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

Abstract

The application provides a low-frequency transformer performance test method and device, electronic equipment and storage medium, and relates to the technical field of low-frequency transformer performance test. The method comprises the following steps: obtaining electrical performance parameter pre-test data of each transformer sample; calculating electrical performance parameter distribution characteristic values corresponding to the current batch of transformers; calculating 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; using the adjusted test parameter configuration to perform batch electrical performance test 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. The method effectively avoids the misjudgment or missed judgment phenomenon caused by improper fixed parameter configuration, thereby significantly improving the effectiveness and reliability of the batch test result, and providing a more solid guarantee for product quality.

Description

Technical Field

[0001] This invention relates to the field of low-frequency transformer performance testing technology, and more specifically, to a low-frequency transformer performance testing method, apparatus, electronic device, and storage medium. Background Technology

[0002] On automated production lines for low-frequency transformers, comprehensive electrical performance parameter testing is an indispensable step to ensure that every batch of delivered products meets stringent performance standards and quality requirements. Modern production lines widely employ automated testing systems, enabling high-speed transfer and continuous batch testing of transformers to meet the ever-increasing demands of production cycles.

[0003] However, in actual large-scale production, even transformers with identical design specifications often exhibit unavoidable subtle differences in the distribution of key electrical parameters between different batches due to the inherent volatility and uncertainty of the manufacturing process. Traditional automated testing systems typically pre-set and use fixed test parameter configurations. This unchanging configuration strategy is ill-suited to effectively address and adapt to parameter differences between batches. To ensure the quality of all batches of products leaving the factory, production line quality inspectors must routinely sample and inspect each batch, and manually adjust the test system's parameter configurations based on their experience and the results of these sampling inspections. This reliance on manual intervention significantly increases the production line's labor costs and reduces the inherent efficiency of automated testing, fundamentally contradicting the initial goal of automated production lines—high-speed, continuous batch testing. This contradiction is particularly prominent and acute in application scenarios with extreme requirements for production efficiency.

[0004] Therefore, how to effectively overcome the bottleneck of testing accuracy caused by product batch differences while ensuring the high-speed operation of the automated testing system has become a key technical challenge that low-frequency transformer automated production lines urgently need to overcome. Summary of the Invention

[0005] The purpose of this invention is to provide a method, apparatus, electronic device, and storage medium for testing the performance of low-frequency transformers, which overcomes the bottleneck problem of testing accuracy caused by batch differences in products, effectively avoids misjudgment or omission caused by improper configuration of fixed parameters, thereby significantly improving the effectiveness and reliability of batch test results and 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, applied to a low-frequency transformer performance testing system, comprising the following steps:

[0007] S1. By extracting transformer samples from the current batch of low-frequency transformers and conducting preliminary electrical performance parameter tests, the preliminary electrical performance parameter test data of each transformer sample is obtained.

[0008] S2. Based on the pre-test data of electrical performance parameters of each transformer sample, calculate the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers;

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

[0010] S4. Using the adjusted test parameter configuration, perform 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 current batch of transformers is qualified based on the batch electrical performance test data;

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

[0012] The low-frequency transformer performance testing method provided by this invention involves a preliminary, representative sample of transformers undergoing rapid pre-testing before the formal batch testing begins. This pre-testing aims to identify and understand the distribution characteristics of key performance parameters for the current batch of transformers. Subsequently, the testing system performs in-depth analysis of the data collected during the pre-testing phase. Based on the analysis results, a proportional-integral control algorithm is used to adaptively adjust the configuration of key test parameters in subsequent batch testing, enabling the test parameter configuration to dynamically match the actual parameter distribution characteristics of the current batch of transformers. In this way, the accuracy and effectiveness of the test results can be significantly improved without compromising overall testing efficiency.

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

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

[0015] S22. Based on the no-load current data, calculate the mean and standard deviation of the no-load current to obtain the distribution characteristic value of the no-load current;

[0016] S23. Based on the no-load voltage data, calculate the mean and standard deviation of the no-load voltage to obtain the distribution characteristic value of the no-load voltage;

[0017] S24. Based on the short-circuit impedance data, calculate the mean and standard deviation of the short-circuit impedance to obtain the characteristic value of the short-circuit impedance distribution;

[0018] S25. The no-load current distribution characteristic value, the no-load voltage distribution characteristic value, and the short-circuit impedance distribution characteristic value are weighted and fused to obtain the electrical performance parameter distribution characteristic value corresponding to the current batch of transformers.

[0019] The parameters of the testing system are adaptively adjusted to suit the performance characteristics of different batches of transformers, ensuring the accuracy and effectiveness of the test.

[0020] Furthermore, 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 based on the anti-interference capability of other nearby precision instruments;

[0023] S33. If the preset threshold is exceeded, the amplitude of the excitation signal or the frequency of the excitation signal is adjusted to reduce the electromagnetic interference intensity, provided that the test accuracy meets the requirements, until the electromagnetic interference intensity is lower than the preset threshold.

[0024] S34. Based on the adjusted excitation signal amplitude or frequency, and the distribution characteristic value of the electrical performance parameters, recalculate the measurement range and the measurement resolution.

[0025] The entire testing process effectively overcomes the influence of electromagnetic interference, ensuring the accuracy and reliability of the electrical performance parameter testing of low-frequency transformers.

[0026] Furthermore, 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, and obtain winding temperature rise data;

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

[0029] S333. If the preset temperature rise threshold is exceeded, the amplitude of the excitation signal or the frequency of the excitation signal is adjusted according to the winding temperature rise data to reduce the winding temperature rise rate.

[0030] S334. If the temperature rise does not exceed the preset temperature rise threshold, or if the winding temperature rise data is lower than the preset temperature rise threshold after adjusting the amplitude or frequency adjustment step size of the excitation signal, 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.

[0031] This technology achieves the goal of ensuring the safety and reliability of low-frequency transformer testing while reducing electromagnetic interference.

