Low-frequency transformer performance test method and device, electronic equipment and storage medium

Abstract

The invention provides a low-frequency transformer performance testing method and device, electronic equipment and a storage medium, and relates to the technical field of low-frequency transformer performance testing. The method comprises the following steps: acquiring electrical performance parameter pretest data of each transformer sample; calculating an electrical performance parameter distribution characteristic value corresponding to the current batch of transformers; calculating a test parameter adjustment amount, and adjusting test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; and performing batch electrical performance test on the low-frequency transformer of the current batch by adopting the adjusted test parameter configuration to obtain batch electrical performance test data, and judging whether the performance of the transformer of the current batch is qualified or not according to the batch electrical performance test data. According to the method, the phenomenon of misjudgment or missed judgment caused by improper configuration of fixed parameters is effectively avoided, so that the effectiveness and the reliability of batch test results are remarkably improved, and a firmer guarantee is provided for the product quality.

Description

Technical Field

[0001] The present invention relates to the technical field of low-frequency transformer performance testing. Specifically, it relates to a method, device, electronic device, and storage medium for testing the performance of a low-frequency transformer. Background Art

[0002] In the automated production line of low-frequency transformers, to ensure that each batch of products delivered meets strict performance standards and quality requirements, comprehensive electrical performance parameter testing is an essential link. Modern production lines widely use automated testing systems to work, achieving high-speed transfer and continuous batch testing of transformers to meet the increasing production rhythm requirements.

[0003] However, in actual large-scale production practice, even for transformers with exactly the same design specifications, due to the inherent volatility and uncertainty of the manufacturing process itself, there are often inevitable subtle differences in the distribution of key electrical parameters among products of different batches. Traditional automated testing systems usually preset and adopt fixed test parameter configurations. Such an inflexible configuration strategy is difficult to effectively cope with and adapt to the parameter differences between batches. To ensure the quality of all batches of products leaving the factory, quality inspection personnel on the production line have to routinely sample and test each batch of products, and based on the sampling test results, manually adjust the various parameter configurations of the testing system by experience. This mode relying on manual intervention significantly increases the man-hour cost of the production line, reduces the inherent efficiency of automated testing, and is fundamentally contradictory to the initial goal of the automated production line to strive for high rhythm and continuous batch testing. Especially in application scenarios with extremely high requirements for production efficiency, this contradiction is particularly prominent and acute.

[0004] Therefore, how to effectively overcome the test accuracy bottleneck problem caused by product batch differences on the premise of ensuring the high-speed operation of the automated testing system has become a key technical problem that urgently needs to be solved in the automated production line of low-frequency transformers. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, device, electronic device, and storage medium for testing the performance of a low-frequency transformer, which overcomes the test accuracy bottleneck problem caused by product batch differences, effectively avoids misjudgment or missed judgment phenomena caused by improper fixed parameter configuration, and thus significantly improves the effectiveness and reliability of batch test results, providing a more solid guarantee for product quality.

[0006] In a first aspect, the present invention provides a method for testing the performance of a low-frequency transformer, which is applied to a low-frequency transformer performance testing system and includes the following steps:

[0007] S1. Extract transformer samples of the current batch of low-frequency transformers and conduct preliminary tests on electrical performance parameters to obtain preliminary test data of the electrical performance parameters of each transformer sample;

[0008] S2. Calculate the distribution characteristic values of the electrical performance parameters corresponding to the transformers of the current batch according to the preliminary test data of the electrical performance parameters of each transformer sample;

[0009] S3. Calculate the test parameter adjustment amount according to the distribution characteristic values of the electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution;

[0010] S4. Use the adjusted test parameter configuration to conduct batch electrical performance tests on the low-frequency transformers of the current batch, obtain batch electrical performance test data, and determine whether the performance of the transformers of the current batch is qualified according to the batch electrical performance test data;

[0011] S5. Generate a test report for the transformers of the current batch, and the test report includes the batch information of the transformers of the current batch, the adjusted test parameter configuration, and the batch electrical performance test data.

[0012] The low-frequency transformer performance test method provided by the present invention, for each batch of transformers to be batch-tested, before the formal batch test starts, a small number of representative transformer samples are extracted in advance for rapid preliminary tests, aiming to initially explore and master the distribution characteristics of the key performance parameters of the transformers of the current batch. Subsequently, the test system will conduct in-depth analysis on the data collected in the preliminary test stage, and based on the analysis results, the proportional-integral control algorithm can be used to adaptively adjust the key test parameter configurations in the subsequent batch test process, so that the test parameter configuration can dynamically match the actual parameter distribution characteristics of the transformers of the current batch. In this way, on the premise of ensuring that the overall test efficiency is not discounted, the accuracy and effectiveness of the test results can be significantly improved.

[0013] Further, the specific steps in step S2 include:

[0014] S21. Collect the preliminary test data of the electrical performance parameters of each transformer sample; the electrical performance parameters include no-load current, no-load voltage, and short-circuit impedance; the preliminary test data of the electrical performance parameters include no-load current data, no-load voltage data, and short-circuit impedance data;

[0015] S22. Calculate the mean and standard deviation of the no-load current according to the no-load current data to obtain the distribution characteristic value of the no-load current;

[0016] S23. Calculate the mean and standard deviation of the no-load voltage according to the no-load voltage data to obtain the distribution characteristic value of the no-load voltage;

[0017] S24. Calculate the mean and standard deviation of the short-circuit impedance based on the short-circuit impedance data to obtain the distribution characteristic values of the short-circuit impedance;

[0018] S25. Perform weighted fusion on the no-load current distribution characteristic values, the no-load voltage distribution characteristic values, and the short-circuit impedance distribution characteristic values to obtain the distribution characteristic values of the electrical performance parameters corresponding to the current batch of transformers.

[0019] Adaptively adjust the parameter configuration of the test system to adapt to the performance characteristics of different batches of transformers and ensure the accuracy and effectiveness of the test.

[0020] Further, the specific steps in step S3 include:

[0021] S31. Obtain the current electromagnetic interference intensity by monitoring the electromagnetic environment of the test station;

[0022] S32. Determine whether the electromagnetic interference intensity exceeds a preset threshold; the preset threshold is determined according to the anti-interference ability of other adjacent precision instruments;

[0023] S33. If it exceeds the preset threshold, on the premise of ensuring that the test accuracy meets the requirements, adjust the amplitude or frequency of the excitation signal to reduce the electromagnetic interference intensity until the electromagnetic interference intensity is lower than the preset threshold;

[0024] S34. Recalculate the measurement range and the measurement resolution according to the adjusted amplitude or frequency of the excitation signal and the distribution characteristic values of the electrical performance parameters.

[0025] The entire test process can effectively overcome the influence of electromagnetic interference and ensure the accuracy and reliability of the electrical performance parameter test of the low-frequency transformer.

[0026] Further, the specific steps in step S33 include:

[0027] S331. Monitor the winding temperature of the low-frequency transformer after adjusting the amplitude or frequency of the excitation signal to obtain the winding temperature rise data;

[0028] S332. Determine whether the winding temperature rise data exceeds a preset temperature rise threshold;

[0029] S333. If it exceeds the preset temperature rise threshold, adjust the adjustment step of the amplitude or frequency of the excitation signal according to the winding temperature rise data to reduce the winding temperature rise rate;

[0030] S334. If the preset temperature rise threshold is not exceeded, or after adjusting the amplitude or frequency adjustment step of the excitation signal, the winding temperature rise data is lower than the preset temperature rise threshold, then determine whether the electromagnetic interference intensity is lower than the preset threshold. If not, continue to adjust the amplitude of the excitation signal or the frequency of the excitation signal until the electromagnetic interference intensity is lower than the preset threshold.

[0031] It realizes the technical effect of ensuring the safety and reliability of the low-frequency transformer test while reducing electromagnetic interference.

[0032] Further, the specific steps in step S34 include:

[0033] S341. According to the adjusted amplitude of the excitation signal or the frequency of the excitation signal, query the preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationships between different excitation signal amplitudes, different excitation signal frequencies and different measurement ranges;

[0034] S342. Adjust the initial measurement range according to the distribution characteristic value of the electrical performance parameters to obtain the adjusted measurement range and use it as the target measurement range;

[0035] S343. Determine the measurement resolution according to the target measurement range; the measurement resolution is positively correlated with the target measurement range.

