Device and method for testing low temperature working conditions of deep cooling motor

Abstract

The present invention provides a cryogenic motor low-temperature working condition testing device and method, which relate to the field of motor testing, wherein the device comprises: a structure acquisition module, used to acquire structural information of a cryogenic motor to be tested; a working condition determination module, used to determine at least one test working condition and a test item corresponding to each test working condition based on the structural information of the cryogenic motor to be tested; an environment simulation module, used to establish a simulated test environment corresponding to each test working condition according to the test working condition; a data acquisition module, used to acquire test data of the cryogenic motor to be tested in the simulated test environment and the test item corresponding to the test working condition for each test working condition; a data analysis module, used to analyze the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested in the simulated test environment and the test item corresponding to each test working condition, which has the advantage of improving the accuracy of the cryogenic motor low-temperature working condition test.

Description

Technical Field

[0001] The invention relates to the field of motor testing, and in particular to a device and method for testing a deep-cold motor under low-temperature conditions. Background Art

[0002] In scientific research, industrial production, and technical applications in specific fields, it is often necessary to conduct experiments or operations at extremely low temperatures. For example, in the study of superconducting materials, it is necessary to observe the superconducting properties of materials in an environment close to absolute zero; in the chemical industry, certain chemical reactions need to be carried out at low temperatures to improve yield or selectivity; in the medical field, low-temperature environments are used to preserve and transport biological samples or drugs. These application scenarios have given rise to the demand for cryogenic motors. Cryogenic motors are specially designed motors whose main feature is that they can operate in cryogenic environments. The type test of motors includes many items, such as no-load current, no-load loss, efficiency, temperature rise, starting torque, maximum torque, etc. The detection of these items must be the same or similar to the actual operating conditions, and there should not be too much difference. For ordinary motors, general motor test stations can fully meet the requirements. However, for cryogenic motors, since the operating temperature (below -100°C) is much lower than room temperature, the resistance of the motor windings has changed greatly. If the test is still carried out in a normal temperature environment, the results obtained will be seriously deviated from the actual situation, which loses the meaning of the test.

[0003] At the current motor type test station, when the motor is tested, the ambient temperature is room temperature, that is, about 20°C. Even if the actual operating temperature of the motor is not within this range, the temperature difference is not large and will not have a substantial impact on the test structure. However, in a deep cold environment, that is, dozens of degrees below zero or even lower, the temperature difference with room temperature is large, and the ambient temperature of the laboratory can no longer meet the test conditions for deep cold motors.

[0004] Therefore, it is necessary to provide a cryogenic motor low-temperature operating condition testing device and method to improve the accuracy of the cryogenic motor low-temperature operating condition testing. Summary of the invention

[0005] In order to solve the technical problem in the prior art that the normal temperature environment cannot meet the test conditions of the cryogenic motor, resulting in a serious deviation between the results obtained in the prior art and the actual conditions of the cryogenic motor under low-temperature conditions, the present invention provides a cryogenic motor low-temperature condition testing device, including: a structure acquisition module, used to obtain the structural information of the cryogenic motor to be tested; a working condition determination module, used to determine at least one test working condition and a test item corresponding to each test working condition based on the structural information of the cryogenic motor to be tested; an environmental simulation module, used to establish a simulated test environment corresponding to the test working condition for each test working condition according to the test working condition; a data acquisition module, used to obtain the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test condition for each test working condition; a data analysis module, used to analyze the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test working condition.

[0006] Furthermore, the operating condition determination module determines at least one test operating condition based on the structural information of the deep-cold motor to be tested, including: obtaining structural information of multiple test motors; obtaining test data of multiple test items of the multiple test motors under multiple test conditions; determining the test operating condition corresponding to each of the test motors according to the test data of multiple test items of the multiple test motors under multiple test conditions; determining at least one test operating condition according to the structural information of the deep-cold motor to be tested, the structural information of the multiple test motors and the test operating condition corresponding to each of the test motors.

[0007] Furthermore, the operating condition determination module determines the test operating condition corresponding to each of the test motors based on the test data of multiple test items of the multiple test motors under multiple test operating conditions, including: calculating the structural difference value of any two of the test motors based on the structural information of the multiple test motors; clustering the multiple test motors based on the structural difference value of any two of the test motors according to a clustering algorithm to determine multiple test motor clusters; for each of the test motor clusters, determining the performance characteristic matrix of each test motor included in the test motor cluster under each test operating condition based on the test data of multiple test items of each test motor included in the test motor cluster under multiple test operating conditions, calculating the operating condition correlation coefficient between each of the test operating conditions and the test motor cluster based on the performance characteristic matrix of each test motor included in the test motor cluster under each test operating condition, determining the test operating condition corresponding to the test motor cluster based on the operating condition correlation coefficient between each of the test operating conditions and the test motor cluster, and using the test operating condition corresponding to the test motor cluster as the test operating condition corresponding to each test motor included in the test motor cluster.

[0008] Furthermore, the operating condition determination module determines the test items corresponding to each of the test conditions based on the structural information of the deep-cold motor to be tested, including: for each test condition corresponding to the test motor cluster, determining the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition according to the test data of multiple test items of each test motor included in the test motor cluster under the test condition; calculating the item correlation coefficient between each test item and each test condition according to the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition, and determining the test items corresponding to the test motor cluster under the test condition; using the test items corresponding to the test motor cluster under each test condition as the test items corresponding to each test motor included in the test motor cluster under each test condition; determining the test items corresponding to each of the test conditions according to the structural information of the deep-cold motor to be tested, the structural information of the multiple test motors, the test conditions corresponding to each of the test motors and the test items corresponding to each test condition.