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

[0033] S341. Based on the adjusted excitation signal amplitude or excitation signal frequency, query a preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationship 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 based on the target measurement range; the measurement resolution is positively correlated with the target measurement range.

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

[0037] An electrical performance parameter correlation matrix is ​​established 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 ​​based on the electrical performance parameter test data of historical batches of low-frequency transformers and is obtained by calculating the Pearson correlation coefficient between each electrical performance parameter. The electrical performance parameter correlation matrix is ​​visualized using a heat map to facilitate the analysis of the correlation strength and direction between each electrical performance parameter.

[0038] Based on the correlation matrix of the electrical performance parameters, the range adjustment coefficients of the no-load current, no-load voltage and short-circuit impedance are calculated, and the distribution characteristic values ​​of the electrical performance parameters are weighted and corrected according to the range adjustment coefficients to obtain the corrected distribution characteristic values ​​of the electrical performance parameters.

[0039] Based on the corrected distribution characteristics of the electrical performance parameters, a multi-objective optimization model is constructed with the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance as objective functions. The NSGA-II algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set. The solution that satisfies 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 must 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.

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

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

[0042] The initial measurement resolution is calculated based on the number of bits of the analog-to-digital converter (ADC) and the target measurement range.

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

[0044] If the initial measurement resolution is lower than the preset resolution threshold, the number of bits of the analog-to-digital converter (ADC) is adjusted, and the initial measurement resolution is recalculated based on the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold. The adjusted initial measurement resolution is then used as the measurement resolution.

[0045] Secondly, the present invention provides a low-frequency transformer performance testing device, applied to a low-frequency transformer performance testing system, comprising:

[0046] The prediction module is used to obtain the pre-test data of electrical performance parameters for each transformer sample by extracting transformer samples from the current batch of low-frequency transformers and performing pre-tests on electrical performance parameters.

[0047] The calculation module is used to calculate the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers based on the pre-test data of electrical performance parameters of each transformer sample.

[0048] The adjustment module is used to calculate the test parameter adjustment amount based on the distribution characteristic value of the electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount; the test parameter configuration includes excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution;

[0049] The judgment module is used to perform batch electrical performance tests on the current batch of low-frequency transformers using the adjusted test parameter configuration, obtain batch electrical performance test data, and determine whether the performance of the current batch of transformers is qualified based on the batch electrical performance test data.

[0050] The generation module is used to generate a test report for the current batch of transformers. The test report includes batch information of the current batch of transformers, adjusted test parameter configuration, and batch electrical performance test data.

[0051] The low-frequency transformer performance testing device provided by this invention ensures that the test parameters during batch testing match the actual characteristics of the current batch of products, thereby effectively improving testing accuracy and efficiency. After batch testing is completed, the system automatically determines whether the performance of the current batch of transformers is qualified based on the acquired batch electrical performance test data, ensuring the quality of products leaving the factory.

[0052] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory storing computer-readable instructions, which, when executed by the processor, perform the steps of the low-frequency transformer performance testing method provided in the first aspect above.

[0053] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the low-frequency transformer performance testing method provided in the first aspect above.

[0054] As can be seen from the above, the low-frequency transformer performance testing method provided by this invention, in specific application scenarios such as low-frequency transformer automated production lines where there are strict limitations on cycle time and the pursuit of batch continuous testing efficiency, overcomes the limitations of existing automated testing systems that use fixed parameter configurations when facing the challenge of differences in the distribution of electrical performance parameters between batches of transformers of the same specification due to fluctuations in manufacturing processes. It constructs an automated testing method that can adaptively adjust according to the parameter distribution characteristics of batch transformers, thereby effectively improving the accuracy and reliability of electrical performance parameter testing of different batches of transformers without significantly reducing testing efficiency.

[0055] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0056] Figure 1 This is a flowchart of a low-frequency transformer performance testing method provided in an embodiment of the present invention.

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

[0058] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0059] Label Explanation:

[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. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally 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 claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0062] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0063] Reference Appendix Figure 1 This invention provides a method for testing the performance of low-frequency transformers, applied to a low-frequency transformer performance testing system, comprising the following steps:

[0064] S1. By extracting transformer samples from the current batch of low-frequency transformers and conducting preliminary electrical performance parameter tests, the preliminary electrical performance parameter test data of each transformer sample is obtained.

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

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

[0067] S4. Using the adjusted test parameter configuration, perform 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 current batch of transformers is qualified based on the batch electrical performance test data;

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

[0069] In step S1, the transformer sample is randomly selected from the current batch of low-frequency transformers. The electrical performance parameters are pre-tested by using a low-frequency transformer performance testing system to conduct preliminary tests on the transformer sample. The electrical performance parameters pre-test data include, but are not limited to, no-load current data, no-load voltage data, and short-circuit impedance data.

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

[0071] In step S3, the test parameter adjustment amount can be calculated based on the distribution characteristic value of the electrical performance parameters using a proportional-integral control algorithm. The input of the proportional-integral control algorithm is the deviation between the distribution characteristic value 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 range of parameters that the test system can measure, and the measurement resolution determines the minimum parameter change that the test system can resolve.

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

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

[0074] Specifically, addressing the technical problems of insufficient testing accuracy and low efficiency of manual adjustments in automated testing systems for low-frequency transformers due to batch-to-batch variations, this application proposes a performance testing method for low-frequency transformers. This method first performs pre-testing on a portion of the transformer samples from the current batch in step S1, quickly obtaining preliminary data on the electrical performance parameters of that batch of transformers. Then, in step S2, these pre-test data are statistically analyzed to calculate characteristic values ​​reflecting the distribution of electrical performance parameters of the current batch of transformers, such as the mean and standard deviation. This achieves a quantitative characterization of parameter differences between batches.