[0036] Further, the specific steps in step S342 include:

[0037] Establish an electrical performance parameter correlation matrix to characterize the correlation between three electrical performance parameters: no-load current, no-load voltage and short-circuit impedance; the electrical performance parameter correlation matrix is obtained by calculating the Pearson correlation coefficient between the electrical performance parameters based on the electrical performance parameter test data of historical batches of low-frequency transformers; the electrical performance parameter correlation matrix is visually displayed using a heat map to facilitate the analysis of the correlation strength and direction between the electrical performance parameters;

[0038] According to the electrical performance parameter correlation matrix, calculate the range adjustment coefficients of the no-load current, no-load voltage and short-circuit impedance, and weighted-correct the distribution characteristic value of the electrical performance parameters according to the range adjustment coefficients to obtain the corrected distribution characteristic value of the electrical performance parameters;

[0039] According to the corrected eigenvalue of the electrical performance parameter distribution, a multi-objective optimization model with the no-load current measurement accuracy, no-load voltage measurement accuracy, and short-circuit impedance measurement accuracy as the objective functions is constructed. The NSGA-II algorithm is used to solve the multi-objective optimization model, and a Pareto optimal solution set is calculated. A solution that meets the preset range margin constraint is selected from the Pareto optimal solution set as the target measurement range. The preset range margin constraint is that the target measurement range needs to be greater than 1.2 times the estimated maximum parameter value of each electrical performance parameter, so that the target measurement range can simultaneously meet the measurement requirements of the no-load current, no-load voltage, and short-circuit impedance, and ensure a certain measurement redundancy.

[0040] Further, the specific steps in step S343 include:

[0041] Obtain the number of bits of the analog-to-digital converter ADC of the test device;

[0042] According to the number of bits of the analog-to-digital converter ADC and the target measurement range, calculate the initial measurement resolution;

[0043] Judge whether the initial measurement resolution is lower than the preset resolution threshold;

[0044] If the initial measurement resolution is lower than the preset resolution threshold, adjust the number of bits of the analog-to-digital converter ADC, and recalculate the initial measurement resolution according to the adjusted number of bits of the analog-to-digital converter ADC until the initial measurement resolution is not lower than the preset resolution threshold, and use the adjusted initial measurement resolution as the measurement resolution.

[0045] In a second aspect, the present invention provides a low-frequency transformer performance test device, which is applied to a low-frequency transformer performance test system and includes:

[0046] A prediction module, configured to obtain pre-test data of the electrical performance parameters of each transformer sample by extracting transformer samples of the current batch of low-frequency transformers and performing pre-tests on the electrical performance parameters;

[0047] A calculation module, configured to calculate the eigenvalue of the electrical performance parameter distribution corresponding to the current batch of transformers according to the pre-test data of the electrical performance parameters of each transformer sample;

[0048] An adjustment module, configured to calculate a test parameter adjustment amount according to the eigenvalue of the electrical performance parameter distribution, and adjust the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; the test parameter configuration includes the excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution;

[0049] A judgment module, configured to perform batch electrical performance tests on the low-frequency transformers of the current batch by using the adjusted test parameter configuration, obtain batch electrical performance test data, and determine whether the performance of the transformers in the current batch is qualified according to the batch electrical performance test data;

[0050] A generation module, configured to generate a test report for the transformers in the current batch, where the test report includes batch information of the transformers in the current batch, the adjusted test parameter configuration, and the batch electrical performance test data.

[0051] The low-frequency transformer performance test device provided by the present invention can ensure that the test parameters in the batch test process match the actual characteristics of the products in the current batch, thereby effectively improving the test accuracy and efficiency. After the batch test is completed, the system automatically determines whether the performance of the transformers in the current batch is qualified according to the obtained batch electrical performance test data, ensuring the quality of the products leaving the factory.

[0052] In a third aspect, the present invention provides an electronic device, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the low-frequency transformer performance test method provided in the first aspect as described above are run.

[0053] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the low-frequency transformer performance test method provided in the first aspect as described above are run.

[0054] As can be seen from the above, the low-frequency transformer performance test method provided by the present invention, in a specific application scenario such as an automated production line for low-frequency transformers where there are strict restrictions on the beat and the pursuit of batch continuous test efficiency, when facing the challenge that the distribution of electrical performance parameters among batches shows differences due to manufacturing process fluctuations of transformers of the same specification, breaks through the limitation of the existing automated test system using a fixed parameter configuration, and constructs an automated test method that can adaptively adjust according to the parameter distribution characteristics of batch transformers, so as to effectively improve the accuracy and reliability of the test of electrical performance parameters of transformers in different batches without significantly reducing the test efficiency.

[0055] Other features and advantages of the present invention will be described in the subsequent description, and part of them will become obvious from the description, or be understood by implementing the embodiments of the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flowchart of a low-frequency transformer performance test method provided by an embodiment of the present invention.

[0057] Figure 2 It is a schematic structural diagram of a low-frequency transformer performance testing device provided by an embodiment of the present invention.

[0058] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention.

[0059] Label description:

[0060] 100, prediction module; 200, calculation module; 300, adjustment module; 400, judgment module; 500, generation module; 13, electronic device; 1301, processor; 1302, memory; 1303, communication bus. Specific implementation manners

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Usually, the components of the embodiments of the present invention described and shown here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the present invention to be protected, but only represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0062] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present invention, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0063] Refer to the attached Figure 1 , the present invention provides a low-frequency transformer performance testing method, which is applied to a low-frequency transformer performance testing system and includes the following steps:

[0064] S1. By extracting transformer samples of the current batch of low-frequency transformers and performing pre-tests on electrical performance parameters, pre-test data of the electrical performance parameters of each transformer sample is obtained;

[0065] S2. According to the pre-test data of the electrical performance parameters of each transformer sample, calculate the distribution characteristic values of the electrical performance parameters corresponding to the current batch of transformers;

[0066] S3. Calculate the test parameter adjustment amount according to the distribution characteristic values of the electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; the test parameter configuration includes the excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution;

[0067] S4. Use the adjusted test parameter configuration to conduct batch electrical performance tests on the current batch of low-frequency transformers, obtain batch electrical performance test data, and determine whether the performance of the transformers in the current batch is qualified according to the batch electrical performance test data;

[0068] S5. Generate a test report for the current batch of transformers, where the test report includes the batch information of the current batch of transformers, the adjusted test parameter configuration, and the batch electrical performance test data.

[0069] In step S1, the transformer samples are randomly selected from the current batch of low-frequency transformers, and the preliminary electrical performance test is performed on the transformer samples using the low-frequency transformer performance test system. The preliminary electrical performance test data includes, but is not limited to, no-load current data, no-load voltage data, and short-circuit impedance data.

[0070] In step S2, the distribution characteristic values of the electrical performance parameters are the results of statistical analysis of the preliminary test data, which are used to characterize the overall distribution characteristics of the electrical performance parameters of the transformers in the current batch. The distribution characteristic values can be the mean and standard deviation of the no-load current, no-load voltage, and short-circuit impedance respectively, or a comprehensive characteristic value obtained by weighted fusion of the mean and standard deviation.

[0071] In step S3, the test parameter adjustment amount can be calculated according to the distribution characteristic values of the electrical performance parameters by using the proportional-integral control algorithm. The input of the proportional-integral control algorithm is the deviation between the distribution characteristic values of the electrical performance parameters and the preset target value, and the output is the test parameter adjustment amount. The test parameter adjustment amount is used to adjust the test parameter configuration of the test system. The test parameter configuration includes the excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution. The excitation signal amplitude and excitation signal frequency affect the intensity and frequency characteristics of the test signal. The measurement range determines the parameter range that the test system can measure, and the measurement resolution determines the minimum change amount of the parameters that the test system can distinguish.

[0072] In step S4, the batch electrical performance test uses the adjusted test parameter configuration to comprehensively test all the low-frequency transformers in the current batch. The batch electrical performance test data is the basis for evaluating whether the performance of the transformers in the current batch is qualified. It is determined whether the transformer performance is qualified by comparing the batch electrical performance test data with the preset performance indicators.

[0073] In step S5, the test report is a document that records the test results of the current batch of transformers. The test report includes batch information to identify the batch of the tested transformers, the adjusted test parameter configuration to record the actual test conditions used, and the batch electrical performance test data to show the detailed test results.

[0074] Specifically, in response to the technical problems of insufficient test accuracy and low manual adjustment efficiency caused by product batch differences in the low-frequency transformer automated test system, this application proposes a low-frequency transformer performance test method. This method first extracts a part of the transformer samples of the current batch in step S1 for pre-testing to quickly obtain the preliminary data of the electrical performance parameters of this batch of transformers. Then, in step S2, statistical analysis is performed on these pre-test data, and characteristic values that can reflect the distribution characteristics of the electrical performance parameters of the current batch of transformers, such as the mean and standard deviation, are calculated. Thus, the quantitative characterization of parameter differences between batches is achieved.