[0009] Furthermore, the operating condition determination module determines at least one test operating condition and test items corresponding to each test operating condition based on the structural information of the deep-refrigerated motor to be tested, including: for each of the test motor clusters, determining the central structural information of the test motor cluster according to the structural information of each test motor included in the test motor cluster; for each of the test motor clusters, determining the first central structural feature sequence corresponding to the test motor cluster according to the central structural information of the test motor cluster, wherein the first central structural feature sequence is composed of eigenvalues ​​corresponding to a plurality of motor structural factors; for each of the motor structural factors, calculating the factor correlation coefficient of the motor structural factor according to the eigenvalue of the motor structural factor corresponding to each of the test motor clusters; determining a plurality of target motor structural factors according to the factor correlation coefficient of each of the motor structural factors; for each of the test motor clusters, determining the first central structural feature sequence corresponding to the test motor cluster according to the central structural information of the test motor cluster; wherein the first central structural feature sequence is composed of eigenvalues ​​corresponding to a plurality of motor structural factors; , determine the second central structure feature sequence corresponding to the test motor cluster based on the central structure information of the test motor, wherein the second central structure feature sequence is composed of feature values ​​corresponding to multiple target motor structure factors; determine the structure feature sequence corresponding to the deep-cold motor to be tested based on the multiple target motor structure factors and the structure information of the deep-cold motor to be tested; calculate the sequence difference value between the structure feature sequence corresponding to the deep-cold motor to be tested and the second central structure feature sequence corresponding to each of the test motor clusters; determine the test motor cluster corresponding to the deep-cold motor to be tested based on the sequence difference value between the structure feature sequence corresponding to the deep-cold motor to be tested and the second central structure feature sequence corresponding to each of the test motor clusters; determine the at least one test condition based on the test motor cluster corresponding to the deep-cold motor to be tested; determine the test items corresponding to each of the test conditions based on the test items corresponding to the test motor cluster corresponding to the deep-cold motor to be tested under each test condition.

[0010] Furthermore, the environmental simulation module includes an environmental temperature control unit, an environmental humidity control unit and an environmental atmospheric pressure control unit, wherein the environmental temperature control unit, the environmental humidity control unit and the environmental atmospheric pressure control unit are used to adjust the environmental temperature, environmental humidity and environmental atmospheric pressure of the test environment according to the test conditions, and establish a simulated test environment corresponding to the test conditions.

[0011] Furthermore, the data acquisition module obtains test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to the test conditions, including: determining multiple vibration detection positions and multiple sound detection positions corresponding to the deep-cold motor to be tested based on the test data of multiple test items of the multiple test motors under multiple test conditions; obtaining test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to the test conditions based on the multiple vibration detection positions and multiple sound detection positions corresponding to the deep-cold motor to be tested.

[0012] Further, the data acquisition module determines multiple vibration detection positions and multiple sound detection positions corresponding to the deep-cold motor to be tested based on the test data of multiple test items of the multiple test motors under multiple test conditions, including: for each test motor cluster, determining the vibration position risk coefficient of each test vibration position and the test motor cluster and the sound position risk coefficient of each test sound position and the test motor cluster according to the test data of multiple test items of each test motor included in the test motor cluster under multiple test conditions; determining multiple test vibration positions and multiple test sound positions corresponding to the test motor cluster according to the vibration position risk coefficient of each test vibration position and the test motor cluster and the sound position risk coefficient of each test sound position and the test motor cluster; determining multiple vibration detection positions and multiple sound detection positions corresponding to the deep-cold motor to be tested according to the test motor cluster corresponding to the deep-cold motor to be tested and the multiple test vibration positions and multiple test sound positions corresponding to each test motor cluster.

[0013] Furthermore, the data analysis module analyzes the performance of the deep-cold motor to be tested according to the test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to each test condition, including: for each of the test motor clusters, a performance analysis model corresponding to the test motor cluster is established according to the test data of multiple test items of each test motor included in the test motor cluster under multiple test conditions; according to the test motor cluster corresponding to the deep-cold motor to be tested, the performance analysis model corresponding to the test motor cluster is called to analyze the performance of the deep-cold motor to be tested based on the test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to each test condition.

[0014] The present invention provides a method for testing low-temperature conditions of a cryogenic motor, which is applied to the above-mentioned low-temperature conditions testing device for a cryogenic motor, comprising: obtaining structural information of a cryogenic motor to be tested; based on the structural information of the cryogenic motor to be tested, determining at least one test condition and a test item corresponding to each test condition; for each test condition, establishing a simulated test environment corresponding to the test condition according to the test condition; for each test condition, obtaining test data of the cryogenic motor to be tested under the simulated test environment and the test item corresponding to the test condition; and analyzing the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested under the simulated test environment and the test item corresponding to each test condition.