[0075] Next, in step S3, a proportional-integral (PI) control algorithm can be introduced. This algorithm takes the distribution characteristics 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 excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution, is automatically adjusted according to the calculated adjustment amount. The use of the PPI control algorithm ensures the accuracy and stability of the test parameter adjustment, enabling the test system to quickly respond to differences between product batches and overcoming the arbitrariness and inefficiency of manual adjustment based on experience.

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

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

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

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

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

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

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

[0083] S25. The no-load current distribution characteristic value, no-load voltage distribution characteristic value, and short-circuit impedance distribution characteristic value are weighted and fused according to the following formula to obtain the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers:

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

[0085] Where D is the characteristic value of the electrical performance parameter distribution, σ I σ V σ Z These are the standard deviations of no-load current, no-load voltage, and short-circuit impedance, respectively, in μ. I μ V μ Z These are the mean values ​​of no-load current, no-load voltage, and short-circuit impedance, respectively, σ I / μ I This is represented by the characteristic value of the no-load current distribution, σ. V / μ V Represented as the characteristic value of the no-load voltage distribution, σ Z / μ Z It is represented as the characteristic value of short-circuit impedance distribution, and w1, w2, and w3 are the corresponding weighting coefficients.

[0086] In step S21, the electrical performance parameters of the transformer sample are pre-tested using testing equipment. The electrical performance parameters are limited to no-load current, no-load voltage, and short-circuit impedance.

[0087] In steps S22 to S24, the mean and standard deviation are calculated for each type of electrical performance parameter's pretest data. The mean reflects the central tendency of the data, while the standard deviation reflects the dispersion 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. This ratio achieves a normalized representation of the data dispersion, facilitating the comparison of the distribution characteristic values ​​of different electrical performance parameters.

[0088] In step S25, a weighted fusion formula is used to integrate the distribution characteristic values ​​of the three electrical performance parameters. The weighting coefficients can be set according to the relative importance of different electrical performance parameters in actual applications, so as to achieve flexible adjustment of the distribution characteristic values ​​of the comprehensive electrical performance parameters.

[0089] Specifically, this embodiment first collects pre-test data on no-load current, no-load voltage, and short-circuit impedance. 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 in that batch, while the standard deviation quantifies the degree of deviation of the parameter value from the mean, i.e., 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 of the electrical performance parameters in the current batch of transformers, and the more significant the differences between batches. Conversely, the lower the distribution characteristic value of the electrical performance parameters, the more concentrated the distribution of parameters in the batch, and the smaller the differences between batches. Therefore, subsequent steps can adaptively adjust the parameter configuration of the test system 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, ensuring the accuracy and effectiveness of the test.

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

[0091] S31. Obtain the current electromagnetic interference intensity by monitoring the electromagnetic environment of the test station;

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

[0093] S33. If the preset threshold is exceeded, the amplitude or frequency of the excitation signal will be adjusted to reduce the electromagnetic interference intensity, until the electromagnetic interference intensity is lower than the preset threshold, provided that the test accuracy meets the requirements.

[0094] S34. Based on the adjusted excitation signal amplitude or frequency, and the distribution characteristics of the electrical performance parameters, recalculate the measurement range and measurement resolution.

[0095] In step S31, electromagnetic environment monitoring is achieved by deploying electromagnetic interference sensors near the test station. The sensors collect 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 a critical value for electromagnetic interference intensity. The setting of this value takes into account the anti-interference capability of precision instruments around the test system. Specifically, the preset threshold can be set slightly lower than the maximum tolerable electromagnetic interference intensity value of the most sensitive precision instrument in the vicinity, thereby ensuring that the test system operates in a relatively safe electromagnetic environment.

[0097] In step S33, adjusting the amplitude or frequency of the excitation signal to reduce electromagnetic interference can be achieved in various ways. For example, reducing the amplitude of the excitation signal directly reduces the electromagnetic energy radiated by the test system, thereby reducing the electromagnetic interference. Adjusting the frequency of the excitation signal can avoid interference frequency bands in the electromagnetic environment, thus reducing electromagnetic interference at specific frequencies. Ensuring that the test accuracy meets the requirements is a prerequisite for adjusting the excitation signal parameters; therefore, the amplitude and frequency adjustments must be made 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 characteristic values ​​of the electrical performance parameter distribution. Changes 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. The measurement resolution, as a reflection of measurement accuracy, 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, to address the issue of electromagnetic interference potentially affecting test accuracy, this solution incorporates an electromagnetic environment monitoring system to achieve real-time assessment of electromagnetic interference intensity at the test station. When the detected electromagnetic interference intensity exceeds a preset threshold, the system automatically adjusts the amplitude or frequency of the excitation signal to proactively reduce electromagnetic interference. This adjustment is performed while ensuring that test accuracy remains largely unaffected, avoiding sacrificing test results accuracy due to excessive reduction in excitation signal strength. Proactively reducing electromagnetic interference intensity also avoids impacting the use of surrounding precision instruments, thus contributing to the assurance of their testing accuracy. After completing the electromagnetic interference adjustment, the system recalculates and optimizes the measurement range and resolution based on the adjusted excitation signal parameters, ensuring that the test system maintains optimal test performance under the new excitation signal configuration. Therefore, the entire testing process effectively overcomes the influence of electromagnetic interference, guaranteeing the accuracy and reliability of low-frequency transformer electrical performance parameter testing.