[0075] Next, in step S3, a proportional-integral control algorithm can be introduced. This algorithm takes the distribution characteristic values of the electrical performance parameters calculated in step S2 as input and automatically calculates the adjustment amount of the test parameters. The test parameter configuration, including key parameters such as the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution, is automatically adjusted according to the calculated adjustment amount. The use of the proportional-integral control algorithm ensures the accuracy and stability of the test parameter adjustment, enables the test system to quickly respond to the differences between product batches, and overcomes the randomness and inefficiency problems of manual experience adjustment.

[0076] After the adaptive adjustment of the test parameters is completed, step S4 uses the adjusted test parameter configuration to perform batch electrical performance tests on all low-frequency transformers of the current batch. This ensures that the test parameters in the batch test process match the actual characteristics of the products in the current batch, thereby effectively improving the test accuracy and efficiency. After the batch test is completed, the system automatically determines whether the performance of the transformers in the current batch is qualified based on the obtained batch electrical performance test data, ensuring the quality of the factory products. Finally, in step S5, the system automatically generates a test report containing complete test information. The test report not only includes the batch information of the transformers in the current batch and the batch electrical performance test data, but also details the adjusted test parameter configuration. This makes the entire test process and results highly traceable, providing strong data support for subsequent quality management and problem tracing.

[0077] In some specific embodiments, on the automated production line of low-frequency transformers, whenever a new batch is switched for testing, the automated system first randomly selects 5-10 transformer samples from this batch. These samples are automatically sent to the pre-test station, and the system uses the preset initial test parameter configuration to quickly pre-test the electrical performance parameters such as no-load current, no-load voltage, and short-circuit impedance of the sample transformers, obtaining the pre-test data of each sample. After the pre-test is completed, the system calculates the mean and standard deviation of the no-load current, no-load voltage, and short-circuit impedance respectively based on these pre-test data, and weights and fuses these six statistics according to the preset weights to obtain a comprehensive electrical performance parameter distribution characteristic value. This characteristic value is input into the proportional-integral controller and compared with the preset target characteristic value (for example, the average characteristic value of historical batches). The controller calculates the adjustment amounts of the excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution based on the deviation. The test system automatically adjusts the test parameter configuration according to these adjustment amounts. After the parameter adjustment is completed, the automated system conducts batch testing on all transformers in the current batch to obtain batch testing data. The system automatically determines whether the performance of the transformers in this batch is qualified according to the preset qualified standard, and writes the test results and the adjusted test parameter configuration into the test report, realizing the full automation and adaptive optimization of the test process.

[0078] In certain embodiments, the specific steps in step S2 include:

[0079] S21. Collect the pre-test data of the electrical performance parameters of each transformer sample; the electrical performance parameters include no-load current, no-load voltage, and short-circuit impedance; the pre-test data of the electrical performance parameters include no-load current data, no-load voltage data, and short-circuit impedance data;

[0080] S22. Calculate the mean and standard deviation of the no-load current based on the no-load current data to obtain the no-load current distribution characteristic value;

[0081] S23. Calculate the mean and standard deviation of the no-load voltage based on the no-load voltage data to obtain the no-load voltage distribution characteristic value;

[0082] S24. Calculate the mean and standard deviation of the short-circuit impedance based on the short-circuit impedance data to obtain the short-circuit impedance distribution characteristic value;

[0083] S25. Weight and fuse the no-load current distribution characteristic value, no-load voltage distribution characteristic value, and short-circuit impedance distribution characteristic value according to the following formula to obtain the electrical performance parameter distribution characteristic value corresponding to the transformers in the current batch:

[0084] D = w1(σ I / μ I ) + w2(σ V / μ V ) + w3(σZ / μ Z );

[0085] Among them, D is the distribution characteristic value of the electrical performance parameter, and σ I , σ V , σ Z are the standard deviations of the no-load current, no-load voltage, and short-circuit impedance respectively, and μ I , μ V , μ Z are the means of the no-load current, no-load voltage, and short-circuit impedance respectively. σ I / μ I represents the distribution characteristic value of the no-load current, σ V / μ V represents the distribution characteristic value of the no-load voltage, and σ Z / μ Z represents the distribution characteristic value of the short-circuit impedance. w1, w2, and w3 are the corresponding weight coefficients respectively.

[0086] In step S21, pre-test data of the electrical performance parameters of the transformer samples are collected by the test equipment, and the electrical performance parameters are limited to the no-load current, no-load voltage, and short-circuit impedance.

[0087] In steps S22 to S24, for each pre-test data of the electrical performance parameters, the mean and standard deviation are calculated respectively. The mean reflects the central tendency of the data, and the standard deviation reflects the dispersion degree of the data. By calculating the ratio of the standard deviation to the mean, the distribution characteristic value of each electrical performance parameter is obtained, and this ratio realizes the normalized representation of the data dispersion degree, which is convenient for comparing the distribution characteristic values of different electrical performance parameters.

[0088] In step S25, the distribution characteristic values of the three electrical performance parameters are integrated using the weighted fusion formula, and the weight coefficients can be set according to the relative importance of different electrical performance parameters in actual applications, realizing the flexible adjustment of the distribution characteristic value of the comprehensive electrical performance parameter.

[0089] Specifically, in this embodiment, pre-test data of no-load current, no-load voltage, and short-circuit impedance are first collected, and these data reflect the basic electrical performance information of the transformer batch. Then, the mean and standard deviation are calculated for each parameter. The mean represents the average level of the electrical performance parameters of this batch, and the standard deviation quantifies the degree of deviation of the parameter value from the mean, that is, the volatility of the parameters within the batch. By calculating the ratio of the standard deviation to the mean, a relative measure of the volatility of different parameters is achieved. Finally, these three ratios are weighted and summed to obtain the distribution characteristic value of the electrical performance parameters. The higher the distribution characteristic value of the electrical performance parameters, the greater the dispersion degree of the electrical performance parameters of the current batch of transformers, and the more significant the difference between batches. On the contrary, the lower the distribution characteristic value of the electrical performance parameters, the more concentrated the distribution of the batch parameters, and the smaller the difference between batches. Thus, in subsequent steps, the parameter configuration of the test system can be adaptively adjusted based on the magnitude of the distribution characteristic value of the electrical performance parameters to adapt to the performance characteristics of different batches of transformers and ensure the accuracy and effectiveness of the test.

[0090] In some embodiments, the specific steps in step S3 include:

[0091] S31. By monitoring the electromagnetic environment of the test station, obtain the current electromagnetic interference intensity;

[0092] S32. Determine whether the electromagnetic interference intensity exceeds a preset threshold; the preset threshold is determined according to the anti-interference ability of other nearby precision instruments;

[0093] S33. If it exceeds the preset threshold, then on the premise of ensuring that the test accuracy meets the requirements, adjust the amplitude or frequency of the excitation signal to reduce the electromagnetic interference intensity until the electromagnetic interference intensity is lower than the preset threshold;

[0094] S34. According to the adjusted amplitude or frequency of the excitation signal, and the distribution characteristic value of the electrical performance parameters, recalculate the measurement range and measurement resolution.

[0095] In step S31, the monitoring of the electromagnetic environment is achieved by deploying electromagnetic interference sensors near the test station. The sensors collect the electromagnetic wave intensity data around the test station in real time and transmit the data to the system controller. The system controller analyzes and processes the received electromagnetic wave intensity data to obtain the electromagnetic interference intensity value of the current test station.

[0096] In step S32, the preset threshold is the critical value of the electromagnetic interference intensity, and the setting of this value takes into account the anti-interference ability of the precision instruments around the test system. Specifically, the preset threshold can be set to be slightly lower than the maximum tolerable electromagnetic interference intensity value of the most sensitive precision instrument around, so as to ensure that the test system operates in a relatively safe electromagnetic environment.

[0097] In step S33, the adjustment of the amplitude or frequency of the excitation signal to reduce the electromagnetic interference intensity can be achieved in various ways. For example, reducing the amplitude of the excitation signal will directly reduce the electromagnetic energy radiated by the test system, thereby reducing the electromagnetic interference intensity. Adjusting the excitation signal frequency can avoid the interference frequency band in the electromagnetic environment, thereby reducing the electromagnetic interference at a specific frequency. Ensuring that the test accuracy meets the requirements is the prerequisite for adjusting the excitation signal parameters. Therefore, the adjustment amplitude and frequency need to be within the range that ensures the accuracy of the test results.

