A voltage transformer on-site calibration system and status diagnosis method

Abstract

The present invention discloses a voltage transformer on-site calibration system and state diagnosis method, which relates to the field of power equipment detection technology. The system comprises the following steps: measuring the primary and secondary voltages of a standard voltage transformer, calculating the voltage transformer ratio and the standard voltage transformer phase difference; obtaining the voltage transformer secondary voltage, and combining it with the voltage transformer primary voltage to obtain the voltage transformer phase difference; calculating the voltage error rate based on the standard voltage transformer secondary voltage and the voltage transformer secondary voltage, constructing a comprehensive calibration index model, and obtaining the voltage transformer on-site calibration coefficient; collecting the working state data of the voltage transformer, combining it with the voltage transformer on-site calibration coefficient, and constructing a state diagnosis model using a support vector machine algorithm to obtain the state diagnosis coefficient. The state diagnosis coefficient is compared and analyzed with the state diagnosis threshold to diagnose whether the voltage sensor state is abnormal. The present invention further improves calibration accuracy and solves the problem of large errors in traditional measurement and calculation methods.

Description

Technical Field

[0001] The present invention relates to the technical field of power equipment detection, and more particularly to an on-site calibration system and a state diagnosis method for a voltage transformer. Background Art

[0002] Voltage transformers are widely used in power systems for voltage measurement and monitoring, and their accuracy is crucial to power system stability. As power equipment ages, voltage transformers may experience performance degradation or failure, making regular on-site calibration and status diagnosis particularly important. However, traditional voltage transformer calibration methods often rely on manual testing, which is inefficient, susceptible to human error, and lacks real-time monitoring and diagnosis of equipment status. Voltage transformers, primarily used for proportional voltage conversion, play a vital role in power systems. They convert high voltages to low voltages proportionally, enabling various measuring instruments and relay protection devices to perform voltage measurements and protective actions.

[0003] Conventional voltage transformer calibration methods suffer from numerous shortcomings. First, most calibrations rely solely on comparing a single voltage parameter, failing to fully reflect the transformer's true performance and resulting in poorly accurate calibration results. For example, focusing solely on the secondary voltage value ignores important parameters like phase deviation, potentially preventing potential transformers from being detected promptly. Second, the hardware in field calibration systems lacks adaptive capabilities. In complex electromagnetic environments, signal acquisition modules cannot effectively handle interference, and conventional fixed sampling frequencies cannot specifically avoid or capture interfering frequency bands, severely impacting the accuracy of calibration data. Furthermore, power supply conditions vary significantly across different sites, making the power supply modules of existing calibration systems difficult to adapt flexibly. This often leads to unstable power supply or even inoperability. Furthermore, current voltage transformer status diagnosis relies heavily on manual judgment, lacking scientific data support and accurate diagnostic models. Faced with a large number of voltage transformers of varying models and operating conditions, traditional empirical judgments struggle to promptly and accurately detect potential faults, posing safety risks to power system operations.

[0004] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a voltage transformer on-site calibration system and a status diagnosis method, which solves the problems raised in the above-mentioned background technology through on-site calibration and status diagnosis of the voltage transformer.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A voltage transformer on-site calibration system and status diagnosis method, comprising the following steps:

[0008] Measure the primary voltage and secondary voltage of the standard voltage transformer, and calculate the voltage transformer ratio and standard voltage transformer phase difference based on the primary voltage and secondary voltage of the standard voltage transformer;

[0009] The voltage transformer secondary voltage is obtained according to the voltage transformer primary voltage and the voltage transformer ratio combined with the adaptive frequency adjustment, and the voltage transformer phase difference is obtained in combination with the voltage transformer primary voltage;

[0010] The voltage error rate is calculated based on the standard voltage transformer secondary voltage and the voltage transformer secondary voltage. A comprehensive calibration index model is constructed by combining the standard voltage transformer phase difference and the voltage transformer phase difference to obtain the voltage transformer on-site calibration coefficient.

[0011] The working status data of the voltage transformer is collected. Combined with the on-site calibration coefficient of the voltage transformer, the support vector machine algorithm is used to construct a status diagnosis model to obtain the status diagnosis coefficient. The status diagnosis coefficient is compared and analyzed with the status diagnosis threshold to diagnose whether there is any abnormality in the voltage sensor status.