[0100] In some specific implementations, an electromagnetic interference sensor is selected as a high-sensitivity electromagnetic field probe, installed approximately 0.5 meters directly above the low-frequency transformer performance testing station to monitor the electromagnetic radiation level near the station in real time. A preset threshold is set to 3V / m, a value determined based on the electromagnetic interference immunity of a high-precision spectrum analyzer in the testing workshop. When the electromagnetic interference intensity exceeds 3V / m, the testing system prioritizes reducing the excitation signal amplitude by 5% each time, while simultaneously monitoring the electromagnetic interference intensity until it drops below 3V / m. As a preferred implementation, if the electromagnetic interference intensity remains above 3V / m when the excitation signal amplitude is reduced to 80% of its initial value, the system begins adjusting the excitation signal frequency by 1Hz each time, performing a scanning adjustment within a ±5Hz range, again targeting an electromagnetic interference intensity below 3V / m. After the excitation signal parameters are adjusted, the system recalculates the measurement range based on the new excitation signal amplitude and frequency, as well as the distribution characteristics of the electrical performance parameters of the previous batch of transformers, using a proportional-integral control algorithm. The measurement resolution is then adjusted to match the new measurement range, ensuring that the test accuracy is not reduced due to the adjustment of the excitation signal. At the same time, as mentioned above, the reduction in electromagnetic interference intensity also helps to ensure the test accuracy of the spectrum analyzer and avoids the low-frequency transformer performance test system affecting the normal operation of surrounding instruments.

[0101] In some 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 winding temperature rise data;

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

[0104] S333. If the preset temperature rise threshold is exceeded, the amplitude of the excitation signal or the adjustment step size of the excitation signal frequency will be adjusted according to the winding temperature rise data to reduce the winding temperature rise rate.

[0105] S334. If the temperature rise does not exceed the preset temperature rise threshold, or if the winding temperature rise data is lower than the preset temperature rise threshold after adjusting the amplitude or frequency of the excitation signal, 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 winding temperature can be monitored by a temperature sensor, which is configured to contact or be close to the winding of the low-frequency transformer to collect winding temperature data in real time.

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

[0108] In step S333, the adjustment strategy for adjusting the step size can be as follows: 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 achieve the goal of reducing the electromagnetic interference intensity more quickly.

[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 amplitude or frequency of the excitation signal is finely adjusted until the electromagnetic interference intensity drops to an acceptable level.

[0110] Specifically, this embodiment adds a monitoring and control mechanism for winding temperature during excitation signal adjustment. When the amplitude or frequency of the excitation signal is adjusted to reduce electromagnetic interference, the system monitors the temperature change of the transformer winding in real time. If the system detects a risk that the winding temperature may exceed a preset temperature rise threshold, it will proactively reduce the amplitude of the excitation signal adjustment to slow down the rate of winding temperature rise and prevent the transformer from being damaged due to overheating. Only when the winding temperature is effectively controlled will the system 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 safety and reliability of low-frequency transformer testing 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 winding temperature rise data 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 5% per adjustment to 1% per adjustment, and the adjustment step size of the frequency is reduced from 1Hz per adjustment to 0.2Hz per adjustment, gradually adjusting the excitation signal with smaller amplitudes to slow down the winding temperature rise rate. Through this fine-grained adjustment step size control, the winding temperature can be effectively prevented from rising too quickly, ensuring the safety of the low-frequency transformer during the testing process.

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

[0113] S341. Based on 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 relationship between different excitation signal amplitudes, different excitation signal frequencies and different measurement ranges;

[0114] S342. Adjust the initial measurement range according to the distribution characteristic value of electrical performance parameters, and obtain the adjusted measurement range as the target measurement range;

[0115] S343. Determine the measurement resolution based on 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 by conducting multiple experiments beforehand to test the measurement range that ensures testing accuracy for different combinations of excitation signal amplitude and frequency, and recording these correspondences 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, thus achieving a preliminary and rapid setting of the measurement range.

[0117] Furthermore, after obtaining the initial measurement range, in step S342, the initial measurement range is adjusted according to the characteristic values ​​of the electrical performance parameter distribution. These characteristic values ​​reflect the overall distribution of the electrical performance parameters of the current batch of transformers. For example, if the characteristic values ​​indicate that the parameter values ​​of the current batch of transformers are generally too large, the measurement range can be appropriately expanded; conversely, if the parameter values ​​are generally too small, the measurement range can be appropriately reduced. This adjustment can be achieved through various methods such as proportional adjustment or segmented adjustment, with the aim of making the measurement range more closely match the actual parameter distribution of the current batch of transformers, thereby improving the accuracy and sensitivity of the measurement.

[0118] Therefore, in step S343, the measurement resolution is determined based on the target measurement range. The measurement resolution is positively correlated with the target measurement range; that is, as the measurement range increases, the measurement resolution can be appropriately increased, and vice versa. This positive correlation can be achieved through various methods such as preset functions and lookup tables. For example, a preset resolution calculation formula can be used: Resolution = Target Measurement Range / Fixed Coefficient, where the fixed coefficient can be determined based on the accuracy requirements and hardware configuration of the testing system. This approach ensures that the measurement resolution remains at a reasonable level under different measurement ranges, balancing measurement accuracy and testing efficiency.

[0119] Specifically, during the performance testing of low-frequency transformers, the testing system first consults a pre-established mapping table based on the adjusted excitation signal amplitude and frequency (e.g., the excitation signal amplitude is adjusted to 10V and the excitation signal frequency to 50Hz). The mapping table records the correspondence between different combinations of excitation signal parameters and measurement ranges. 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, assuming that the characteristic value indicates that the overall electrical performance parameters of the current batch of transformers are too large. Based on this characteristic value, the system adjusts the initial measurement range of 1A. For example, through the proportional-integral control algorithm, the range adjustment coefficient is calculated to be 1.2, and the target measurement range is adjusted to 1.2A.

[0121] Finally, based on the target measurement range of 1.2A, the system determines the measurement resolution. Assuming the system pre-determines a positive correlation between resolution and range: 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 testing system can quickly and automatically set and adjust the measurement range and resolution to match the excitation signal and the parameter distribution of the current batch of transformers, ensuring the accuracy and effectiveness of the test.

