Multi-dimensional dynamic motor test system

Abstract

The invention discloses a multi-dimensional dynamic motor test system, which relates to the technical field of motor test, and comprises the following steps: establishing a motor digital model, and carrying out simulation motor test to obtain motor simulation parameters; inputting the motor simulation parameters into a pre-constructed parameter error analysis model for data analysis to obtain a simulation operation error coefficient; performing actual testing on the motor to obtain actual operation parameters of the motor, and inputting the actual operation parameters into a pre-constructed parameter error analysis model to obtain an actual operation error coefficient; performing error correction on the motor simulation parameter and the motor actual operation parameter according to the simulation operation error coefficient and the actual operation error coefficient to obtain a correction calculation result; and performing motor performance verification according to the correction calculation result, and outputting a motor test result. The technical problems that the motor performance cannot be comprehensively and accurately evaluated and the test result is greatly interfered by environmental factors in the prior art are solved, and the technical effect of comprehensively evaluating the motor performance is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of motor testing, and in particular to a multi-dimensional dynamic motor testing system. Background Art

[0002] With the rapid development of industrial automation and intelligent manufacturing, motors, as core drive components, have been widely used in industrial equipment, transportation, consumer electronics and other fields. However, with the continuous improvement of equipment operation requirements and the complexity of process flows, motor performance testing and evaluation are also facing increasing challenges. Traditional motor testing methods often rely on a single simulation test or actual test, which has problems such as incomplete test data, insufficient accuracy, and sensitivity to environmental factors. It is difficult to meet the needs of modern industry for efficient, accurate and reliable testing. Summary of the invention

[0003] The present application provides a multi-dimensional dynamic motor testing system, which is used to solve the technical problems that the prior art cannot comprehensively and accurately evaluate the motor performance and the test results are greatly affected by environmental factors.

[0004] In view of the above problems, the present application provides a multi-dimensional dynamic motor testing system.

[0005] The present application provides a multi-dimensional dynamic motor testing system, the system comprising:

[0006] A digital model building module, the digital model building module acquires motor operating parameters and establishes a motor digital model; a simulation test module, the simulation test module performs a simulated motor test based on the motor digital model to obtain motor simulation parameters; a first error coefficient acquisition module, the first error coefficient acquisition module inputs the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain simulated operation error coefficients; a second error coefficient acquisition module, the second error coefficient acquisition module performs an actual test on the motor to obtain the actual motor operating parameters, and inputs the actual motor operating parameters into a pre-built parameter error analysis model to obtain the actual operation error coefficients; an error correction module, the error correction module performs error correction on the motor simulation parameters and the actual motor operating parameters according to the simulated operation error coefficients and the actual operation error coefficients to obtain correction calculation results, the correction calculation results including motor simulation correction parameters and motor actual correction parameters; a motor test result acquisition module, the motor test result acquisition module performs motor performance verification according to the correction calculation results and outputs motor test results.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The present application obtains motor operating parameters and establishes a motor digital model; based on the motor digital model, simulates the motor test to obtain motor simulation parameters; inputs the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain a simulated operation error coefficient; performs actual testing on the motor to obtain the motor actual operating parameters, inputs the motor actual operating parameters into a pre-built parameter error analysis model to obtain an actual operation error coefficient; performs error correction on the motor simulation parameters and the motor actual operating parameters according to the simulated operation error coefficient and the actual operation error coefficient to obtain a correction calculation result, the correction calculation result includes the motor simulation correction parameters and the motor actual correction parameters; performs motor performance verification according to the correction calculation result, and outputs a motor test result. The present invention solves the technical problem that the prior art cannot comprehensively and accurately evaluate motor performance and the test results are greatly affected by environmental factors. The present invention obtains motor operating parameters to establish a digital model, combines the simulated test and actual test data into the error analysis model, generates error correction results, optimizes the simulation and actual parameters through error correction, and performs performance verification, and finally outputs accurate motor test results, achieving the technical effect of comprehensive evaluation of motor performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 A schematic diagram of the structure of a multi-dimensional dynamic motor testing system provided in an embodiment of the present application;

[0011] Figure 2 A flowchart of execution steps of a motor test result acquisition module in a multi-dimensional dynamic motor test system provided in an embodiment of the present application.