[0098] In step S34, the recalculation of the measurement range and measurement resolution is based on the adjusted excitation signal parameters and the eigenvalue of the electrical performance parameter distribution characteristics. The change in the amplitude or frequency of the excitation signal will affect the sensitivity and measurable range of the test system to the electrical performance parameters. Therefore, the measurement range needs to be adjusted according to the actual excitation signal parameters to match the optimal test range. As an embodiment of the measurement accuracy, the measurement resolution also needs to be adapted to the adjusted measurement range to ensure that the required test accuracy can still be obtained under the new measurement range.

[0099] Specifically, for the problem that the electromagnetic environment interference may affect the test accuracy, this solution realizes the real-time evaluation of the electromagnetic interference intensity at the test station by adding an electromagnetic environment monitoring link. When the monitored electromagnetic interference intensity exceeds the preset threshold, the system can automatically adjust the amplitude or frequency of the excitation signal to actively reduce the electromagnetic interference. This adjustment is carried out on the premise that the test accuracy is basically not affected, avoiding sacrificing the accuracy of the test results due to excessive reduction of the excitation signal intensity. Actively reducing the electromagnetic interference intensity can also avoid affecting the use of surrounding precision instruments, which is beneficial to ensuring the test accuracy of surrounding instruments. After completing the anti-electromagnetic interference adjustment, the system will also recalculate and optimize the measurement range and measurement resolution according to the adjusted excitation signal parameters to ensure that the test system can still maintain the best test performance under the new excitation signal configuration. Thus, the entire test process can effectively overcome the influence of electromagnetic interference and ensure the accuracy and reliability of the electrical performance parameter test of the low-frequency transformer.

[0100] In some specific embodiments, the electromagnetic interference sensor is selected as a high-sensitivity electromagnetic field probe and installed about 0.5 meters directly above the performance test station of the low-frequency transformer to continuously monitor the electromagnetic radiation level near the station. The preset threshold is set at 3 V / m, which is determined based on the electromagnetic interference resistance of a high-precision spectrum analyzer in the test workshop. When the electromagnetic interference intensity exceeds 3 V / m, the test system preferentially reduces the amplitude of the excitation signal by 5% each time and simultaneously monitors the electromagnetic interference intensity until the electromagnetic interference intensity drops below 3 V / m. As a preferred embodiment, if the electromagnetic interference intensity is still higher than 3 V / m when the amplitude of the excitation signal is reduced to 80% of the initial value, the system starts to adjust the frequency of the excitation signal, adjusting it by 1 Hz each time and performing a scanning adjustment within the range of ±5 Hz, also with the goal of the electromagnetic interference intensity being lower than 3 V / m. After the parameters of the excitation signal are adjusted, the system recalculates the measurement range through a proportional-integral control algorithm based on the new amplitude and frequency of the excitation signal, as well as the characteristic values of the electrical performance parameters of the transformers in the previous batches, and adjusts the measurement resolution to a level matching the new measurement range to ensure that the test accuracy is not reduced due to the adjustment of the excitation signal. At the same time, as described above, the decrease in the electromagnetic interference intensity is also beneficial for ensuring the test accuracy of the spectrum analyzer and preventing the performance test system of the low-frequency transformer from affecting the normal operation of surrounding instruments.

[0101] In certain embodiments, the specific steps in step S33 include:

[0102] S331. Monitor the winding temperature of the low-frequency transformer after adjusting the amplitude or frequency of the excitation signal, and obtain the winding temperature rise data;

[0103] S332. Determine whether the winding temperature rise data exceeds the preset temperature rise threshold;

[0104] S333. If it exceeds the preset temperature rise threshold, then adjust the adjustment step of the amplitude or frequency of the excitation signal according to the winding temperature rise data to reduce the winding temperature rise rate;

[0105] S334. If it does not exceed the preset temperature rise threshold, or after adjusting the adjustment step of the amplitude or frequency of the excitation signal, the winding temperature rise data is lower than the preset temperature rise threshold, then determine whether the electromagnetic interference intensity is lower than the preset threshold. If not, continue to adjust the amplitude or frequency of the excitation signal until the electromagnetic interference intensity is lower than the preset threshold.

[0106] In step S331, the monitoring of the winding temperature can be achieved through a temperature sensor, which is configured to contact or be close to the winding of the low-frequency transformer to collect the winding temperature data in real time.

[0107] In step S332, the preset temperature rise threshold is the upper safety temperature limit set according to the temperature resistance grade of the insulation material of the low-frequency transformer and the requirements for long-term operation reliability.

[0108] In step S333, the adjustment strategy for the adjustment step size can be that when the winding temperature rise rate is high, the adjustment step size of the excitation signal amplitude or frequency is reduced. Conversely, when the winding temperature rise rate is low, the adjustment step size can be appropriately increased to more quickly achieve the goal of reducing the electromagnetic interference intensity.

[0109] In step S334, if the winding temperature does not exceed the preset temperature rise threshold, but the electromagnetic interference intensity is still higher than the preset threshold, the excitation signal amplitude or frequency is continuously fine-tuned until the electromagnetic interference intensity drops to an acceptable level.

[0110] Specifically, in this embodiment, a monitoring and control mechanism for the winding temperature during the process of adjusting the excitation signal is added. When adjusting the excitation signal amplitude or frequency to reduce electromagnetic interference, the system will real-time monitor the temperature change of the transformer winding. If it is detected that there is a risk that the winding temperature exceeds the preset temperature rise threshold, the system will actively reduce the amplitude of the excitation signal adjustment, reduce the speed of the winding temperature rise, and avoid damage to the transformer due to overheating. Only on the premise that the winding temperature is effectively controlled, the system will continue to adjust the excitation signal until the electromagnetic interference intensity is reduced to a level that meets the test requirements. Thus, this embodiment achieves the technical effect of ensuring the test safety and reliability of the low-frequency transformer while reducing electromagnetic interference.

[0111] In some specific embodiments, the preset temperature rise threshold is set to 80 degrees Celsius. In step S331, a thermocouple temperature sensor is attached to the surface of the low-frequency transformer winding to collect the winding temperature rise data at a frequency of once per second. In step S333, when the winding temperature rise data exceeds 80 degrees Celsius, the adjustment step size of the excitation signal amplitude is reduced from the original 5% per adjustment to 1% per adjustment, and the adjustment step size of the frequency is reduced from the original 1 Hz per adjustment to 0.2 Hz per adjustment, so as to gradually adjust the excitation signal with a smaller amplitude, thereby slowing down the winding temperature rise rate. Through this refined adjustment step size control, the rapid rise of the winding temperature can be effectively avoided, ensuring the safety of the low-frequency transformer during the test.

[0112] In certain embodiments, the specific steps in step S34 include:

[0113] S341. According to the adjusted excitation signal amplitude or excitation signal frequency, query the preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationships between different excitation signal amplitudes, different excitation signal frequencies, and different measurement ranges;

[0114] S342. Adjust the initial measurement range according to the distribution eigenvalue of the electrical performance parameters to obtain the adjusted measurement range, which is used as the target measurement range.

[0115] S343. Determine the measurement resolution according to the target measurement range; the measurement resolution is positively correlated with the target measurement range.

[0116] In this embodiment, the mapping table can be established as follows: Conduct multiple experiments in advance. For different combinations of the excitation signal amplitude and the excitation signal frequency, test the measurement range that can ensure the test accuracy, and record these corresponding relationships in the mapping table. In step S341, by querying this mapping table, an initial measurement range that matches the current excitation signal parameters can be quickly obtained, realizing the preliminary and rapid setting of the measurement range.

[0117] Furthermore, after obtaining the initial measurement range, in step S342, adjust the initial measurement range according to the distribution eigenvalue of the electrical performance parameters. The distribution eigenvalue of the electrical performance parameters reflects the overall distribution of the electrical performance parameters of the current batch of transformers. For example, if the distribution eigenvalue indicates that the parameter values of the current batch of transformers are generally large, the measurement range can be appropriately expanded; conversely, if the parameter values are generally small, the measurement range can be appropriately reduced. This adjustment can be carried out in various ways such as proportional adjustment and segmented adjustment. The purpose is to make the measurement range more suitable for the actual parameter distribution of the current batch of transformers, improving the measurement accuracy and sensitivity.