[0122] In some specific implementations, the mapping table can be stored in the form of a database or spreadsheet, supporting fast query operations. The distribution characteristic values ​​of 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 range adjustment coefficient can be calculated using a proportional-integral control algorithm, dynamically adjusting the range adjustment coefficient based on the deviation between the distribution characteristic values ​​of the electrical performance parameters and the preset target values. The positive correlation between measurement resolution and the target measurement range can be defined using a piecewise function, employing different resolution calculation formulas within different ranges to achieve more refined resolution adjustment. Through the above specific implementations, the accuracy and flexibility of measurement range and resolution settings can be further improved, better adapting to the automated performance testing needs of low-frequency transformers of different batches and specifications.

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

[0124] An electrical performance parameter correlation matrix is ​​established 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 ​​based on the electrical performance parameter test data of historical batches of low-frequency transformers and is obtained by calculating the Pearson correlation coefficient between each electrical performance parameter. The electrical performance parameter correlation matrix is ​​visualized using a heat map to facilitate the analysis of the correlation strength and direction between each electrical performance parameter.

[0125] Based on the correlation matrix of electrical performance parameters, the range adjustment coefficients of no-load current, no-load voltage and short-circuit impedance are calculated, and the distribution characteristic values ​​of electrical performance parameters are weighted and corrected according to the range adjustment coefficients to obtain the corrected distribution characteristic values ​​of electrical performance parameters.

[0126] Based on the corrected distribution characteristics of electrical performance parameters, a multi-objective optimization model is constructed with the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance as objective functions. The NSGA-II algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set. The solution that satisfies 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 must 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, the establishment of the electrical performance parameter correlation matrix can utilize stored historical batches of low-frequency transformer electrical performance parameter test data. Specifically, test data of no-load current, no-load voltage, and short-circuit impedance from multiple batches of transformers are collected to form a dataset. Then, for each pair of 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 calculated Pearson correlation coefficient ranges from -1 to 1, with values ​​close to 1 indicating a strong positive correlation, close to -1 indicating a strong negative correlation, and close to 0 indicating a weak correlation. The calculated Pearson correlation coefficients between each pair of parameters are organized into a matrix, i.e., the electrical performance parameter correlation matrix. To more intuitively display the strength and direction of the correlation between parameters, the electrical performance parameter correlation matrix can be visualized as a heatmap, where the heatmap uses color depth to represent the magnitude of the correlation coefficient, with darker colors generally indicating a stronger correlation.

[0128] The range adjustment factor can be calculated based on the correlation coefficient in the correlation matrix of electrical performance parameters. For example, if there is a strong positive correlation between no-load current and short-circuit impedance, the distribution characteristics of short-circuit impedance need to be considered when adjusting the measurement range of no-load current. The range adjustment factor can be designed to be proportional to the magnitude of the correlation coefficient. The purpose of using the range adjustment factor to weight and correct the distribution characteristics of electrical performance parameters is to ensure that the corrected characteristics 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, firstly, the optimization objective is 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, the reciprocal of the measurement error or the signal-to-noise ratio can be used to characterize the measurement accuracy. Then, the NSGA-II algorithm is used 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 solutions, representing the optimal set of solutions that balance different objectives, i.e., improving one objective function without at least decreasing others. Finally, from the Pareto optimal solution set obtained by the NSGA-II algorithm, the solution that satisfies the preset range margin constraint is selected as the target measurement range. The specific implementation of the preset range margin constraint can be as follows: for each electrical performance parameter, calculate its estimated maximum parameter value; for example, the mean plus a certain number of standard deviations 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. Choosing a margin factor of 1.2 is to ensure that the target measurement range can cover the fluctuation range of the parameters and reserve a certain measurement redundancy, so as to simultaneously meet the measurement requirements of no-load current, no-load voltage and short-circuit impedance.

[0130] Specifically, this embodiment first establishes an electrical performance parameter correlation matrix, enabling the scheme to effectively analyze and quantify the interrelationships among three electrical performance parameters: no-load current, no-load voltage, and short-circuit impedance. The establishment of this correlation matrix allows range adjustment to consider not only the distribution characteristics of individual parameters in isolation, but also the mutual influence between parameters. Secondly, through range adjustment coefficients and weighted corrections, the distribution characteristics of the electrical performance parameters are further optimized. The corrected characteristics 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 employing the NSGA-II algorithm, the scheme achieves trade-offs and optimization among multiple measurement accuracy objectives. The NSGA-II algorithm can search for a set of Pareto optimal solutions, providing more selection space and decision-making basis for range selection. Finally, by pre-setting range margin constraints, the target measurement range selected from the Pareto optimal solution set satisfies the measurement requirements of each parameter while ensuring a certain degree of measurement redundancy, preventing parameter fluctuations from exceeding the range and ensuring measurement reliability. Therefore, this embodiment achieves more accurate and reliable measurement range adjustment by comprehensively considering the correlation between electrical performance parameters, optimizing measurement accuracy, and ensuring range margin, thus solving the bottleneck problem of test accuracy caused by product batch differences and traditional fixed range configuration strategies mentioned in the background art.

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

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

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

[0134] Based on the ADC bit depth and the target measurement range, the initial measurement resolution is calculated using 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 a preset resolution threshold;

[0136] If the initial measurement resolution is lower than the preset resolution threshold, the number of bits of the analog-to-digital converter (ADC) is adjusted, and the initial measurement resolution is recalculated based on the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold. The adjusted initial measurement resolution is then used as the measurement resolution.

[0137] This embodiment explicitly states the need to obtain the number of bits of the analog-to-digital converter (ADC) of the test equipment. This 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. Given a fixed target measurement range, the number of bits of the ADC directly determines the magnitude of the initial measurement resolution.