[0012] Explanation of the reference numerals: digital model building module 11 , simulation test module 12 , first error coefficient acquisition module 13 , second error coefficient acquisition module 14 , error correction module 15 , motor test result acquisition module 16 . DETAILED DESCRIPTION

[0013] The present application provides a multi-dimensional dynamic motor testing system to solve the technical problems that the prior art cannot comprehensively and accurately evaluate the motor performance and the test results are greatly interfered by environmental factors. A digital model is established by obtaining the motor operating parameters, and the error analysis model is input by combining the simulation test and actual test data to generate error correction results. After optimizing the simulation and actual parameters through error correction, performance verification is performed, and finally accurate motor test results are output, thereby achieving the technical effect of comprehensively evaluating the motor performance.

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] It should be noted that any variations of the terms "include" and "have" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0016] Examples, such as Figure 1 As shown, an embodiment of the present application provides a multi-dimensional dynamic motor testing system, the system comprising:

[0017] The digital model building module 11 obtains motor operating parameters and builds a motor digital model.

[0018] In the embodiments of the present application, the acquisition of motor operating parameters is the basis for building a digital model. Operating parameters refer to key values ​​that reflect the working state of the motor, including but not limited to speed, torque, current, voltage, and temperature. These parameters are usually collected in real time by a multidimensional sensor array installed on the motor. The sensor can convert mechanical and electrical signals into digital signals, providing raw data support for subsequent processing.

[0019] Next, the digital model building module preprocesses the collected operating parameters. Preprocessing refers to cleaning, noise reduction and standardization of raw data to improve data quality and consistency. For example, filtering algorithms are used to remove noise signals, and normalization methods are used to map parameter values ​​to a uniform numerical range. After preprocessing, the data is more suitable for model building.

[0020] Then, the preprocessed data is used for operation fitting, that is, the actual operation behavior of the motor is fitted through a mathematical model. Operation fitting is an approximate calculation method based on the relationship between parameters. Its purpose is to describe the dynamic characteristics of the motor operation through mathematical formulas or data-driven algorithms (such as the least squares method). For example, the load characteristic curve of the motor is fitted based on the relationship between speed and torque; the thermal balance model is fitted based on current and temperature data.

[0021] After the running fitting is completed, a motor digital model is established based on the fitting results.

[0022] Furthermore, in the system provided in the embodiment of the application, the digital model building module 11 is also used for:

[0023] Data collection is performed on the motor to be tested to obtain the motor operating parameters; operation fitting is performed based on the motor operating parameters to obtain the motor digital model.

[0024] In an embodiment of the present application, the operating parameters of the motor to be tested are first obtained through a data acquisition module. Operating parameters refer to dynamic performance indicators exhibited during the operation of the motor, usually including speed, torque, current, voltage, vibration, temperature, etc. These parameters are collected in real time by sensors installed on the motor (such as torque sensors, temperature sensors, current transformers, etc.). The sensor converts the physical signal into a digital signal and transmits it to the processing system through a data acquisition device. The goal of data acquisition is to ensure the high accuracy and stability of the operating parameters and provide real and reliable data for subsequent analysis.

[0025] Then, the collected operating parameters are preprocessed. The purpose of data preprocessing is to clean and standardize the collected data to eliminate the influence of external interference on the operating parameters. Specifically, high-frequency noise is removed by low-pass filtering. Low-pass filtering can retain the main low-frequency components in the signal and eliminate high-frequency fluctuations caused by environmental vibration or electronic interference, making the data smoother and physically meaningful.