[0015] Compared with the prior art, the cryogenic motor low temperature working condition testing device and method provided by the present invention have at least the following beneficial effects:

[0016] 1. The structure acquisition module can accurately capture the structural information of the cryogenic motor to be tested, which provides a solid foundation for the subsequent determination of the test conditions. Based on the structural information of the motor, the condition determination module can customize the test conditions and test items that match the motor characteristics, thereby ensuring the pertinence and effectiveness of the test. The environmental simulation module can simulate a test environment that is highly similar to the real cryogenic environment, which is essential for evaluating the performance of the motor under extreme low temperature conditions. The module can also flexibly adjust the parameters of the test environment, such as temperature, humidity, pressure, etc., according to the specific requirements of the test conditions to meet the needs of different test items. The data acquisition module can comprehensively collect various test data of the motor under the simulated test environment, including key parameters such as voltage, current, power, torque, and speed. The module uses high-precision sensors and acquisition equipment to ensure the accuracy and reliability of the data, providing strong support for subsequent data analysis. The data analysis module can conduct in-depth analysis and processing of the collected test data to extract the performance characteristics, failure modes, and potential problems of the motor. The module can evaluate the performance level of the motor and provide a scientific basis and guidance for the optimization design, improved production, and maintenance of the motor. The entire test system adopts a modular design, and the modules work together to significantly improve the test efficiency. Through the automated and intelligent test process, manual intervention and errors are reduced, the test cycle is shortened, and the test cost is reduced. The test system has good scalability and can be continuously upgraded and improved with the increase in test requirements and the update of test technology. At the same time, the system also has high flexibility and can adapt to the test requirements of cryogenic motors of different models and specifications.

[0017] 2. By calculating the structural difference value and the working condition correlation coefficient, the similarity between the motor to be tested and the test motor cluster can be matched more accurately, so as to select the test working condition that better matches the characteristics of the motor to be tested. Determining the test items according to the project correlation coefficient can ensure that the test content covers the key performance indicators that the motor to be tested may encounter under specific working conditions. Through the intelligent grouping and selection process, test equipment and human resources can be used more effectively to avoid waste of resources. For each test motor cluster, only one comprehensive test condition and test item analysis is needed to provide test guidance for all motors in the cluster.

[0018] The test conditions and test items can be adjusted according to the specific structural information of the motor to be tested, so as to adapt to cryogenic motors of different models and specifications. By dynamically adjusting the test conditions and items, different test requirements can be responded to more flexibly, and the versatility and adaptability of the test can be improved.

[0019] 3. By determining the central structural information and the second central structural feature sequence of the test motor cluster, the structural similarity between different test motor clusters can be described and compared more accurately. The introduction of motor structural factors and factor correlation coefficients can screen out the key structural factors that have the greatest impact on motor performance, thereby ensuring that the selection of test conditions and test items is closely related to these key factors. By calculating the sequence difference values ​​between the deep-cold motor to be tested and each test motor cluster, the test motor cluster with the most similar structure to the motor to be tested can be selected for testing, thereby avoiding unnecessary waste of resources. This test selection method based on structural similarity can ensure that test resources are used where they are most needed and improve the utilization efficiency of test resources. Through standardized test conditions and test item determination processes, it can ensure that deep-cold motors of different batches and models are compared and evaluated under the same test conditions. This standardized test method helps to enhance the versatility and repeatability of the test, making the test results more reliable and convincing. Through precise testing and data analysis, we can have a deeper understanding of the performance of deep-cold motors under different structural factors, thereby providing strong support for the design and optimization of motors. It can reveal the intrinsic relationship between motor performance and structural factors, and provide a scientific basis for improving motor structure, performance and reliability. Through intelligent test conditions and test item selection methods, unnecessary test steps and test time can be reduced, thereby improving test efficiency. At the same time, since test resources are more reasonably allocated and utilized, the test cost can be further reduced and the cost-effectiveness of the test can be improved.

[0020] 4. By determining the detection position based on the vibration and sound position risk coefficients of the test motor cluster, the key areas where problems may occur on the deep-cold motor to be tested can be located more accurately, thereby improving the accuracy and pertinence of data collection. This intelligent location selection method avoids blind and random data collection and improves the efficiency of data collection. Through intelligent location selection, test resources such as sensors and data acquisition equipment can be allocated more reasonably to ensure that resources are used where they are most needed. This helps to reduce testing costs and improve the cost-effectiveness of testing. Using a performance analysis model based on a test motor cluster, it can ensure that deep-cold motors of different batches and models are compared and evaluated under the same test conditions, enhancing the reliability and repeatability of the test. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0022] Figure 1 It is a schematic diagram of a module of a cryogenic motor low temperature working condition testing device according to some embodiments of this specification;

[0023] Figure 2 is a flowchart of determining at least one test condition and test items corresponding to each test condition according to some embodiments of this specification;

[0024] Figure 3 It is a flow chart of a method for testing a cryogenic motor under low temperature conditions according to some embodiments of this specification. DETAILED DESCRIPTION

[0025] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0026] Figure 1 is a schematic diagram of a module of a cryogenic motor low temperature working condition test device according to some embodiments of this specification, such as Figure 1 As shown, the cryogenic motor low-temperature operating condition testing device may include a structure acquisition module, an operating condition determination module, an environmental simulation module, a data acquisition module and a data analysis module.

[0027] The structure acquisition module can be used to obtain the structural information of the deep-cooled motor to be tested.

[0028] The structural information of the cryogenic motor may include the structural information of the stator, the structural information of the rotor, the structural information of the insulation structure and the structural information of other parts. The structural acquisition module may acquire the structural information of the cryogenic motor through the structural diagram, component description, working principle and the like of the cryogenic motor.