[0138] This embodiment adds a judgment step: determining whether the initial measurement resolution is lower than a preset resolution threshold. The preset resolution threshold is a minimum acceptable resolution level set based on actual test accuracy requirements. If the initial measurement resolution is lower than the preset resolution threshold, the solution proposes adjusting the number of bits in the analog-to-digital converter (ADC) and recalculating the initial measurement resolution until it is not lower than the preset resolution threshold. This means that when the number of bits in the hardware's ADC is insufficient to provide adequate resolution, the measurement resolution can be improved by adjusting the number of bits in the ADC, thereby ensuring that the final measurement resolution meets the test accuracy requirements. The adjusted initial measurement resolution is then used as the final measurement resolution, guaranteeing 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, if the ADC is 12 bits. Then, the system adopts the target measurement range, for example, 10A. The initial measurement resolution is calculated to be approximately 2.4mA according to the formula above. The system presets a resolution threshold, for example, 3mA. The system compares the initial measurement resolution of 2.4mA with the preset resolution threshold of 3mA. Since 2.4mA is less than 3mA, the initial measurement resolution is lower than the preset resolution threshold. At this point, the system adjusts the number of bits of the ADC, for example, adjusting it to 10 bits. Based on the adjusted ADC number of bits, the initial measurement resolution is recalculated to be approximately 9.7mA. The recalculated initial measurement resolution of 9.7mA is compared again with the preset resolution threshold of 3mA. Since 9.7mA is greater than 3mA, the initial measurement resolution is not lower than the preset resolution threshold. Therefore, the system uses the adjusted initial measurement resolution of 9.7mA as the final measurement resolution. Through these steps, the measurement resolution meets the test accuracy requirements, improving the quality and efficiency of low-frequency transformer performance testing.

[0140] In some specific implementations, the test equipment is equipped with a variable-bit analog-to-digital converter (ADC). The test system can automatically adjust the ADC bit depth based on a comparison between the calculated initial measurement resolution and a preset resolution threshold. For example, when the initial measurement resolution is lower than the threshold, the control system instructs the hardware to switch to a higher-bit ADC for data acquisition. As a preferred implementation, adjusting the ADC bit depth can employ oversampling technology. Without replacing the hardware ADC, the bit depth of the ADC is effectively increased through multiple sampling and averaging, thereby improving the measurement resolution. Thus, the measurement resolution can be flexibly adjusted within hardware limitations to meet the testing requirements of different accuracy levels.

[0141] Please refer to Figure 2 , Figure 2 This invention provides a low-frequency transformer performance testing device in some embodiments, applied to a low-frequency transformer performance testing system. The low-frequency transformer performance testing device is integrated into a back-end control device in the form of a computer program, comprising:

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

[0143] The calculation module 200 is used to calculate the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers based on the pre-test data of electrical performance parameters of each transformer sample.

[0144] The adjustment module 300 is used to calculate the test parameter adjustment amount based on 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 test parameter adjustment amount; the test parameter configuration includes excitation signal amplitude, excitation signal frequency, measurement range and measurement resolution;

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

[0146] The generation module 500 is used to generate test reports for the current batch of transformers. The test reports include batch information, adjusted test parameter configurations, and batch electrical performance test data for the current batch of transformers.

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

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

[0149] S22. Based on the no-load current data, calculate the mean and standard deviation of the no-load current to obtain the characteristic value of the no-load current distribution;

[0150] S23. Based on the no-load voltage data, calculate the mean and standard deviation of the no-load voltage to obtain the characteristic value of the no-load voltage distribution;

[0151] S24. Based on the short-circuit impedance data, calculate the mean and standard deviation of the short-circuit impedance to obtain the characteristic value of the short-circuit impedance distribution;

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

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

[0154] Where D is the characteristic value of the electrical performance parameter distribution, σ I σ V σZ These are the standard deviations of no-load current, no-load voltage, and short-circuit impedance, respectively, in μ. I μ V μ Z These are the mean values ​​of no-load current, no-load voltage, and short-circuit impedance, respectively, σ I / μ I This is represented by the characteristic value of the no-load current distribution, σ. V / μ V Represented as the characteristic value of the no-load voltage distribution, σ Z / μ Z It is represented as the characteristic value of short-circuit impedance distribution, and w1, w2, and w3 are the corresponding weighting coefficients.

[0155] In some embodiments, the adjustment module 300 performs the following when calculating the test parameter adjustment amount based on the distribution characteristic values ​​of electrical performance parameters, and adjusting the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount:

[0156] S31. Obtain the current electromagnetic interference intensity by monitoring the electromagnetic environment of the test station;

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

[0158] S33. If the preset threshold is exceeded, the amplitude or frequency of the excitation signal will be adjusted to reduce the electromagnetic interference intensity, until the electromagnetic interference intensity is lower than the preset threshold, provided that the test accuracy meets the requirements.

[0159] S34. Based on the adjusted excitation signal amplitude or frequency, and the distribution characteristics of the electrical performance parameters, recalculate the measurement range and measurement resolution.

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

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

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

[0163] S333. If the preset temperature rise threshold is exceeded, the amplitude of the excitation signal or the adjustment step size of the excitation signal frequency will be adjusted according to the winding temperature rise data to reduce the winding temperature rise rate.

[0164] S334. If the temperature rise does not exceed the preset temperature rise threshold, or if the winding temperature rise data is lower than the preset temperature rise threshold after adjusting the amplitude or frequency of the excitation signal, 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, the adjustment module 300 performs the following when recalculating the measurement range and measurement resolution based on the adjusted excitation signal amplitude or frequency and the distribution characteristics of the electrical performance parameters:

[0166] S341. Based on 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 relationship 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 electrical performance parameters, and obtain the adjusted measurement range as the target measurement range;

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

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

[0170] An electrical performance parameter correlation matrix is ​​established 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 ​​based on the electrical performance parameter test data of historical batches of low-frequency transformers and is obtained by calculating the Pearson correlation coefficient between each electrical performance parameter. The electrical performance parameter correlation matrix is ​​visualized using a heat map to facilitate the analysis of the correlation strength and direction between each electrical performance parameter.