[0026] After the preprocessing is completed, the operation fitting stage begins. Operation fitting is a process of modeling the relationship between the motor's operating parameters based on mathematical methods. Its purpose is to generate a mathematical model that can describe the dynamic characteristics of the motor. Specifically, the parameters are fitted through the polynomial regression method to establish the relationship curve between key parameters such as speed and torque, temperature and current.

[0027] Finally, the motor digital model is constructed based on the results of the operation fitting. The digital model reflects the performance characteristics of the motor under different operating conditions through a collection of mathematical expressions obtained through fitting. For example, the digital model can be used to predict the operating state of the motor under specific load or environmental conditions, and provide a basis for subsequent testing and verification.

[0028] The simulation test module 12 performs a simulation motor test based on the motor digital model to obtain motor simulation parameters.

[0029] In the embodiment of the present application, the simulation test module 12 simulates the performance of the motor under different operating conditions by setting test conditions based on the motor digital model. After loading the motor digital model, the simulation calculation is started to generate motor simulation parameters corresponding to the operating conditions, including speed, torque, power, temperature and vibration.

[0030] Furthermore, in the system provided by the embodiment of the application, the simulation test module 12 is also used for:

[0031] Based on the motor digital model, simulation calculation is performed to obtain the motor simulation parameters; wherein the motor simulation parameters include rotation speed, torque, power, temperature, and vibration.

[0032] In an embodiment of the present application, the digital model of the motor is loaded first. The digital model of the motor integrates the relationship between operating parameters such as speed, torque, current, etc., and can reflect the dynamic behavior of the motor under different working conditions. After loading the model, the simulation environment is initialized to simulate the operating state of the motor. Next, the simulation conditions are set by technical experts. This step defines the input variables of the simulation calculation, such as input voltage, ambient temperature, load conditions, etc. The setting of these conditions needs to fit the actual usage scenario to ensure the credibility of the simulation results. For example, by setting the voltage range, the performance of the motor under different power supply conditions can be evaluated.

[0033] Then, start the simulation calculation, that is, based on the motor digital model and input conditions, use dynamic simulation tools (such as MATLAB Simulink) to simulate the operation process of the motor. During the simulation process, the dynamic response of the motor at different time points or load conditions is calculated to generate a series of output parameters. After the simulation is completed, the generated motor simulation parameters are extracted and sorted. These parameters include speed, torque, power, temperature, and vibration. Among them, the speed reflects the speed performance of the motor under load conditions; the torque represents the output capacity of the motor; the power measures the energy output of the motor under different electrical conditions; the temperature evaluates the thermal stability of the motor; and the vibration reflects the mechanical operation smoothness of the motor.

[0034] Finally, the sorted motor simulation parameters are output, saved in digital form and transmitted to other modules of the system for subsequent error analysis and performance verification.

[0035] The first error coefficient acquisition module 13 inputs the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain a simulation operation error coefficient.

[0036] In the embodiment of the present application, the first error coefficient acquisition module receives the motor simulation parameters, and then calls the parameter error analysis model to perform error calculation. The model is trained based on a large amount of historical sample data. The parameter error analysis model is used to analyze the parameter error analysis model to obtain the simulation operation error coefficient.

[0037] Furthermore, in the system provided in the embodiment of the application, the first error coefficient acquisition module 13 is also used for:

[0038] Acquire sample motor operating parameters, and annotate the sample motor operating parameters with error coefficients to obtain a corresponding sample error coefficient set; perform supervised training based on the sample motor operating parameters and the sample error coefficient set to obtain the parameter error analysis model; analyze the motor simulation parameters according to the parameter error analysis model to obtain the simulation operation error coefficient.

[0039] In the embodiment of the present application, the sample motor operating parameters are first collected, including speed, torque, power, temperature and vibration, etc., through the sensor array under different operating environments and test conditions. These operating parameters not only reflect the performance of the motor, but also include the potential impact of environmental factors on the performance, such as temperature changes, humidity, load conditions, etc.