[0012] In a preferred embodiment, the process of calculating the standard voltage transformer phase difference is as follows:

[0013] The primary and secondary voltage signals are collected to obtain discrete voltage signal sequences. and , where n is the sampling point number;

[0014] Preprocess the collected voltage signal, including filtering and denoising operations;

[0015] Perform Fourier transform on the preprocessed voltage signal to obtain the spectrum of the primary voltage and secondary voltage signals respectively. and , where k is the frequency component number;

[0016] Extract the phase of the fundamental components of the primary and secondary voltages from the spectrum and ;

[0017] According to the phase of the fundamental component of the primary voltage and the secondary voltage and Calculating the Phase Difference of a Standard Voltage Transformer , the formula is: .

[0018] In a preferred embodiment, the process of adaptively adjusting the frequency is as follows:

[0019] At the initial sampling frequency For primary voltage Sampling is performed to obtain a discrete voltage sequence ,in N is the number of sampling points;

[0020] Perform spectrum analysis on the collected primary voltage sequence, use fast Fourier transform to obtain the signal spectrum, and analyze the frequency components and intensity distribution of the interference signal in the spectrum;

[0021] Determine the interference frequency range based on the frequency components and intensity distribution of the interference signal and the interference signal strength;

[0022] The corresponding spectrum index is obtained according to the main interference frequency range, and the sampling frequency is adjusted based on the interference signal strength and the initial sampling frequency. The calculation formula is as follows:

[0023] ;

[0024] Where, is to adjust the sampling frequency; is the initial sampling frequency; is the interference signal strength; is the reference interference signal strength; is the spectrum of the signal; Interference frequency The corresponding spectrum index; 、 is the adjustment factor.

[0025] In a preferred embodiment, the interference signal strength acquisition process is as follows:

[0026] For narrowband interference, the amplitude value of the interference signal at its center frequency is directly read as a measure of the interference signal strength;

[0027] For broadband interference, it is necessary to integrate the power within the frequency band occupied by the interference signal to obtain the interference signal strength. The specific process is as follows:

[0028] The power spectrum density function is measured by a spectrum analyzer, and the interference signal strength is obtained by integration calculation based on the main interference frequency range. The specific calculation formula is as follows:

[0029] ;

[0030] Where, is the interference signal strength, and the interference frequency range is , is the power spectral density function.

[0031] In a preferred embodiment, the specific process of obtaining the voltage transformer phase difference is as follows:

[0032] By comparing the signs of adjacent sampling points, the zero-crossing points of the new primary voltage sequence and the secondary voltage sequence of the voltage transformer are found respectively;

[0033] Record the sampling moments of adjacent zero crossing points of the primary and secondary voltage signals and , combined with the signal period t to calculate the voltage transformer phase difference, the formula is .

[0034] In a preferred embodiment, the secondary voltage sequence acquisition process is as follows:

[0035] The ambient temperature and humidity when measuring the primary voltage are combined with the new primary voltage sequence and the voltage transformer ratio to calculate the voltage transformer secondary voltage sequence. The specific calculation formula is as follows:

[0036] ;

[0037] Where, is the voltage transformer secondary voltage sequence, is the new primary voltage sequence, N is the number of sampling points, B is the voltage transformer ratio, T is the ambient temperature, is the ambient temperature reference value, is the ambient humidity, is the ambient humidity reference value, 、 are the weight coefficients of ambient temperature and humidity respectively. In a preferred embodiment, the expression of the comprehensive calibration index model is:

[0038] ;

[0039] Where X is the voltage transformer field calibration coefficient, is the standard voltage transformer phase difference, is the voltage transformer phase difference, w is the voltage error rate, , , is the calibration index, determined by historical calibration data.

[0040] In a preferred embodiment, the operating status data includes current fluctuation coefficient and load power factor change rate;

[0041] The current fluctuation coefficient acquisition process is as follows:

[0042] In the secondary side circuit of the voltage transformer, a high-precision current transformer is connected in series to collect the load current in real time and obtain the load current sequence ;

[0043] According to the load current sequence, the maximum and minimum values of the load current are obtained, and the average value of the load current is calculated to obtain the current fluctuation coefficient. The specific calculation formula is as follows:

[0044] ;

[0045] Where, is the current fluctuation coefficient, Average load current, is the maximum load current, is the minimum load current;

[0046] The load power factor change rate acquisition process is as follows:

[0047] Use a power factor meter combined with power to calculate the load power factor at multiple time points. Calculate the load power factor change rate based on the load power factor and time points. The formula is as follows:

[0048] ;

[0049] Where, is the load power factor change rate, is the load power factor measured for the k+1th time, is the time point of the k+1th measurement, is the load power factor measured for the kth time, is the time point of the kth measurement.