[0171] Based on the correlation matrix of electrical performance parameters, the range adjustment coefficients of no-load current, no-load voltage and short-circuit impedance are calculated, and the distribution characteristic values ​​of electrical performance parameters are weighted and corrected according to the range adjustment coefficients to obtain the corrected distribution characteristic values ​​of electrical performance parameters.

[0172] Based on the corrected distribution characteristics of electrical performance parameters, a multi-objective optimization model is constructed with the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance as objective functions. The NSGA-II algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set. The solution that satisfies 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 must 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, the adjustment module 300 performs the following when determining the measurement resolution based on the target measurement range:

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

[0175] Based on the ADC bit depth and the target measurement range, the initial measurement resolution is calculated using 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] Determine whether the initial measurement resolution is lower than a preset resolution threshold;

[0177] If the initial measurement resolution is lower than the preset resolution threshold, the number of bits of the analog-to-digital converter (ADC) is adjusted, and the initial measurement resolution is recalculated based on the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold. The adjusted initial measurement resolution is then used as the measurement resolution.

[0178] Please refer to Figure 3 , Figure 3This is a schematic diagram of the structure of an electronic device provided in 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 via a communication bus 1303 and / or other forms of connection mechanism (not shown). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device is running, the processor 1301 executes the computer-readable instructions to execute the low-frequency transformer performance testing method in any optional implementation of the above embodiments, to achieve the following functions: by extracting transformer samples from the current batch of low-frequency transformers and performing pre-testing of electrical performance parameters, obtaining pre-test data of electrical performance parameters for each transformer sample; based on... Based on the pre-test data of electrical performance parameters of each transformer sample, the distribution characteristic values ​​of electrical performance parameters corresponding to the current batch of transformers are calculated. Based on these distribution characteristic values, the adjustment amount of the test parameters is calculated, and the test parameter configuration of the low-frequency transformer performance testing system is adjusted accordingly. The test parameter configuration includes the excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution. Using the adjusted test parameter configuration, batch electrical performance tests are performed on the current batch of low-frequency transformers to obtain batch electrical performance test data. Based on the batch electrical performance test data, it is determined whether the performance of the current batch of transformers is qualified. A test report for the current batch of transformers is generated, containing batch information, the adjusted test parameter configuration, and the batch electrical performance test data.

[0179] This invention provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs a low-frequency transformer performance testing method according to any optional implementation of the above embodiments, to achieve the following functions: obtaining pre-test data of electrical performance parameters for each transformer sample by extracting transformer samples from the current batch of low-frequency transformers and performing pre-tests on their electrical performance parameters; calculating the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers based on the pre-test data of electrical performance parameters for each transformer sample; calculating the adjustment amount of test parameters based on the distribution characteristic value of electrical performance parameters, and adjusting the test parameter configuration of the low-frequency transformer performance testing system based on the adjustment amount of test parameters; the test parameter configuration includes excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution; performing batch electrical performance testing 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 based on the batch electrical performance test data; generating a test report for the current batch of transformers, the test report including batch information of the current batch of transformers, the adjusted test parameter configuration, and the batch electrical performance test data.

[0180] 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 Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0181] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0182] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

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

[0184] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0185] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for testing the performance of a low-frequency transformer, applied to a low-frequency transformer performance testing system, characterized in that, Includes the following steps: S1. By extracting transformer samples from the current batch of low-frequency transformers and conducting preliminary electrical performance parameter tests, the preliminary electrical performance parameter test data of each transformer sample is obtained. S2. Based on the pre-test data of electrical performance parameters of each transformer sample, calculate the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers; S3. Calculate the test parameter adjustment amount based on the distribution characteristic values ​​of the electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount; the test parameter configuration includes excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution; S4. Using the adjusted test parameter configuration, perform 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 current batch of transformers is qualified based on the batch electrical performance test data; S5. Generate a test report for the current batch of transformers, the test report including batch information of the current batch of transformers, adjusted test parameter configuration and batch electrical performance test data; The specific steps in step S3 include: S31. Obtain the current electromagnetic interference intensity by monitoring the electromagnetic environment of the test station; S32. Determine whether the electromagnetic interference intensity exceeds a preset threshold; the preset threshold is determined based on the anti-interference capability of other nearby precision instruments; S33. If the preset threshold is exceeded, the amplitude of the excitation signal or the frequency of the excitation signal is adjusted to reduce the electromagnetic interference intensity, provided that the test accuracy meets the requirements, until the electromagnetic interference intensity is lower than the preset threshold. S34. Based on the adjusted excitation signal amplitude or excitation signal frequency, and the distribution characteristic value of the electrical performance parameters, recalculate the measurement range and the measurement resolution; The specific steps in step S34 include: S341. Based on the adjusted excitation signal amplitude or excitation signal frequency, query a preset mapping table to obtain the corresponding measurement range as the initial measurement range; the mapping table records the mapping relationship 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 and use it as the target measurement range; S343. Determine the measurement resolution based on the target measurement range; the measurement resolution is positively correlated with the target measurement range; The specific steps in step S342 include: An electrical performance parameter correlation matrix is ​​established 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 ​​based on the electrical performance parameter test data of historical batches of low-frequency transformers and is obtained by calculating the Pearson correlation coefficient between each electrical performance parameter. The electrical performance parameter correlation matrix is ​​visualized using a heat map to facilitate the analysis of the correlation strength and direction between each electrical performance parameter. Based on the correlation matrix of the electrical performance parameters, the range adjustment coefficients of the no-load current, no-load voltage and short-circuit impedance are calculated, and the distribution characteristic values ​​of the electrical performance parameters are weighted and corrected according to the range adjustment coefficients to obtain the corrected distribution characteristic values ​​of the electrical performance parameters. Based on the corrected distribution characteristics of the electrical performance parameters, a multi-objective optimization model is constructed with the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance as objective functions. The NSGA-II algorithm is used to solve the multi-objective optimization model to obtain the Pareto optimal solution set. The solution that satisfies 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 must 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 measurement redundancy.