[0040] Next, the error coefficients of the sample motor operating parameters are annotated. The error coefficient is a correction factor used to adjust the test data. The purpose is to take into account the impact of environmental interference so that the adjusted operating parameters are closer to the actual performance. The error coefficient annotation is completed by technical experts based on historical data and empirical rules. For example, based on previous operating data in similar environments, experts can assign specific error coefficients to operating parameters under certain conditions to reflect the impact of test conditions on performance. After the annotation is completed, a sample error coefficient set is generated, in which each error coefficient corresponds one-to-one with the corresponding sample operating parameter.

[0041] Then, supervised training is performed based on the sample motor operating parameters and sample error coefficient sets. Supervised training establishes a mathematical model that can automatically predict the error coefficient by learning the relationship between the parameters and the error coefficient. During the training process, the sample operating parameters are used as input and the sample error coefficient is used as output. Machine learning algorithms such as support vector machines are used for training, and finally a parameter error analysis model with predictive capabilities is generated.

[0042] After the model is built, the motor simulation parameters are input into the parameter error analysis model for data analysis. During the analysis, the parameter error analysis model outputs the simulation operation error coefficient corresponding to each simulation parameter based on the simulation parameters and the error relationship learned in training.

[0043] The second error coefficient acquisition module 14 performs actual testing on the motor to obtain actual operating parameters of the motor, and inputs the actual operating parameters of the motor into a pre-built parameter error analysis model to obtain actual operating error coefficients.

[0044] In the embodiment of the present application, the second error coefficient acquisition module first performs actual motor testing and obtains actual operating parameters through sensors in a real operating environment. These operating parameters include speed, torque, power, temperature, vibration, etc., which are important indicators reflecting the dynamic performance of the motor under actual working conditions. The sensor collects data in real time and converts the signal into digital operating parameters through the data transmission module.

[0045] Then, the actual operating parameters collected are input into the parameter error analysis model. The error calculation is performed by calling the parameter error analysis model, and the corresponding error coefficients are calculated according to the actual operating parameters combined with the characteristic mapping of the model. These error coefficients quantify the degree of influence of environmental factors on the actual test data. Finally, the actual operating error coefficient is output and corresponds to each actual operating parameter for subsequent error correction and performance verification steps.

[0046] The error correction module 15 performs error correction on the motor simulation parameters and the motor actual operation parameters according to the simulation operation error coefficient and the actual operation error coefficient to obtain a correction calculation result, wherein the correction calculation result includes the motor simulation correction parameters and the motor actual correction parameters.

[0047] In the embodiment of the present application, the error correction module first receives the simulated operation error coefficient and the actual operation error coefficient. Next, the motor simulation parameters are corrected. The correction method is to multiply the simulated operation error coefficient with the motor simulation parameter one by one to calculate the motor simulation correction parameter. Then, the motor actual operation parameter is corrected. By multiplying the actual operation error coefficient with the actual operation parameter, the influence of the environment and test conditions on the actual operation data is corrected to obtain the motor actual correction parameter.

[0048] Finally, the motor simulation correction parameters and the motor actual correction parameters are integrated to generate the correction calculation results and output them.

[0049] Furthermore, in the system provided in the embodiment of the application, the error correction module 15 is also used for:

[0050] The simulated operation error coefficients are mapped one-to-one with the motor simulation parameters, and the actual operation error coefficients are mapped one-to-one with the motor actual operation parameters; the simulated operation error coefficients are multiplied by the corresponding motor simulation parameters to generate the motor simulation correction parameters; the actual operation error coefficients are multiplied by the corresponding motor actual operation parameters to generate the motor actual correction parameters; the motor simulation correction parameters and the motor actual correction parameters are integrated and output as the correction calculation result.