[0029] The operating condition determination module can be used to determine at least one test operating condition and test items corresponding to each test operating condition based on the structural information of the deep-cooled motor to be tested.

[0030] Preferably, the operating condition determination module determines at least one test operating condition based on the structural information of the cryogenic motor to be tested, including:

[0031] Obtain structural information of multiple test motors;

[0032] Obtain test data of multiple test motors under multiple test conditions and multiple test items;

[0033] Determine the test conditions corresponding to each test motor according to the test data of multiple test items of multiple test motors under multiple test conditions;

[0034] At least one test condition is determined based on the structural information of the deep-cooled motor to be tested, the structural information of multiple test motors, and the test conditions corresponding to each test motor.

[0035] Specifically, any two test conditions have differences in at least one environmental parameter among the environmental temperature, environmental humidity, environmental pressure, etc. For example, test condition 1 has an environmental temperature of -80°C, an environmental humidity of 5%, and an environmental pressure of 700hPa, and test condition 2 has an environmental temperature of -90°C, an environmental humidity of 10%, and an environmental pressure of 800hPa.

[0036] Any two test items differ in at least one operating parameter such as motor load or test duration.

[0037] The test data of the test motor in each test item may include speed, current, voltage, power, efficiency, temperature, vibration, sound and other data.

[0038] Preferably, the working condition determination module determines the test working condition corresponding to each test motor according to the test data of multiple test items of multiple test motors under multiple test working conditions, including:

[0039] According to the structural information of multiple test motors, the structural difference value of any two test motors is calculated;

[0040] Clustering the multiple test motors based on structural difference values ​​of any two test motors according to a clustering algorithm (e.g., a K-means clustering algorithm, a hierarchical clustering algorithm, etc.) to determine multiple test motor clusters;

[0041] For each test motor cluster, the performance characteristic matrix of each test motor included in the test motor cluster under each test condition is determined based on the test data of multiple test items of each test motor included in the test motor cluster under multiple test conditions; the condition correlation coefficient between each test condition and the test motor cluster is calculated based on the performance characteristic matrix of each test motor included in the test motor cluster under each test condition; the test conditions corresponding to the test motor cluster are determined based on the condition correlation coefficient between each test condition and the test motor cluster; the test conditions corresponding to the test motor cluster are used as the test conditions corresponding to each test motor included in the test motor cluster.

[0042] Specifically, for each test motor, a structural feature sequence of the test motor is determined based on the structural information of the test motor, wherein the structural feature sequence is composed of characteristic values ​​corresponding to multiple motor structure factors. As an example, the multiple motor structure factors may include at least shell size, shell material, stator size, stator material, rotor size, rotor material, insulation structure size, insulation structure material, winding type, number of poles, number of slots, etc.

[0043] The structural difference value of the two test motors can be calculated according to the following formula:

[0044] ,

[0045] in, is the structural difference between the i-th test motor and the j-th test motor, is the preset parameter, greater than 0, is the characteristic value of the mth motor structure factor corresponding to the ith test motor, is the characteristic value of the mth motor structure factor corresponding to the jth test motor, is the total number of motor structure factors.

[0046] Each row vector (also referred to as a "performance characteristic vector") of the performance characteristic matrix of the test motor under each test condition may correspond to the test data of a test item of the test motor under the test condition. For example, the first row vector of the performance characteristic matrix of the test motor under test condition A1 may correspond to test item 1, and the second row vector of the performance characteristic matrix of the test motor under test condition A1 may correspond to test item 2. Each element of the row vector of the performance characteristic matrix may correspond to a type of test data. For example, the row vector is (r, I, W, V1, T, V2, V3), where r is the speed, I is the current, V1 is the voltage, W is the power, T is the temperature, V2 is the vibration, and V3 is the sound.

[0047] The correlation coefficient between the test condition and the condition of the test motor cluster can be calculated according to the following formula:

[0048] ,

[0049] in, is the correlation coefficient between the i-th test condition and the j-th test motor cluster condition, The jth test motor cluster includes The performance characteristic matrix of the test motor under the i-th test condition is related to the j-th test motor cluster including the The cosine similarity of the performance characteristic matrix of the test motor under the i-th test condition, The jth test motor cluster includes The performance characteristic matrix of the test motor under the i-th test condition is: The jth test motor cluster includes The performance characteristic matrix of the test motor under the i-th test condition is: is the total number of test motors included in the jth test motor cluster.

[0050] The test condition whose condition correlation coefficient is greater than the condition correlation coefficient threshold is taken as the test condition corresponding to the test motor cluster.

[0051] Each test item may include at least one of the following test contents:

[0052] Resistance measurement: Measure the resistance of the motor windings to ensure it is within the manufacturer's specifications.

[0053] Voltage measurement: When the motor is running, measure the voltage at the motor input terminal.

[0054] Current measurement: Measure the current value of the motor when the motor is running.

[0055] Insulation test: Check the insulation performance between motor windings.

[0056] No-load test: The motor is run without load, and its voltage, current and other parameters are measured to evaluate the no-load performance of the motor.

[0057] Load test: Run the motor with load and measure its voltage, current, power and other parameters to evaluate the load performance of the motor.

[0058] Efficiency determination: The efficiency of the motor is calculated by measuring the input electrical power and output mechanical power.

[0059] Overvoltage test: Apply a voltage exceeding the rated voltage to the motor to evaluate its overvoltage withstand capability.