[0118] Thus, in step S343, the measurement resolution is determined according to the target measurement range. The measurement resolution is positively correlated with the target measurement range. It can be understood that when the measurement range increases, the measurement resolution can be appropriately increased; conversely, when the measurement range decreases, the measurement resolution needs to be reduced. This positive correlation can be achieved through various methods such as preset functions and look-up tables. For example, a resolution calculation formula can be preset: resolution = target measurement range / fixed coefficient, where the fixed coefficient can be determined according to the accuracy requirements of the test system and the hardware configuration. In this way, it can be ensured that the measurement resolution can be maintained at a reasonable level under different measurement ranges, taking into account both the measurement accuracy and the test efficiency.

[0119] Specifically, during the performance test of the low-frequency transformer, first, the test system queries the pre-established mapping table according to the adjusted excitation signal amplitude and excitation signal frequency. For example, the excitation signal amplitude is adjusted to 10V, and the excitation signal frequency is adjusted to 50Hz. The mapping table records the corresponding relationships between different combinations of excitation signal parameters and the measurement range. For example, when the excitation signal amplitude is 10V and the frequency is 50Hz, the mapping table indicates that the initial measurement range is 1A.

[0120] Then, the system obtains the distribution characteristic value of the electrical performance parameters of the current batch of transformers. Assume that this characteristic value indicates that the overall electrical performance parameters of the current batch of transformers are on the high side. Based on this characteristic value, the system adjusts the initial measurement range of 1A. For example, through the proportional-integral control algorithm, the calculated range adjustment coefficient is 1.2, and the target measurement range is adjusted to 1.2A.

[0121] Finally, according to the target measurement range of 1.2A, the system determines the measurement resolution. Assume that the positive correlation relationship between the preset resolution and the range of the system is: resolution = range / 1000. Then when the target measurement range is 1.2A, the measurement resolution is determined to be 0.0012A. Through the above steps, the test system can quickly and automatically set the measurement range and measurement resolution that are adapted to the adjusted excitation signal and the parameter distribution of the current batch of transformers, ensuring the accuracy and effectiveness of the test.

[0122] In some specific embodiments, the mapping table can be stored in the form of a database or a spreadsheet and supports fast query operations. The distribution characteristic value of the electrical performance parameters can be calculated using a weighted fusion algorithm, comprehensively considering the distribution of multiple electrical performance parameters such as no-load current, no-load voltage, and short-circuit impedance. The calculation of the range adjustment coefficient can use the proportional-integral control algorithm, and the range adjustment coefficient is dynamically adjusted according to the deviation between the distribution characteristic value of the electrical performance parameters and the preset target value. The positive correlation relationship between the measurement resolution and the target measurement range can be defined by a piecewise function. In different range ranges, different resolution calculation formulas are used to achieve more refined resolution adjustment. Through the above specific embodiments, the accuracy and flexibility of setting the measurement range and measurement resolution can be further improved, better adapting to the automated performance test requirements of different batches and different specifications of low-frequency transformers.

[0123] In certain embodiments, the specific steps in step S342 include:

[0124] Establish an electrical performance parameter correlation matrix to characterize the correlation between three electrical performance parameters: no-load current, no-load voltage, and short-circuit impedance; the electrical performance parameter correlation matrix is obtained by calculating the Pearson correlation coefficient between each electrical performance parameter based on the electrical performance parameter test data of historical batches of low-frequency transformers; the electrical performance parameter correlation matrix is visually displayed using a heat map to facilitate the analysis of the correlation strength and direction between each electrical performance parameter;

[0125] According to the electrical performance parameter correlation matrix, calculate the range adjustment coefficients of the no-load current, no-load voltage, and short-circuit impedance, and weighted-correct the distribution characteristic value of the electrical performance parameters according to the range adjustment coefficients to obtain the corrected distribution characteristic value of the electrical performance parameters;

[0126] According to the corrected eigenvalue of the electrical performance parameter distribution, a multi-objective optimization model with the measurement accuracy of no-load current, the measurement accuracy of no-load voltage, and the measurement accuracy of short-circuit impedance as the objective functions is constructed. The NSGA-II algorithm is used to solve the multi-objective optimization model, and the Pareto optimal solution set is calculated. Then, a solution that meets the preset range margin constraint is selected from the Pareto optimal solution set as the target measurement range. The preset range margin constraint is that the target measurement range needs to be greater than 1.2 times the estimated maximum parameter value of each electrical performance parameter, so that the target measurement range can simultaneously meet the measurement requirements of no-load current, no-load voltage, and short-circuit impedance, and ensure a certain measurement redundancy.

[0127] In this embodiment, for the establishment of the electrical performance parameter correlation matrix, the test data of the electrical performance parameters of the stored historical batches of low-frequency transformers can be used. Specifically, the test data of the no-load current, no-load voltage, and short-circuit impedance of multiple past batches of transformers are collected to form a data set. Then, for every two electrical performance parameters, such as no-load current and no-load voltage, the Pearson correlation coefficient formula is used to calculate the correlation coefficient between them. The value range of the calculation result of the Pearson correlation coefficient is from -1 to 1. A value close to 1 indicates a strong positive correlation, a value close to -1 indicates a strong negative correlation, and a value close to 0 indicates a weak correlation. The Pearson correlation coefficients between each pair of parameters calculated are organized in the form of a matrix, that is, the electrical performance parameter correlation matrix. To more intuitively display the correlation strength and direction between parameters, the electrical performance parameter correlation matrix can be visualized as a heat map, where the heat map uses the depth of color to represent the magnitude of the correlation coefficient, and the darker the color usually indicates the stronger the correlation.

[0128] For the calculation of the range adjustment coefficient, it can be based on the correlation coefficient in the electrical performance parameter correlation matrix. For example, if there is a strong positive correlation between no-load current and short-circuit impedance, then when adjusting the measurement range of no-load current, the distribution eigenvalue of short-circuit impedance needs to be considered, and the range adjustment coefficient can be designed to be proportional to the magnitude of the correlation coefficient. The purpose of weighted correction of the electrical performance parameter distribution eigenvalue by the range adjustment coefficient is to make the corrected eigenvalue comprehensively reflect the distribution characteristics of each parameter and the mutual influence between parameters.

[0129] For the construction and solution of the multi-objective optimization model, first, clarify that the optimization objectives are to simultaneously improve the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance. These measurement accuracies can be quantified as objective functions. For example, indicators such as the reciprocal of the measurement error or the signal-to-noise ratio can be used to characterize the measurement accuracy. Then, use the NSGA-II algorithm to solve the constructed multi-objective optimization model. The NSGA-II algorithm is a commonly used evolutionary algorithm suitable for solving multi-objective optimization problems. It can search for a set of Pareto optimal solution sets, which represent the optimal solution sets that balance different objectives, that is, when improving one objective function, at least the other objective functions will not be reduced. Finally, from the Pareto optimal solution set obtained by the NSGA-II algorithm, select the solution that satisfies the preset range margin constraint as the target measurement range. The specific implementation method of the preset range margin constraint can be, for each electrical performance parameter, calculate its estimated maximum parameter value. For example, the mean plus several times the standard deviation can be used to estimate the maximum parameter value. Then, ensure that the selected target measurement range is greater than 1.2 times the estimated maximum parameter value of each electrical performance parameter. The margin coefficient of 1.2 is selected to ensure that the target measurement range can cover the fluctuation range of the parameters and reserve a certain measurement redundancy, so as to meet the measurement requirements of no-load current, no-load voltage, and short-circuit impedance at the same time.

[0130] Specifically, in this embodiment, first, by establishing an electrical performance parameter correlation matrix, the scheme can effectively analyze and quantify the mutual correlation between the three electrical performance parameters of no-load current, no-load voltage, and short-circuit impedance. The establishment of the electrical performance parameter correlation matrix enables the range adjustment to no longer consider the distribution characteristic values of individual parameters in isolation, but to comprehensively consider the mutual influence between parameters. Secondly, through the range adjustment coefficient and weighted correction, the distribution characteristic values of electrical performance parameters are further optimized. The corrected characteristic values can more comprehensively reflect the overall parameter distribution characteristics and provide a more accurate basis for subsequent range adjustment. Then, by constructing a multi-objective optimization model and adopting the NSGA-II algorithm, the scheme realizes the trade-off and optimization between multiple measurement accuracy objectives. The NSGA-II algorithm can search for a set of Pareto optimal solution sets, providing more selection space and decision-making basis for range selection. Finally, through the preset range margin constraint, the target measurement range selected from the Pareto optimal solution set can not only meet the measurement requirements of each parameter, but also ensure a certain measurement redundancy, avoiding the parameter fluctuation exceeding the range, and ensuring the reliability of the measurement. Thus, this embodiment realizes a more accurate and reliable measurement range adjustment by comprehensively considering the correlation between electrical performance parameters, optimizing the measurement accuracy, and ensuring the range margin, and solves the test accuracy bottleneck problem mentioned in the background technology caused by product batch differences and traditional fixed range configuration strategies.

