parameters: When testing the industrial robot, first set the parameters to facilitate calculation and comparison when measuring the parameters later. The set parameters include the three-axis position parameters and the three-axis attitude angles; The three-axis position parameters are x c ,y c 、z c is the command pose coordinate, the attitude angle parameter a of the three axes c 、b c 、c c is the attitude angle of the command pose; S2. Industrial robot operation measurement parameters: Control the industrial robot to operate, so that the industrial robot moves to a suitable position, and measure the robot's three-axis movement parameters through a laser rangefinder. The three-axis parameters obtained are the x, y, and z position coordinates, and the three-axis attitude angle parameters a, b, and c are obtained; S3, analyzing the collected parameters: filtering the collected data information to improve the accuracy of the data information, and screening abnormal data to remove abnormal data in the data information, and normalizing the data information so that the data information is mapped within [0,1]; S4, posture accuracy calculation: calculate and analyze the collected posture coordinates and posture angle parameters and the set posture coordinates and posture angles; Calculate the X-axis pose coordinate data based on the collected continuous detection data: Calculate the Y-axis pose coordinate data: Calculate the Z-axis pose coordinate data: Deviation pose coordinate data of X axis: Deviation pose coordinate data of the Y axis: Deviation pose coordinate data of Z axis: Then the position calculation of the three-axis pose coordinate deviation is: Calculate the X-axis attitude angle data based on the collected continuous detection data: Calculate the Y-axis attitude angle data: Calculate the Z-axis attitude angle data: Deviation attitude angle data of X axis: Deviation position attitude angle data of Y axis: Z-axis deviation attitude angle data: Then the position calculation of the three-axis attitude angle deviation is: S5. Analyze and calculate various parameters: Calculate and analyze using the following formula: G=w1Q1+w2Q2+…+w n Q n =W T Q+b, Where Qn represents the various detection calculations of the industrial robot, G is obtained by the LASSO linear regression model, and the value range is [0, 1]. That is, G represents the operation accuracy of the industrial robot. When the output value is 0, it means that the industrial robot operates inaccurately. When the output value is 1, it means that the industrial robot operates accurately. b is the operation deviation, and the set value is 0.

05.

2. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The test industrial robot is fully assembled and fully operational, and the necessary leveling operations, adjustment steps and functional tests are all completed satisfactorily. Except for the drift test of posture characteristics, which should be started from the cold state, the robot should be properly preheated before the rest of the tests. If the robot has equipment used by the user that may affect the measured characteristics, or if the equipment can only record the characteristics with special functions, the status during the test must be described in the test report and should remain unchanged in each test.

3. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The test environment conditions for testing the industrial robot include temperature, relative humidity, electromagnetic field and electrostatic field, radio frequency interference, air pollution and altitude limit; The test environment temperature should be 25℃, and the test temperature should be kept within ±2℃. In order to make the robot and measuring instruments in a thermally stable state before the test, they need to be placed in the test environment for a long enough time, and the test environment should be kept for 24 hours to prevent ventilation and external heat radiation. The relative humidity is 25%-60%, and interference from electromagnetic and electrostatic fields, radio frequency interference, and air pollution is strictly prohibited. The altitude limit is set below 1000m.

4. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The industrial robot in S2 collects various operating parameters of the industrial robot through continuous operation measurement, and stores and records each time each parameter is collected, and records each parameter in a storage module, and caches the first collected data information. After multiple collections, the collected data information is filtered, and the filtered data information is stored and calculated.

5. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The analysis of the parameters in S3 includes acquisition processing, analog-to-digital conversion, filtering processing and amplification processing of the collected parameters; The acquisition processing is used to receive detection data information from various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss.

6. The method for automated performance testing of an industrial robot according to claim 5, characterized in that: The filtering process uses a mean filter for calculation, and the calculation formula of the mean filter is as follows: Among them, v(n) indicates the output data set after mean filtering, m represents the size of the window, and v(n) j Represents the jth data information in the input data set; The mean filter specifies a window with an odd length, uses the average value of all the data in the window to replace the value in the middle, and then translates the window with a step size of 1. The above operation is repeated until it slides to the end of the time series data.

7. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The abnormal data screening adopts clustering algorithm for calculation processing, and the calculation formula of the clustering algorithm is as follows: Divide the collected data into z clusters. Among them, F is the outlier factor, D is the data information set by the robot, |z j | is the number of samples in the jth cluster group, d(p,z j ) is the distance between sample p and the jth cluster center, z j is the jth cluster center. Data information far away from the cluster center is judged as abnormal data information and is removed.

8. The method for automated performance testing of an industrial robot according to claim 7, characterized in that: After the abnormal data information is eliminated, the abnormal data screening supplements the data information of the eliminated positions through an averaging algorithm; Assume that the data to be removed is X j , then the data information on both sides are X j-1 and X j+1 , then the average value is calculated as follows: in, That is, it is the average value that needs to be inserted into the position of the eliminated data, and is obtained by averaging the data on both sides of the eliminated data.

9. The method for automated performance testing of an industrial robot according to claim 1, characterized in that: The normalization process performs linear normalization on the posture coordinates and posture angle parameters, and maps the corresponding data values ​​to the interval [0,1]; That is, the calculation formula is as follows: Where g is the result of weight normalization calculated by Gaussian function, and the output range is between 0 and 1. G is the weight calculated by Gaussian function. If the data output weight is between 0 and 1, it means that the data is normal. If the data output weight is outside 0-1, it means that the data is abnormal. min is the minimum value among the weights calculated by the Gaussian function, G max It is the maximum value among the weights calculated by the Gaussian function. Through normalization, the data information is reduced in dimension and abnormal data information can be detected.

10. An automated performance testing system for an industrial robot, characterized in that: Included are: The control system is used to control the detection system of the industrial robot and to control the operation of the industrial robot so that the industrial robot can operate stably and the detection system can collect various detection information in real time; The detection module is used to detect the operating position of the industrial robot, collect the position coordinates and attitude angle parameters, and transmit the collected data information to facilitate the performance measurement of the industrial robot; The processing module is used to process various data information of the industrial robot, including acquisition processing, analog-to-digital conversion, filtering processing and amplification processing; the acquisition processing is used to receive detection data information of various instruments, the analog-to-digital conversion is used to perform AD conversion processing on the received data to facilitate subsequent calculation processing of the data information, the filtering processing is used to filter the collected data to eliminate noise in the collected data information, and the amplification processing is used to amplify the collected data information to prevent data information loss; Calculation and processing: Calculation and processing of the collected data information, including abnormal detection, removal of abnormal data, replacement of abnormal data and normalization of the data information, and calculation of the deviation of the posture coordinates and attitude angle parameters based on the processed and analyzed data information, so as to facilitate the calculation and analysis of the data information; Model calculation analysis: The LASSO linear regression model is used to calculate various detection calculations of the industrial robot. When the output value is 0, it means that the industrial robot is not running accurately. When the output value is 1, it means that the industrial robot is running accurately.

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