[0060] Moment of inertia measurement: Measures the moment of inertia of a motor’s rotor to assess its dynamic performance.

[0061] Vibration testing: Use vibration sensors to measure the vibration of the motor while it is running to evaluate its mechanical stability and running smoothness.

[0062] Noise test: Use a noise measuring instrument to measure the noise level of the motor while it is running to evaluate its noise performance.

[0063] Torque test: measure the torque value of the motor under different loads to evaluate its torque output capacity.

[0064] Speed ​​measurement: Use a tachometer to measure the actual speed of the motor.

[0065] Measurement of key characteristic parameters: including measurement of continuous torque, continuous power, peak torque, peak power, maximum operating speed, maximum efficiency and other parameters.

[0066] Stalled-rotor test: The current and torque values ​​of the motor are measured when the motor rotor is blocked to evaluate the motor's stall performance.

[0067] Preferably, the working condition determination module determines the test items corresponding to each test working condition based on the structural information of the cryogenic motor to be tested, including:

[0068] For each test condition corresponding to the test motor cluster, determine the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition based on the test data of multiple test items of each test motor included in the test motor cluster under the test condition; calculate the item correlation coefficient between each test item and each test condition based on the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition, and determine the test item corresponding to the test motor cluster under the test condition;

[0069] The test items corresponding to the test motor cluster under each test condition shall be the test items corresponding to each test motor included in the test motor cluster under each test condition;

[0070] According to the structural information of the cryogenic motor to be tested, the structural information of multiple test motors, the test conditions corresponding to each test motor and the test items corresponding to each test condition, the test items corresponding to each test condition are determined.

[0071] Specifically, the correlation coefficient between each test item and each test condition can be calculated according to the following formula:

[0072] ,

[0073] in, is the project correlation coefficient between the ith test condition and the tth test item corresponding to the jth test motor cluster, The jth test motor cluster includes The performance characteristic vector of the tth test item of the test motor under the ith test condition, The jth test motor cluster includes The performance characteristic vector of the tth test item of a test motor under the ith test condition.

[0074] The test items whose item correlation coefficients are greater than the item correlation coefficient threshold may be used as the test items corresponding to the test motor cluster under the test working conditions.

[0075] Figure 2 is a flowchart of determining at least one test condition and test items corresponding to each test condition according to some embodiments of this specification, such as Figure 2 As shown, preferably, the working condition determination module determines at least one test working condition and the test items corresponding to each test working condition based on the structural information of the cryogenic motor to be tested, including:

[0076] For each test motor cluster, determining the central structural information of the test motor cluster according to the structural information of each test motor included in the test motor cluster;

[0077] For each test motor cluster, determining a first central structure feature sequence corresponding to the test motor cluster according to the central structure information of the test motor cluster, wherein the first central structure feature sequence is composed of feature values ​​corresponding to a plurality of motor structure factors;

[0078] For each motor structure factor, the factor correlation coefficient of the motor structure factor was calculated based on the eigenvalue of the motor structure factor corresponding to each experimental motor cluster;

[0079] Determine a plurality of target motor structure factors according to the factor correlation coefficient of each motor structure factor;

[0080] For each test motor cluster, according to the multiple target motor structure factors and the central structure information of the test motor cluster, a second central structure feature sequence corresponding to the test motor cluster is determined, wherein the second central structure feature sequence is composed of feature values ​​corresponding to the multiple target motor structure factors;

[0081] Determine a structural feature sequence corresponding to the deep-cold motor to be tested according to multiple target motor structural factors and structural information of the deep-cold motor to be tested;

[0082] Calculate the sequence difference value between the structural feature sequence corresponding to the deep-cooled motor to be tested and the second central structural feature sequence corresponding to each test motor cluster;

[0083] Determine the test motor cluster corresponding to the deep-cold motor to be tested according to the sequence difference value between the structural feature sequence corresponding to the deep-cold motor to be tested and the second central structural feature sequence corresponding to each test motor cluster, and determine at least one test condition according to the test motor cluster corresponding to the deep-cold motor to be tested;

[0084] According to the test items corresponding to the test motor cluster corresponding to the deep-cooled motor to be tested under each test condition, the test items corresponding to each test condition are determined.

[0085] Specifically, for each test motor cluster, the structural information of each test motor included in the test motor cluster may be averaged to serve as the central structural information of the test motor cluster.

[0086] The factor correlation coefficient of the motor structure factor can be calculated according to the following formula:

[0087] ,

[0088] in, is the factor correlation coefficient of the kth motor structure factor, For the The eigenvalue of the kth motor structure factor in the first central structure feature sequence corresponding to the experimental motor cluster, is the total number of test motor clusters.

[0089] The motor structure factor with a factor correlation coefficient greater than the factor correlation coefficient threshold is used as the target motor structure factor.

[0090] The sequence difference value between the structural feature sequence corresponding to the deep-cooled motor to be tested and the second central structural feature sequence corresponding to each test motor cluster can be calculated according to the following formula:

[0091] ,

[0092] in, is the sequence difference value between the structural feature sequence corresponding to the deep-cooled motor to be tested and the second central structural feature sequence corresponding to the kth test motor cluster, is the total number of target motor structure factors, is the first in the structural feature sequence corresponding to the deep-cooled motor to be tested. The value of the element, is the second central structure feature sequence corresponding to the kth test motor cluster The value of the element, is the preset parameter, Greater than 0.