[0051] In the embodiment of the present application, a one-to-one mapping operation is first performed. The simulated operation error coefficient is matched with the motor simulation parameters one by one, and the actual operation error coefficient is matched with the motor actual operation parameters one by one, ensuring that each error coefficient corresponds to a specific operation parameter. This mapping process is to clarify the scope of application of error correction and make subsequent calculations targeted. For example, the simulated operation error coefficient corresponds to simulation parameters such as speed and torque, and the actual operation error coefficient corresponds to actual parameters such as power and temperature.

[0052] Next, the motor simulation parameters are corrected. Each simulation operation error coefficient is multiplied by the corresponding simulation parameter to generate the corrected motor simulation correction parameters. For example, for the speed in the simulation parameter, multiply it by the corresponding simulation operation error coefficient to obtain the correction parameter for the speed in the motor simulation parameter. These corrected parameters are integrated to obtain the motor simulation correction parameters. Similarly, the actual motor operation parameters are corrected, and each actual operation error coefficient is multiplied by the corresponding actual operation parameter to generate the corrected motor actual correction parameters.

[0053] Finally, the motor simulation correction parameters and the motor actual correction parameters are integrated to generate the final correction calculation results.

[0054] The motor test result acquisition module 16 performs motor performance verification according to the correction calculation result and outputs the motor test result.

[0055] In an embodiment of the present application, first, the motor test result acquisition module receives the correction calculation results, which include the motor simulation correction parameters and actual correction parameters that have been error-corrected. Then a performance verification analysis is performed. Performance verification is to compare the corrected parameters with the preset performance standards to evaluate whether the performance of the motor under different working conditions meets the design requirements. The performance deviation evaluation is then started. By analyzing the difference between the correction parameters and the performance standards, a performance deviation result is generated. The performance deviation result quantifies the degree of deviation between the actual operating state of the motor and the ideal design target, and can intuitively reflect the operating performance of the motor in different dimensions.

[0056] Finally, the results of performance verification and deviation assessment are integrated to generate and output the motor test results.

[0057] Further, such as Figure 2 As shown, in the system provided by the embodiment of the application, the motor test result acquisition module 16 is also used for:

[0058] According to the correction calculation result, the corresponding parameters in the motor simulation correction parameters and the motor actual correction parameters are averaged to obtain a motor performance mean index; the motor performance mean index is compared with a preset performance standard to generate a performance deviation result; based on the performance deviation result, the motor operating performance is evaluated to generate a motor test result.

[0059] In the embodiment of the present application, the motor simulation correction parameters in the correction calculation results and the corresponding performance parameters in the motor actual correction parameters are first averaged to generate a motor performance average index. This process combines simulation and actual correction data to comprehensively reflect the motor's operating performance and avoids the deviation that may be caused by a single data.

[0060] The motor performance average index is then compared to the preset performance standards. The preset performance standards consist of the maximum and minimum values ​​of each performance parameter and are used to define the normal operating range. For example, the speed standard sets the maximum and minimum speed values ​​to ensure that the motor will neither overspeed nor underrun the starting requirements; the torque standard specifies the maximum and minimum output torque to ensure normal load capacity and starting performance.

[0061] Then, the performance deviation result is generated based on the comparison results. During the comparison process, if the performance mean index is between the maximum and minimum values ​​of the corresponding parameter, the performance is considered normal; if it exceeds the maximum value or is lower than the minimum value, the performance is judged to be unqualified. For example, if the mean speed exceeds the maximum allowable range, it may indicate that the motor has a risk of overspeed, while being lower than the minimum value may reflect a startup or load problem.

[0062] Finally, the motor's operating performance is comprehensively evaluated based on the performance deviation results to generate the motor test results. The test results clearly indicate whether the motor performance is qualified, and include specific deviation information. If all performance meets the preset performance standards, the test results will show "qualified"; if any parameter exceeds the standard range, it will be marked as "unqualified" and the performance items that need to be improved will be listed.