[0131] In some specific embodiments, it is assumed that the test data of the electrical performance parameters of the historical batch of low-frequency transformers is used to construct an association matrix of electrical performance parameters. Through calculation, the Pearson correlation coefficient between the no-load current and the short-circuit impedance is 0.8, indicating a strong positive correlation between the two; the Pearson correlation coefficient between the no-load voltage and the no-load current is 0.2, indicating a weak correlation between the two; the Pearson correlation coefficient between the no-load voltage and the short-circuit impedance is -0.1, indicating that the two are almost uncorrelated. Based on this association matrix, the range adjustment coefficients are set as follows: the range adjustment coefficient of the no-load current is 1.2, the range adjustment coefficient of the short-circuit impedance is 1.1, and the range adjustment coefficient of the no-load voltage is 1.0. When the distribution characteristic values of the electrical performance parameters of the new batch of transformers are calculated, for example, the distribution characteristic value of the no-load current is 0.05, the distribution characteristic value of the no-load voltage is 0.02, and the distribution characteristic value of the short-circuit impedance is 0.03, then the corrected distribution characteristic values of the electrical performance parameters are: the corrected distribution characteristic value of the no-load current = 0.05 * 1.2 = 0.06, the corrected distribution characteristic value of the short-circuit impedance = 0.03 * 1.1 = 0.033, and the corrected distribution characteristic value of the no-load voltage = 0.02 * 1.0 = 0.02. Then, using the corrected distribution characteristic values of the electrical performance parameters as inputs, a multi-objective optimization model is constructed, with the objective functions being the measurement accuracy of the no-load current, the measurement accuracy of the no-load voltage, and the measurement accuracy of the short-circuit impedance. The NSGA-II algorithm is used to solve this model to obtain the Pareto optimal solution set. Suppose a solution selected from the Pareto optimal solution set corresponds to the following target measurement ranges: the no-load current measurement range is 1 A, the no-load voltage measurement range is 10 V, and the short-circuit impedance measurement range is 10 Ω. The preset range margin constraint is set to 1.2 times, and it is necessary to verify whether the selected ranges are greater than 1.2 times the estimated maximum parameter values of each electrical performance parameter. Suppose the estimated maximum no-load current is 0.8 A, the maximum no-load voltage is 8 V, and the maximum short-circuit impedance is 8 Ω. Then the 1.2-fold margin constraints are 0.96 A, 9.6 V, and 9.6 Ω respectively. Since the selected ranges of 1 A, 10 V, and 10 Ω are all greater than the corresponding margin constraint values, this solution satisfies the preset range margin constraint and is finally determined as the target measurement range.

[0132] In certain embodiments, the specific steps in step S343 include:

[0133] Obtain the number of bits N of the analog-to-digital converter (ADC) of the test equipment;

[0134] According to the number of bits N of the analog-to-digital converter (ADC) and the target measurement range, calculate the initial measurement resolution according to the following formula: R = L / 2 N ; where R is the initial measurement resolution, L is the target measurement range, and N is the number of bits of the analog-to-digital converter (ADC);

[0135] Determine whether the initial measurement resolution is lower than the preset resolution threshold;

[0136] If the initial measurement resolution is lower than the preset resolution threshold, adjust the number of bits of the analog-to-digital converter (ADC), and recalculate the initial measurement resolution according to the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold, and use the adjusted initial measurement resolution as the measurement resolution.

[0137] This embodiment clearly states that it is necessary to obtain the number of bits of the analog-to-digital converter (ADC) of the test device, which is the basis for calculating the initial measurement resolution. The number of bits of the ADC determines the minimum voltage or current change that the test system can resolve. The higher the number of bits, the greater the resolution potential. This formula clearly shows that the initial measurement resolution is directly proportional to the target measurement range and inversely proportional to the number of bits of the ADC exponentially. When the target measurement range is determined, the number of bits of the ADC directly determines the magnitude of the initial measurement resolution.

[0138] This embodiment adds a judgment step, that is, to judge whether the initial measurement resolution is lower than the preset resolution threshold. The preset resolution threshold is a minimum acceptable resolution level set according to the actual test accuracy requirements. If the initial measurement resolution is lower than the preset resolution threshold, the solution proposes to adjust the number of bits of the ADC and recalculate the initial measurement resolution until the initial measurement resolution is not lower than the preset resolution threshold. This means that when the number of bits of the ADC in the hardware is not sufficient to provide sufficient resolution, the measurement resolution can be improved by adjusting the number of bits of the ADC, so as to ensure that the final measurement resolution can meet the test accuracy requirements, and use the adjusted initial measurement resolution as the final measurement resolution, ensuring the effectiveness and reliability of the measurement resolution.

[0139] Specifically, first, the test system reads the number of bits of the analog-to-digital converter (ADC) from the hardware configuration. For example, it reads that the ADC has 12 bits. Then, the system adopts the target measurement range. For example, the target measurement range is 10 A. According to the above formula, the initial measurement resolution is calculated to be approximately equal to 2.4 mA. The system presets a resolution threshold. For example, the preset resolution threshold is 3 mA. The system compares the initial measurement resolution of 2.4 mA with the preset resolution threshold of 3 mA. Since 2.4 mA is less than 3 mA, the initial measurement resolution is lower than the preset resolution threshold. At this time, the system adjusts the number of bits of the analog-to-digital converter (ADC). For example, it adjusts the ADC to 10 bits. According to the adjusted number of bits of the ADC, the initial measurement resolution is recalculated to be approximately equal to 9.7 mA. The recalculated initial measurement resolution of 9.7 mA is compared with the preset resolution threshold of 3 mA again. Since 9.7 mA is greater than 3 mA, the initial measurement resolution is not lower than the preset resolution threshold. Therefore, the system takes the adjusted initial measurement resolution of 9.7 mA as the final measurement resolution. Through the above steps, it is ensured that the measurement resolution meets the test accuracy requirements, improving the quality and efficiency of the low-frequency transformer performance test.

[0140] In some specific embodiments, the test device is configured with an analog-to-digital converter (ADC) with variable number of bits. The test system can automatically adjust the number of bits of the analog-to-digital converter (ADC) according to the comparison result between the calculated initial measurement resolution and the preset resolution threshold. For example, when the initial measurement resolution is lower than the threshold, the control system commands the hardware to switch to an ADC with a higher number of bits for data acquisition. As a preferred embodiment, the oversampling technique can be used to adjust the number of bits of the analog-to-digital converter (ADC). Without replacing the hardware ADC, the number of bits of the ADC can be equivalently increased by averaging multiple samples, improving the measurement resolution. Thus, under the limitation of hardware conditions, the measurement resolution can be flexibly adjusted to meet the test requirements of different accuracy levels.

[0141] Please refer to Figure 2 , Figure 2 which is a low-frequency transformer performance test device in some embodiments of the present invention. It is applied to a low-frequency transformer performance test system and is integrated in the backend control device in the form of a computer program, including:

[0142] A prediction module 100, configured to obtain the pre-test data of the electrical performance parameters of each transformer sample by extracting the transformer samples of the current batch of low-frequency transformers and performing pre-tests on the electrical performance parameters;

[0143] A calculation module 200, configured to calculate the distribution characteristic values of the electrical performance parameters corresponding to the current batch of transformers according to the pre-test data of the electrical performance parameters of each transformer sample;

[0144] An adjustment module 300 is configured to calculate an adjustment amount of test parameters according to the distribution characteristic values of electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance test system based on the adjustment amount of the test parameters; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution.

[0145] A judgment module 400 is configured to perform batch electrical performance tests on the low-frequency transformers of the current batch by using the adjusted test parameter configuration, obtain batch electrical performance test data, and determine whether the performance of the transformers of the current batch is qualified according to the batch electrical performance test data.

[0146] A generation module 500 is configured to generate a test report for the transformers of the current batch, and the test report includes the batch information of the transformers of the current batch, the adjusted test parameter configuration, and the batch electrical performance test data.

[0147] In some embodiments, when the calculation module 200 calculates the distribution characteristic values of the electrical performance parameters corresponding to the transformers of the current batch according to the pre-test data of the electrical performance parameters of each transformer sample, it performs the following steps:

[0148] S21. Collect the pre-test data of the electrical performance parameters of each transformer sample; the electrical performance parameters include no-load current, no-load voltage, and short-circuit impedance; the pre-test data of the electrical performance parameters includes no-load current data, no-load voltage data, and short-circuit impedance data.