2. The low-frequency transformer performance testing method according to claim 1, characterized in that, The specific steps in step S2 include: S21. Collect pre-test data of electrical performance parameters for each transformer sample; electrical performance parameters include no-load current, no-load voltage, and short-circuit impedance; the pre-test data of electrical performance parameters includes no-load current data, no-load voltage data, and short-circuit impedance data; S22. Based on the no-load current data, calculate the mean and standard deviation of the no-load current to obtain the distribution characteristic value of the no-load current; S23. Based on the no-load voltage data, calculate the mean and standard deviation of the no-load voltage to obtain the distribution characteristic value of the no-load voltage; S24. Based on the short-circuit impedance data, calculate the mean and standard deviation of the short-circuit impedance to obtain the characteristic value of the short-circuit impedance distribution; S25. The no-load current distribution characteristic value, the no-load voltage distribution characteristic value, and the short-circuit impedance distribution characteristic value are weighted and fused to obtain the electrical performance parameter distribution characteristic value corresponding to the current batch of transformers.

3. The low-frequency transformer performance testing method according to claim 1, characterized in that, The specific steps in step S33 include: S331. Monitor the winding temperature of the low-frequency transformer after adjusting the amplitude or frequency of the excitation signal, and obtain winding temperature rise data; S332. Determine whether the winding temperature rise data exceeds a preset temperature rise threshold; S333. If the preset temperature rise threshold is exceeded, the amplitude of the excitation signal or the frequency of the excitation signal is adjusted according to the winding temperature rise data to reduce the winding temperature rise rate. S334. If the temperature rise does not exceed the preset temperature rise threshold, or if the winding temperature rise data is lower than the preset temperature rise threshold after adjusting the amplitude or frequency adjustment step size of the excitation signal, 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.

4. The low-frequency transformer performance testing method according to claim 1, 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; The initial measurement resolution is calculated based on the number of bits of the analog-to-digital converter (ADC) and the target measurement range. Determine whether the initial measurement resolution is lower than a preset resolution threshold; If the initial measurement resolution is lower than the preset resolution threshold, the number of bits of the analog-to-digital converter (ADC) is adjusted, and the initial measurement resolution is recalculated based on the adjusted number of bits of the ADC until the initial measurement resolution is not lower than the preset resolution threshold. The adjusted initial measurement resolution is then used as the measurement resolution.

5. A low-frequency transformer performance testing device, applied to a low-frequency transformer performance testing system, characterized in that, include: The prediction module is used to obtain the pre-test data of electrical performance parameters for each transformer sample by extracting transformer samples from the current batch of low-frequency transformers and performing pre-tests on electrical performance parameters. The calculation module is used to calculate the distribution characteristic value of electrical performance parameters corresponding to the current batch of transformers based on the pre-test data of electrical performance parameters of each transformer sample. The adjustment module is used to calculate the test parameter adjustment amount based on the distribution characteristic value of the electrical performance parameters, and adjust the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount; the test parameter configuration includes excitation signal amplitude, excitation signal frequency, measurement range, and measurement resolution; The judgment module is used to perform batch electrical performance tests on the current batch of low-frequency transformers using the adjusted test parameter configuration, obtain batch electrical performance test data, and determine whether the performance of the current batch of transformers is qualified based on the batch electrical performance test data. The generation module is used to generate a test report for the current batch of transformers. The test report includes batch information of the current batch of transformers, adjusted test parameter configuration, and batch electrical performance test data. The adjustment module is executed when calculating the test parameter adjustment amount based on the distribution characteristic values ​​of electrical performance parameters, and adjusting the test parameter configuration of the low-frequency transformer performance testing system based on the test parameter adjustment amount: S31. Obtain the current electromagnetic interference intensity by monitoring the electromagnetic environment of the test station; S32. Determine whether the electromagnetic interference intensity exceeds the preset threshold; The preset threshold is determined based on the anti-interference capability of other nearby precision instruments; S33. If the preset threshold is exceeded, the amplitude or frequency of the excitation signal will be adjusted to reduce the electromagnetic interference intensity, until the electromagnetic interference intensity is lower than the preset threshold, provided that the test accuracy meets the requirements. S34. Based on the adjusted excitation signal amplitude or frequency, and the distribution characteristics of the electrical performance parameters, recalculate the measurement range and measurement resolution; The adjustment module is executed when recalculating the measurement range and resolution based on the adjusted excitation signal amplitude or frequency, and the distribution characteristics of the electrical performance parameters: S341. Based on 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 relationship 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 electrical performance parameters, and obtain the adjusted measurement range as the target measurement range; S343. Determine the measurement resolution based on the target measurement range; the measurement resolution is positively correlated with the target measurement range. The adjustment module is executed when adjusting the initial measurement range based on the distribution characteristics of electrical performance parameters, obtaining the adjusted measurement range, and using it as the target measurement range: 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 various electrical performance parameters based on the test data of electrical performance parameters of historical batches of low-frequency transformers. The correlation matrix of electrical performance parameters is visualized using a heatmap to facilitate the analysis of the correlation strength and direction between various electrical performance parameters. Based on the correlation matrix of electrical performance parameters, the range adjustment coefficients for no-load current, no-load voltage, and short-circuit impedance are calculated. The distribution characteristic values ​​of the electrical performance parameters are then weighted and corrected according to these range adjustment coefficients to obtain the corrected distribution characteristic values. Based on these corrected distribution characteristic values, a multi-objective optimization model is constructed with the measurement accuracy of no-load current, no-load voltage, and short-circuit impedance as the objective functions. The NSGA-II algorithm is used to solve the multi-objective optimization model, obtaining the Pareto optimal solution set. The solution that satisfies 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 must 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 measurement redundancy.

6. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-readable instructions, which, when executed by the processor, perform the steps in the low-frequency transformer performance testing method as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it performs the steps in the low-frequency transformer performance testing method as described in any one of claims 1-4.

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