[0063] Furthermore, in the system provided in the application embodiment, the preset performance standards include a speed range standard, a torque range standard, a power range standard, a temperature range standard, and a vibration amplitude standard.

[0064] In an embodiment of the present application, the preset performance standards are used to define the normal range of key performance parameters in the operation of the motor, including speed range standards, torque range standards, power range standards, temperature range standards and vibration amplitude standards. Each standard consists of a maximum value and a minimum value, which are used to guide performance verification and test result judgment.

[0065] The preset speed range standard includes maximum speed and minimum speed values, for example, the speed under rated load shall not be lower than the designed minimum value, and the speed under high load shall not exceed the set maximum value.

[0066] The torque range standard includes a maximum torque value and a minimum torque value. The minimum value indicates the motor's starting ability under light load conditions, while the maximum value indicates the motor's carrying capacity under heavy load conditions.

[0067] The power range standard reflects the energy conversion efficiency of the motor. The preset maximum value is used to limit excessive power consumption to ensure energy-saving performance; the minimum value ensures that the motor can maintain normal operation under rated load.

[0068] The temperature range standard includes the maximum and minimum temperature values ​​for safe operation. For example, the maximum temperature value is used to limit the material damage caused by overheating, and the minimum temperature value is used to prevent the degradation of lubrication performance or component failure caused by low temperature.

[0069] The vibration amplitude standard is a key indicator for evaluating the mechanical stability of the motor. The preset maximum value is used to limit mechanical wear or failure caused by excessive vibration, while the minimum value is used to ensure the smooth operation of the motor. For example, if the vibration amplitude exceeds the maximum value when running under high load, it may indicate that the mechanical parts are loose, while if it is lower than the minimum value when running under low load, it may indicate abnormal operation status.

[0070] Further, in the system provided in the embodiment of the application, after obtaining the motor test result, the system is used to:

[0071] The motor test results are visualized on the terminal; and based on the corresponding relationship between the motor test results and the motor digital model, a terminal interface is displayed.

[0072] In the embodiment of the present application, the test result data is first processed and converted into an intuitive graphical form through visualization technology. These test results include evaluation data and deviation analysis results of key performance indicators such as speed, torque, power, temperature, and vibration. Visualization forms usually include trend charts, bar charts, and pie charts, which are used to display parameter change trends, comparison results with preset performance standards, and the distribution ratio of qualified and unqualified performance items.

[0073] Then, based on the correspondence between the motor test results and the motor digital model, they are dynamically displayed on the terminal interface. By matching the data structure of the test results with the characteristics of the motor digital model, the interface can intuitively overlay the test results on the virtual background of the digital model. For example, the speed test results can be dynamically marked in the speed module area of ​​the digital model, and the torque data can be displayed in the corresponding module to show whether it meets the preset standards, while the status of qualified and unqualified performance items is marked by color.

[0074] Finally, a dynamic interactive display is achieved on the terminal interface, and users can filter different performance items, view the corresponding test results and the characteristics associated with the digital model, so as to quickly understand the motor's operating performance and existing problems.

[0075] In the embodiments of the present application, in summary, the embodiments of the present application have at least the following technical effects:

[0076] The present application obtains motor operating parameters and establishes a motor digital model; based on the motor digital model, simulates the motor test to obtain motor simulation parameters; inputs the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain a simulated operation error coefficient; performs actual testing on the motor to obtain the motor actual operating parameters, inputs the motor actual operating parameters into a pre-built parameter error analysis model to obtain an actual operation error coefficient; performs error correction on the motor simulation parameters and the motor actual operating parameters according to the simulated operation error coefficient and the actual operation error coefficient to obtain a correction calculation result, the correction calculation result includes the motor simulation correction parameters and the motor actual correction parameters; performs motor performance verification according to the correction calculation result, and outputs a motor test result. The present invention solves the technical problem that the prior art cannot comprehensively and accurately evaluate motor performance and the test results are greatly affected by environmental factors. The present invention obtains motor operating parameters to establish a digital model, combines the simulated test and actual test data into the error analysis model, generates error correction results, optimizes the simulation and actual parameters through error correction, and performs performance verification, and finally outputs accurate motor test results, achieving the technical effect of comprehensive evaluation of motor performance.