[0149] S22. Calculate the mean and standard deviation of the no-load current according to the no-load current data to obtain the no-load current distribution characteristic value.

[0150] S23. Calculate the mean and standard deviation of the no-load voltage according to the no-load voltage data to obtain the no-load voltage distribution characteristic value.

[0151] S24. Calculate the mean and standard deviation of the short-circuit impedance according to the short-circuit impedance data to obtain the short-circuit impedance distribution characteristic value.

[0152] S25. Weight and fuse the no-load current distribution characteristic value, the no-load voltage distribution characteristic value, and the short-circuit impedance distribution characteristic value according to the following formula to obtain the distribution characteristic value of the electrical performance parameters corresponding to the transformers of the current batch:

[0153] D = w1(σ I / μ I ) + w2(σ V / μ V ) + w3(σ Z / μ Z );

[0154] where D is the distribution characteristic value of the electrical performance parameters, σ I , σ V , σZ They are the standard deviations of the no-load current, no-load voltage, and short-circuit impedance, respectively, μ I , μ V , μ Z They are the means of the no-load current, no-load voltage, and short-circuit impedance, respectively, σ I / μ I is expressed as the distribution characteristic value of the no-load current, σ V / μ V is expressed as the distribution characteristic value of the no-load voltage, σ Z / μ Z is expressed as the distribution characteristic value of the short-circuit impedance. w1, w2, and w3 are the corresponding weight coefficients respectively.

[0155] In some embodiments, when the adjustment module 300 is used to calculate the test parameter adjustment amount according to the distribution characteristic value of the electrical performance parameter and adjust the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount, it performs:

[0156] S31. By monitoring the electromagnetic environment of the test station, obtain the current electromagnetic interference intensity;

[0157] S32. Determine whether the electromagnetic interference intensity exceeds a preset threshold; the preset threshold is determined according to the anti-interference ability of other nearby precision instruments;

[0158] S33. If it exceeds the preset threshold, then on the premise of ensuring that the test accuracy meets the requirements, adjust the amplitude or frequency of the excitation signal to reduce the electromagnetic interference intensity until the electromagnetic interference intensity is lower than the preset threshold;

[0159] S34. According to the adjusted amplitude or frequency of the excitation signal, and the distribution characteristic value of the electrical performance parameter, recalculate the measurement range and measurement resolution.

[0160] In some embodiments, when the adjustment module 300 is used to adjust the amplitude or frequency of the excitation signal on the premise of ensuring that the test accuracy meets the requirements to reduce the electromagnetic interference intensity until the electromagnetic interference intensity is lower than the preset threshold, it performs:

[0161] S331. Monitor the winding temperature of the low-frequency transformer after adjusting the amplitude or frequency of the excitation signal, and obtain the winding temperature rise data;

[0162] S332. Determine whether the winding temperature rise data exceeds a preset temperature rise threshold;

[0163] S333. If it exceeds the preset temperature rise threshold, then according to the winding temperature rise data, adjust the adjustment step size of the amplitude or frequency of the excitation signal to reduce the winding temperature rise rate;

[0164] S334. If the preset temperature rise threshold is not exceeded, or after adjusting the amplitude or frequency adjustment step of the excitation signal, the winding temperature rise data is lower than the preset temperature rise threshold, then determine whether the electromagnetic interference intensity is lower than the preset threshold. If not, continue to adjust the amplitude or frequency of the excitation signal until the electromagnetic interference intensity is lower than the preset threshold.

[0165] In some embodiments, when the adjustment module 300 is used to recalculate the measurement range and measurement resolution according to the adjusted amplitude or frequency of the excitation signal and the distribution characteristic value of the electrical performance parameters, it performs:

[0166] S341. According to the adjusted amplitude or frequency of the excitation signal, query the preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationships between different excitation signal amplitudes, different excitation signal frequencies and different measurement ranges;

[0167] S342. Adjust the initial measurement range according to the distribution characteristic value of the electrical performance parameters to obtain the adjusted measurement range and use it as the target measurement range;

[0168] S343. Determine the measurement resolution according to the target measurement range; the measurement resolution is positively correlated with the target measurement range.

[0169] In some embodiments, when the adjustment module 300 is used to adjust the initial measurement range according to the distribution characteristic value of the electrical performance parameters to obtain the adjusted measurement range and use it as the target measurement range, it performs:

[0170] Establish an electrical performance parameter correlation matrix to characterize the correlation between three electrical performance parameters: no-load current, no-load voltage and short-circuit impedance; the electrical performance parameter correlation matrix is obtained by calculating the Pearson correlation coefficients between the electrical performance parameters based on the electrical performance parameter test data of historical batches of low-frequency transformers; the electrical performance parameter correlation matrix is visually displayed using a heat map to facilitate the analysis of the correlation strength and direction between the electrical performance parameters;

[0171] According to the electrical performance parameter correlation matrix, calculate the range adjustment coefficients of the no-load current, no-load voltage and short-circuit impedance, and perform weighted correction on the distribution characteristic value of the electrical performance parameters according to the range adjustment coefficients to obtain the corrected distribution characteristic value of the electrical performance parameters;

[0172] According to the corrected distribution characteristic values of electrical performance parameters, a multi-objective optimization model with the measurement accuracies of no-load current, no-load voltage, and short-circuit impedance as the objective functions is constructed. The NSGA-II algorithm is used to solve the multi-objective optimization model, and the Pareto optimal solution set is calculated. Then, the solution that meets the preset range margin constraint is selected from the Pareto optimal solution set as the target measurement range. The preset range margin constraint is that the target measurement range needs to be greater than 1.2 times the estimated maximum parameter value of each electrical performance parameter, so that the target measurement range can simultaneously meet the measurement requirements of no-load current, no-load voltage, and short-circuit impedance, and ensure a certain measurement redundancy.

[0173] In some embodiments, when the adjustment module 300 is used to determine the measurement resolution according to the target measurement range, it performs:

[0174] Obtain the number of bits N of the analog-to-digital converter (ADC) of the test device;

[0175] According to the number of bits N of the analog-to-digital converter (ADC) and the target measurement range, calculate the initial measurement resolution according to the following formula: R = L / 2 N ; where R is the initial measurement resolution, L is the target measurement range, and N is the number of bits of the analog-to-digital converter (ADC);

[0176] Judge whether the initial measurement resolution is lower than the preset resolution threshold;

[0177] If the initial measurement resolution is lower than the preset resolution threshold, adjust the number of bits N of the analog-to-digital converter (ADC), and recalculate the initial measurement resolution according to the adjusted number of bits N of the analog-to-digital converter (ADC) until the initial measurement resolution is not lower than the preset resolution threshold, and use the adjusted initial measurement resolution as the measurement resolution.

[0178] Please refer to Figure 3 , Figure 3A structural schematic diagram of an electronic device provided by an embodiment of the present invention. The present invention provides an electronic device 13, including: a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other through a communication bus 1303 and / or other forms of connection mechanisms (not marked). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device runs, the processor 1301 executes the computer-readable instructions to perform the low-frequency transformer performance testing method in any optional implementation manner of the above embodiments, so as to implement the following functions: by extracting transformer samples of the current batch of low-frequency transformers and performing pre-tests on electrical performance parameters, obtaining pre-test data of electrical performance parameters of each transformer sample; according to the pre-test data of electrical performance parameters of each transformer sample, calculating electrical performance parameter distribution characteristic values corresponding to the current batch of transformers; according to the electrical performance parameter distribution characteristic values, calculating a test parameter adjustment amount, and adjusting the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution; using the adjusted test parameter configuration, performing batch electrical performance testing on the current batch of low-frequency transformers, obtaining batch electrical performance test data, and determining whether the performance of the current batch of transformers is qualified according to the batch electrical performance test data; generating a test report for the current batch of transformers, where the test report includes batch information of the current batch of transformers, the adjusted test parameter configuration, and the batch electrical performance test data.

[0179] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it performs the low-frequency transformer performance testing method in any optional implementation manner of the above embodiments, so as to implement the following functions: by extracting transformer samples of the current batch of low-frequency transformers and performing pre-tests on electrical performance parameters, obtaining pre-test data of electrical performance parameters of each transformer sample; according to the pre-test data of electrical performance parameters of each transformer sample, calculating electrical performance parameter distribution characteristic values corresponding to the current batch of transformers; according to the electrical performance parameter distribution characteristic values, calculating a test parameter adjustment amount, and adjusting the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution; using the adjusted test parameter configuration, performing batch electrical performance testing on the current batch of low-frequency transformers, obtaining batch electrical performance test data, and determining whether the performance of the current batch of transformers is qualified according to the batch electrical performance test data; generating a test report for the current batch of transformers, where the test report includes batch information of the current batch of transformers, the adjusted test parameter configuration, and the batch electrical performance test data.