[0093] The test motor cluster with the smallest sequence difference value can be used as the test motor cluster corresponding to the deep-cooled motor to be tested.

[0094] The environmental simulation module can be used to establish a simulated test environment corresponding to each test condition according to the test condition.

[0095] Preferably, the environmental simulation module includes an environmental temperature control unit, an environmental humidity control unit and an environmental atmospheric pressure control unit, wherein the environmental temperature control unit, the environmental humidity control unit and the environmental atmospheric pressure control unit are used to adjust the environmental temperature, environmental humidity and environmental atmospheric pressure of the test environment according to the test conditions, and establish a simulated test environment corresponding to the test conditions.

[0096] Specifically, the ambient temperature control unit is responsible for adjusting the temperature in the test environment to achieve the required cryogenic conditions. It usually includes a refrigeration system (such as a liquid nitrogen cooling system, a refrigeration compressor, etc.) and a temperature control system (such as a temperature sensor, a heating element, and a temperature controller). The refrigeration system lowers the ambient temperature, while the temperature control system monitors and adjusts the temperature to ensure that the temperature in the test environment is stable within the preset cryogenic range.

[0097] The environmental humidity control unit is used to adjust the humidity level in the test environment. Through humidification or dehumidification equipment (such as humidifiers, dehumidifiers, etc.) and humidity sensors and control systems, the humidity level in the test environment is accurately controlled to meet the requirements of specific test conditions.

[0098] The ambient atmospheric pressure control unit is responsible for adjusting the atmospheric pressure in the test environment. The pressure in the test environment is reduced or increased through a pressure control system (such as a vacuum pump, pressure sensor, and controller) to achieve the required pressure level.

[0099] The data acquisition module can be used to obtain test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test condition for each test condition.

[0100] Specifically include:

[0101] Determine multiple vibration detection positions and multiple sound detection positions corresponding to the cryogenic motor to be tested according to the test data of multiple test items of multiple test motors under multiple test conditions;

[0102] According to a plurality of vibration detection positions and a plurality of sound detection positions corresponding to the cryogenic motor to be tested, test data of the cryogenic motor to be tested under a simulated test environment and test items corresponding to the test conditions are obtained.

[0103] Preferably, the data acquisition module determines multiple vibration detection positions and multiple sound detection positions corresponding to the cryogenic motor to be tested according to the test data of multiple test items of multiple test motors under multiple test conditions, including:

[0104] For each test motor cluster, determine the vibration position risk factor of the test motor cluster corresponding to each test vibration position and the sound position risk factor of the test motor cluster corresponding to each test sound position based on the test data of various test items of each test motor included in the test motor cluster under various test conditions; determine multiple test vibration positions and multiple test sound positions corresponding to the test motor cluster based on the vibration position risk factor of the test motor cluster corresponding to each test vibration position and the sound position risk factor of the test motor cluster corresponding to each test sound position;

[0105] According to the test motor cluster corresponding to the cryogenic motor to be tested and the multiple test vibration positions and the multiple test sound positions corresponding to each test motor cluster, the multiple vibration detection positions and the multiple sound detection positions corresponding to the cryogenic motor to be tested are determined.

[0106] Specifically, for each test condition corresponding to the test motor cluster, the vibration sequence corresponding to each test item at each test vibration position can be determined based on the test data of multiple test items corresponding to each test motor included in the test motor cluster under the test condition, wherein the vibration sequence includes the vibration acceleration of the test vibration position at multiple time points during the test item. The vibration sequence can be subjected to variational mode decomposition to extract the characteristics of each vibration sequence component (for example, center frequency, bandwidth, kurtosis, amplitude, energy, phase, phase difference, etc.).

[0107] For each test vibration position, the vibration position risk coefficient of the test motor cluster corresponding to each test vibration position can be determined by a vibration risk prediction model according to the characteristics of each vibration sequence component of the vibration sequence of each test item corresponding to each test vibration position. The vibration risk prediction model can be a convolutional neural network (CNN) model.

[0108] For each test condition corresponding to the test motor cluster, the sound sequence corresponding to each test item at each test sound position can be determined based on the test data of multiple test items corresponding to each test motor included in the test motor cluster under the test condition, wherein the sound sequence includes the sound acceleration of the test sound position at multiple time points during the test item. The sound sequence can be subjected to variational mode decomposition to extract the features of each sound sequence component (e.g., center frequency, bandwidth, kurtosis, amplitude, energy, phase, phase difference, etc.).

[0109] For each test sound position, the sound position risk coefficient of the test motor cluster corresponding to each test sound position can be determined by the sound risk prediction model according to the characteristics of each sound sequence component of the sound sequence of each test item corresponding to each test sound position. The sound risk prediction model can be a convolutional neural network (CNN) model.

[0110] A vibration sensor may be provided at each vibration detection position corresponding to the cryogenic motor to be tested, and a noise measuring instrument may be provided at each sound detection position corresponding to the cryogenic motor to be tested.

[0111] The data acquisition module can also be equipped with other devices (for example, resistance measuring instruments, voltage sensors, current sensors, insulation resistance testers, speed sensors, acceleration sensors and torque sensors, etc.) to collect other test data (for example, the resistance value of the motor winding, the voltage at the motor input terminal, voltage, current, power, torque values ​​under different loads, the rotational inertia of the motor rotor, etc.).