[0077] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0079] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A multi-dimensional dynamic motor testing system, characterized in that: The system comprises: A digital model building module, wherein the digital model building module obtains motor operating parameters and builds a motor digital model; A simulation test module, wherein the simulation test module performs a simulation motor test based on the motor digital model to obtain motor simulation parameters; a first error coefficient acquisition module, wherein the first error coefficient acquisition module inputs the motor simulation parameters into a pre-built parameter error analysis model for data analysis to obtain a simulation operation error coefficient; a second error coefficient acquisition module, wherein the second error coefficient acquisition module performs actual testing on the motor to obtain actual operating parameters of the motor, and inputs the actual operating parameters of the motor into a pre-built parameter error analysis model to obtain actual operating error coefficients; an error correction module, wherein the error correction module performs error correction on the motor simulation parameters and the motor actual operation parameters according to the simulation operation error coefficient and the actual operation error coefficient to obtain a correction calculation result, wherein the correction calculation result includes the motor simulation correction parameter and the motor actual correction parameter; A motor test result acquisition module is used to verify the motor performance according to the correction calculation result and output the motor test result.

2. A multi-dimensional dynamic motor testing system as claimed in claim 1, characterized in that: Digital model building module, the system is also used for: Collect data from the motor to be tested and obtain the motor operating parameters; Operation fitting is performed based on the motor operation parameters to obtain the motor digital model.

3. A multi-dimensional dynamic motor testing system as claimed in claim 1, characterized in that: Simulation test module, the system is also used for: Based on the motor digital model, a simulation calculation is performed to obtain the motor simulation parameters; The motor simulation parameters include speed, torque, power, temperature and vibration.

4. A multi-dimensional dynamic motor testing system as claimed in claim 1, characterized in that: The first error coefficient acquisition module, the system is also used for: Acquire sample motor operating parameters, and annotate the sample motor operating parameters with error coefficients to obtain a corresponding sample error coefficient set; Performing supervised training based on the sample motor operating parameters and the sample error coefficient set to obtain the parameter error analysis model; The motor simulation parameters are analyzed according to the parameter error analysis model to obtain the simulation operation error coefficient.

5. The multi-dimensional dynamic motor testing system according to claim 1, characterized in that: The error correction module is further used for: Performing a one-to-one mapping between the simulated operation error coefficient and the motor simulation parameter, and performing a one-to-one mapping between the actual operation error coefficient and the motor actual operation parameter; Multiplying the simulated operation error coefficients by corresponding motor simulation parameters to generate the motor simulation correction parameters; Multiplying the actual operation error coefficients by corresponding actual operation parameters of the motors to generate actual correction parameters of the motors; The motor simulation correction parameters and the motor actual correction parameters are integrated and output as the correction calculation result.

6. A multi-dimensional dynamic motor testing system as claimed in claim 1, characterized in that: Motor test result acquisition module, the system is used for: According to the correction calculation result, performing mean calculation on the corresponding parameters of the motor simulation correction parameter and the motor actual correction parameter to obtain a motor performance mean index; Comparing the motor performance mean index with a preset performance standard to generate a performance deviation result; Based on the performance deviation results, the motor operating performance is evaluated and a motor test result is generated.

7. A multi-dimensional dynamic motor testing system as claimed in claim 6, characterized in that: The preset performance standards include speed range standards, torque range standards, power range standards, temperature range standards, and vibration amplitude standards.

8. The multi-dimensional dynamic motor testing system according to claim 1, characterized in that: After obtaining the motor test results, the system is used to: Performing terminal visualization on the motor test results; Based on the correspondence between the motor test result and the motor digital model, a terminal interface display is performed.

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