[0180] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0181] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be in electrical, mechanical or other forms.

[0182] In addition, the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0183] Furthermore, in each embodiment of the present invention, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0184] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0185] The above are only embodiments of the present invention and are not intended to limit the protection scope of the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for testing the performance of a low-frequency transformer, which is applied to a low-frequency transformer performance testing system, is characterized in that, Including the following steps: S1. By extracting transformer samples of the current batch of low-frequency transformers and conducting pre-tests on electrical performance parameters, obtaining pre-test data of electrical performance parameters for each transformer sample; S2. According to the pre-test data of electrical performance parameters of each transformer sample, calculating the distribution characteristic values of electrical performance parameters corresponding to the current batch of transformers; S3. According to the distribution characteristic values of the electrical performance parameters, calculating the test parameter adjustment amount, and adjusting the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution; S4. Using the adjusted test parameter configuration, conducting batch electrical performance tests on the low-frequency transformers of the current batch, obtaining batch electrical performance test data, and determining whether the performance of the transformers of the current batch is qualified according to the batch electrical performance test data; S5. Generating a test report for the transformers of the current batch, the test report including the batch information of the transformers of the current batch, the adjusted test parameter configuration, and the batch electrical performance test data.

2. The performance testing method of the low-frequency transformer according to claim 1, wherein, The specific steps in step S2 include: S21. Collecting the pre-test data of electrical performance parameters of each transformer sample; the electrical performance parameters include no-load current, no-load voltage, and short-circuit impedance; the pre-test data of the electrical performance parameters include no-load current data, no-load voltage data, and short-circuit impedance data; S22. According to the no-load current data, calculating the mean and standard deviation of the no-load current, obtaining the distribution characteristic value of the no-load current; S23. According to the no-load voltage data, calculating the mean and standard deviation of the no-load voltage, obtaining the distribution characteristic value of the no-load voltage; S24. According to the short-circuit impedance data, calculating the mean and standard deviation of the short-circuit impedance, obtaining the distribution characteristic value of the short-circuit impedance; S25. Weightedly fusing the distribution characteristic value of the no-load current, the distribution characteristic value of the no-load voltage, and the distribution characteristic value of the short-circuit impedance to obtain the distribution characteristic value of the electrical performance parameters corresponding to the current batch of transformers.

3. The performance testing method of the low-frequency transformer according to claim 1, characterized in that The specific steps in step S3 include: S31. By monitoring the electromagnetic environment of the test station, obtaining the current electromagnetic interference intensity; S32. Judging whether the electromagnetic interference intensity exceeds a preset threshold; the preset threshold is determined according to the anti-interference ability of other adjacent precision instruments; S33. If it exceeds the preset threshold, then on the premise of ensuring that the test accuracy meets the requirements, adjusting the amplitude of the excitation signal or the frequency of the excitation signal to reduce the electromagnetic interference intensity until the electromagnetic interference intensity is lower than the preset threshold; S34. According to the adjusted amplitude of the excitation signal or the frequency of the excitation signal, and the distribution characteristic values of the electrical performance parameters, recalculating the measurement range and the measurement resolution.

4. The performance testing method of the low-frequency transformer according to claim 3, wherein The specific steps in step S33 include: S331. Monitoring the winding temperature of the low-frequency transformer after adjusting the amplitude of the excitation signal or the frequency of the excitation signal, obtaining winding temperature rise data; S332. Judging whether the winding temperature rise data exceeds a preset temperature rise threshold; S333. If the preset temperature rise threshold is exceeded, adjust the amplitude of the excitation signal or the adjustment step of the excitation signal frequency according to the winding temperature rise data to reduce the winding temperature rise rate; S334. If the preset temperature rise threshold is not exceeded, or after adjusting the amplitude or frequency adjustment step of the excitation signal, the winding temperature rise data is lower than the preset temperature rise threshold, determine whether the electromagnetic interference intensity is lower than the preset threshold. If not, continue to adjust the amplitude of the excitation signal or the excitation signal frequency until the electromagnetic interference intensity is lower than the preset threshold.

5. The performance testing method of the low-frequency transformer according to claim 3, characterized in that The specific steps in step S34 include: S341. According to the adjusted amplitude of the excitation signal or the excitation signal frequency, query the preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationships between different excitation signal amplitudes, different excitation signal frequencies, and different measurement ranges; S342. Adjust the initial measurement range according to the distribution characteristic value of the electrical performance parameters to obtain the adjusted measurement range as the target measurement range; S343. Determine the measurement resolution according to the target measurement range; the measurement resolution is positively correlated with the target measurement range.

6. The performance testing method of the low-frequency transformer according to claim 5, characterized in that, The specific steps in step S342 include: Establish an electrical performance parameter correlation matrix to characterize the correlation between three electrical performance parameters: no-load current, no-load voltage, and short-circuit impedance; the electrical performance parameter correlation matrix is obtained by calculating the Pearson correlation coefficients between the electrical performance parameters based on the electrical performance parameter test data of historical batches of low-frequency transformers; the electrical performance parameter correlation matrix is visually displayed using a heat map to facilitate the analysis of the correlation strength and direction between the electrical performance parameters; According to the electrical performance parameter correlation matrix, calculate the range adjustment coefficients of the no-load current, no-load voltage, and short-circuit impedance, and weight-correct the distribution characteristic value of the electrical performance parameters according to the range adjustment coefficients to obtain the corrected distribution characteristic value of the electrical performance parameters; According to the corrected distribution characteristic value of the electrical performance parameters, construct a multi-objective optimization model with the measurement accuracies of the no-load current, no-load voltage, and short-circuit impedance as the objective functions, solve the multi-objective optimization model using the NSGA-II algorithm, calculate the Pareto optimal solution set, and select the solution that meets the preset range margin constraint from the Pareto optimal solution set as the target measurement range; the preset range margin constraint is: the target measurement range needs to be greater than 1.2 times the estimated maximum parameter value of each electrical performance parameter, so that the target measurement range can simultaneously meet the measurement requirements of the no-load current, no-load voltage, and short-circuit impedance and ensure a certain measurement redundancy.

7. The performance testing method of the low-frequency transformer according to claim 5, characterized in that The specific steps in step S343 include: Obtain the number of bits of the analog-to-digital converter ADC of the test equipment; Calculate the initial measurement resolution according to the number of bits of the analog-to-digital converter ADC and the target measurement range; Judge whether the initial measurement resolution is lower than the preset resolution threshold; If the initial measurement resolution is lower than the preset resolution threshold, adjust the number of bits of the analog-to-digital converter (ADC), and recalculate the initial measurement resolution according to the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold, and use the adjusted initial measurement resolution as the measurement resolution.

8. A low-frequency transformer performance testing device, which is applied to a low-frequency transformer performance testing system, is characterized in that It includes: A prediction module for obtaining pre-test data of the electrical performance parameters of each transformer sample by extracting transformer samples of the current batch of low-frequency transformers and performing pre-tests on the electrical performance parameters; A calculation module for calculating the distribution characteristic values of the electrical performance parameters corresponding to the current batch of transformers according to the pre-test data of the electrical performance parameters of each transformer sample; An adjustment module for calculating the test parameter adjustment amount according to the distribution characteristic values of the electrical performance parameters, and adjusting the test parameter configuration of the low-frequency transformer performance test system based on the test parameter adjustment amount; the test parameter configuration includes the amplitude of the excitation signal, the frequency of the excitation signal, the measurement range, and the measurement resolution; A judgment module for performing batch electrical performance tests on the current batch of low-frequency transformers using the adjusted test parameter configuration, obtaining batch electrical performance test data, and determining whether the performance of the current batch of transformers is qualified according to the batch electrical performance test data; A generation module for generating a test report for the current batch of transformers, the test report including the batch information of the current batch of transformers, the adjusted test parameter configuration, and the batch electrical performance test data.

9. An electronic device, characterized in that, It includes a processor and a memory, and the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the low-frequency transformer performance test method according to any one of claims 1-7 are run.

10. A computer-readable storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by the processor, the steps in the low-frequency transformer performance test method according to any one of claims 1-7 are run.

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