[0112] The data analysis module can be used to analyze the performance of the cryogenic motor to be tested based on the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test condition.

[0113] Specifically include:

[0114] For each test motor cluster, a performance analysis model corresponding to the test motor cluster is established according to test data of multiple test items of each test motor included in the test motor cluster under multiple test conditions, wherein the performance analysis model may be a Long Short Term Memory Network (LSTM) model;

[0115] According to the test motor cluster corresponding to the deep-cold motor to be tested, the performance analysis model corresponding to the test motor cluster is called. Based on the test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to each test condition, the performance of the deep-cold motor to be tested is analyzed. For example, in the deep-cold environment, the no-load voltage of the motor to be tested is stable, and the fluctuation range is within ±1%, indicating that the motor can still maintain good voltage stability under extreme low temperature conditions. The no-load current is small, and the current value decreases slightly with the decrease in temperature. This may be because the deep-cold environment reduces the resistance and magnetic resistance of the motor, thereby reducing the current loss. The no-load power factor is high, close to 0.95, indicating that the motor has good power factor performance under no-load conditions. In the load test, the output voltage and current of the motor to be tested both increase with the increase of load, and the change curve is smooth, indicating that the motor has good load adaptability. The load power and efficiency test results show that the efficiency of the motor under rated load is as high as 96%, and it can still maintain a high efficiency level in the high load area, thanks to the efficient design of the motor and the heat dissipation effect of the deep-cold environment. The torque test results show that the motor has stable torque output under different loads and can meet the design requirements. At the same time, the peak torque and continuous torque of the motor are both high, indicating that the motor has good torque output capacity. The speed test results show that the motor has small speed fluctuations when the load changes and can maintain a stable speed output.

[0116] It is recommended to further optimize the heat dissipation design and control system of the motor to improve its operating efficiency and reliability under extreme low temperature conditions.

[0117] Specifically, the test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to each test condition can be input into the performance analysis model corresponding to the test motor cluster corresponding to the deep-cold motor to be tested. The performance analysis model corresponding to the test motor cluster corresponding to the deep-cold motor to be tested analyzes the performance of the deep-cold motor to be tested and outputs the performance analysis results.

[0118] Figure 3 is a flow chart of a method for testing a cryogenic motor under low temperature conditions according to some embodiments of this specification, such as Figure 3 As shown, the low temperature working condition testing method of a deep-cooled motor may include the following steps.

[0119] Step 310, obtaining structural information of the cryogenic motor to be tested;

[0120] Step 320, based on the structural information of the cryogenic motor to be tested, determining at least one test condition and test items corresponding to each test condition;

[0121] Step 330, for each test condition, according to the test condition, establish a simulation test environment corresponding to the test condition;

[0122] Step 340, for each test condition, obtaining test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test condition;

[0123] Step 350 , analyzing the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test condition.

[0124] The cryogenic motor low temperature operating condition test device can be used to execute the cryogenic motor low temperature operating condition test method. For more descriptions of the cryogenic motor low temperature operating condition test method, please refer to the relevant description of the cryogenic motor low temperature operating condition test method device, which will not be repeated here.

[0125] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A cryogenic motor low temperature working condition test device, characterized in that: include: A structure acquisition module, used to obtain the structural information of the deep-cooled motor to be tested; A working condition determination module, used for determining at least one test working condition and a test item corresponding to each test working condition based on the structural information of the cryogenic motor to be tested; An environmental simulation module, for establishing, for each of the test conditions, a simulated test environment corresponding to the test condition according to the test condition; A data acquisition module, for obtaining, for each of the test conditions, test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test condition; A data analysis module, used to analyze the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test condition; The operating condition determination module determines at least one test operating condition based on the structural information of the cryogenic motor to be tested, including: Obtain structural information of multiple test motors; Acquire test data of multiple test items of the multiple test motors under multiple test conditions; Determine the test condition corresponding to each of the test motors according to the test data of the multiple test items under the multiple test conditions; Determine at least one test condition according to the structural information of the cryogenic motor to be tested, the structural information of the multiple test motors and the test conditions corresponding to each of the test motors; The working condition determination module determines the test working condition corresponding to each of the test motors according to the test data of the multiple test items under the multiple test working conditions, including: Calculating a structural difference value between any two of the test motors according to the structural information of the multiple test motors; Clustering the plurality of test motors based on the structural difference values ​​of any two of the test motors according to a clustering algorithm to determine a plurality of test motor clusters; For each of the test motor clusters, determine the performance characteristic matrix of each test motor included in the test motor cluster under each test condition based on the test data of multiple test items of each test motor included in the test motor cluster under multiple test conditions; calculate the working condition correlation coefficient between each of the test conditions and the test motor cluster based on the performance characteristic matrix of each test motor included in the test motor cluster under each test condition; determine the test condition corresponding to the test motor cluster based on the working condition correlation coefficient between each of the test conditions and the test motor cluster; and use the test condition corresponding to the test motor cluster as the test condition corresponding to each of the test motors included in the test motor cluster; The working condition determination module determines the test items corresponding to each of the test working conditions based on the structural information of the cryogenic motor to be tested, including: For each test condition corresponding to a test motor cluster, determine the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition based on the test data of multiple test items of each test motor included in the test motor cluster under the test condition; calculate the item correlation coefficient between each test item and each test condition based on the performance characteristic vector of each test item of each test motor included in the test motor cluster under the test condition, and determine the test item corresponding to the test motor cluster under the test condition; The test items corresponding to the test motor cluster under each test condition are used as the test items corresponding to each test motor included in the test motor cluster under each test condition; According to the structural information of the cryogenic motor to be tested, the structural information of the multiple test motors, the test conditions corresponding to each of the test motors and the test items corresponding to each test condition, the test items corresponding to each of the test conditions are determined.

2. The cryogenic motor low temperature working condition testing device according to claim 1 is characterized in that: The working condition determination module determines at least one test working condition and a test item corresponding to each test working condition based on the structural information of the cryogenic motor to be tested, including: For each of the test motor clusters, determining the central structural information of the test motor cluster according to the structural information of each test motor included in the test motor cluster; For each of the test motor clusters, determining a first central structure feature sequence corresponding to the test motor cluster according to the central structure information of the test motor cluster, wherein the first central structure feature sequence is composed of feature values ​​corresponding to a plurality of motor structure factors; For each of the motor structure factors, calculating the factor correlation coefficient of the motor structure factor according to the characteristic value of each of the test motor clusters corresponding to the motor structure factor; Determining a plurality of target motor structure factors according to the factor correlation coefficient of each of the motor structure factors; For each of the test motor clusters, determining a second central structure feature sequence corresponding to the test motor cluster according to the multiple target motor structure factors and the central structure information of the test motor cluster, wherein the second central structure feature sequence is composed of feature values ​​corresponding to the multiple target motor structure factors; Determine a structural feature sequence corresponding to the deep-cold motor to be tested according to the multiple target motor structural factors and the structural information of the deep-cold motor to be tested; Calculating the sequence difference value between the structural feature sequence corresponding to the deep-cooled motor to be tested and the second central structural feature sequence corresponding to each of the test motor clusters; Determine the test motor cluster corresponding to the deep-cold motor to be tested according to the sequence difference value between the structural feature sequence corresponding to the deep-cold motor to be tested and the second central structural feature sequence corresponding to each of the test motor clusters, and determine the at least one test condition according to the test motor cluster corresponding to the deep-cold motor to be tested; According to the test items corresponding to the test motor cluster corresponding to the deep-cooled motor to be tested under each test condition, the test items corresponding to each test condition are determined.

3. The cryogenic motor low temperature working condition testing device according to claim 1 or 2, characterized in that: The environmental simulation module includes an environmental temperature control unit, an environmental humidity control unit and an environmental atmospheric pressure control unit, wherein the environmental temperature control unit, the environmental humidity control unit and the environmental atmospheric pressure control unit are used to adjust the test environment temperature, environmental humidity and environmental atmospheric pressure according to the test conditions, and establish a simulated test environment corresponding to the test conditions.

4. The cryogenic motor low temperature working condition testing device according to claim 2, characterized in that: The data acquisition module obtains test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test conditions, including: Determine a plurality of vibration detection positions and a plurality of sound detection positions corresponding to the cryogenic motor to be tested according to the test data of the plurality of test motors for a plurality of test items under a plurality of test conditions; According to a plurality of vibration detection positions and a plurality of sound detection positions corresponding to the cryogenic motor to be tested, test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test conditions are obtained.

5. The cryogenic motor low temperature working condition testing device according to claim 4 is characterized in that: The data acquisition module determines a plurality of vibration detection positions and a plurality of sound detection positions corresponding to the cryogenic motor to be tested according to the test data of the plurality of test motors under a plurality of test conditions for a plurality of test items, including: For each test motor cluster, determine the vibration position risk coefficient between each test vibration position and the test motor cluster and the sound position risk coefficient between each test sound position and the test motor cluster according to the test data of various test items of each test motor included in the test motor cluster under various test conditions; determine multiple test vibration positions and multiple test sound positions corresponding to the test motor cluster according to the vibration position risk coefficient between each test vibration position and the test motor cluster and the sound position risk coefficient between each test sound position and the test motor cluster; According to the test motor cluster corresponding to the deep-cold motor to be tested and the multiple test vibration positions and the multiple test sound positions corresponding to each of the test motor clusters, the multiple vibration detection positions and the multiple sound detection positions corresponding to the deep-cold motor to be tested are determined.

6. The cryogenic motor low temperature working condition testing device according to claim 2, characterized in that: The data analysis module analyzes the performance of the cryogenic motor to be tested according to the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test condition, including: For each of the test motor clusters, a performance analysis model corresponding to the test motor cluster is established according to test data of various test items of each test motor included in the test motor cluster under various test conditions; According to the test motor cluster corresponding to the deep-cold motor to be tested, the performance analysis model corresponding to the test motor cluster is called to analyze the performance of the deep-cold motor to be tested based on the test data of the deep-cold motor to be tested under the simulated test environment and test items corresponding to each test condition.

7. A method for testing cryogenic motors under low temperature conditions, characterized in that: The cryogenic motor low temperature working condition testing device applied to any one of claims 1 to 6 comprises: Obtain the structural information of the deep-cooled motor to be tested; Based on the structural information of the cryogenic motor to be tested, determining at least one test condition and a test item corresponding to each test condition; For each of the test conditions, a simulation test environment corresponding to the test condition is established according to the test condition; For each of the test conditions, obtaining test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to the test condition; The performance of the cryogenic motor to be tested is analyzed based on the test data of the cryogenic motor to be tested under the simulated test environment and test items corresponding to each test condition.

Images