[0050] In a preferred embodiment, the process of obtaining the state diagnosis coefficient is as follows:

[0051] Combine the current fluctuation coefficient, the load power factor change rate and the voltage transformer field calibration coefficient into a characteristic vector A;

[0052] Label each feature vector with the corresponding state category y, where the normal state is marked as +1 and the abnormal state is marked as -1;

[0053] The feature vector A and the corresponding state category y form a data set, and the data set is divided into a training set and a test set according to a certain ratio;

[0054] The decision function value of the samples in the test set is obtained based on the sequential minimum optimization algorithm, and the absolute value of the decision function value is calculated to obtain the state diagnosis coefficient.

[0055] In a preferred embodiment, the process of comparing and analyzing the state diagnosis coefficient with the state diagnosis threshold to diagnose whether the voltage sensor state is abnormal is as follows:

[0056] Compare the calculated state diagnosis coefficient with the state diagnosis threshold:

[0057] If the status diagnosis coefficient is greater than or equal to the status diagnosis threshold, the diagnosis voltage sensor status is not abnormal;

[0058] If the status diagnosis coefficient is less than or equal to the status diagnosis threshold, diagnose that the voltage sensor status is abnormal, analyze the cause of the abnormal voltage sensor status, and take corresponding maintenance measures.

[0059] The technical effects and advantages of the voltage transformer on-site calibration system and status diagnosis method of the present invention are as follows:

[0060] 1. This invention constructs comprehensive calibration indicators by simultaneously collecting parameters such as the primary and secondary voltages of the voltage transformer (VT), as well as the phase difference. Compared to traditional calibration methods that rely solely on comparing a single voltage parameter, this invention comprehensively considers multiple key performance indicators of the VT. This multi-parameter fusion approach more accurately reflects the actual performance of the VT, significantly improving the accuracy of calibration results and effectively reducing the operational risks of the power system caused by inaccurate calibration. Advanced measurement equipment and complex calculation formulas are employed in measuring the parameters of the standard VT and in the subsequent calculation of the transformation ratio and phase difference. For example, when measuring the primary and secondary voltages, high-precision voltage sensors are used, and signal preprocessing, including filtering, noise removal, and environmental correction, is performed. When calculating the transformation ratio, a weighted average method is used to determine the final transformation ratio through statistical analysis of the instantaneous transformation ratio sequence, making the calculation more accurate. In the phase difference calculation, algorithms such as the Hilbert transform and Kalman filter are used to effectively reduce the impact of measurement errors and interference, further improving calibration accuracy. The calibration system monitors the on-site electromagnetic environment in real time and adaptively adjusts the sampling frequency based on the main frequency component range of the interference signal using a formula. In a complex electromagnetic environment, the traditional fixed sampling frequency calibration system is easily interfered with, resulting in inaccurate sampling data, which in turn affects the calibration results. The adaptive sampling frequency adjustment mechanism of the present invention can perform more intensive sampling on the frequency bands sensitive to interference signals in a targeted manner, effectively reducing the impact of interference on the calibration data, ensuring that the voltage transformer signal can be accurately collected in various complex electromagnetic environments, and improving the reliability and stability of the calibration system. The power module of the calibration system can monitor the input power voltage in real time through a formula according to different on-site power supply conditions, and dynamically adjust the transformation ratio to ensure that a stable output voltage is used to power all parts of the system. In the actual power system site, the power supply conditions are complex and changeable, and there may be problems such as voltage fluctuations and harmonics. The adaptive adjustment function of the power module of the present invention enables the calibration system to work normally under different power supply conditions, avoids calibration interruptions or data errors caused by unstable power supply, and enhances the environmental adaptability of the calibration system.

[0061] 2. The present invention utilizes big data analysis technology to collect a large amount of historical calibration data and operating status data of voltage transformers of different models, operating times, and working conditions, including parameters such as voltage error, phase error, ambient temperature, operating time, load characteristics, and insulation performance. A support vector machine algorithm is used to construct a state diagnosis model. By finding the optimal classification hyperplane, the data in the low-dimensional space is mapped to a high-dimensional space for classification. Compared with traditional state diagnosis methods that rely on manual experience, the diagnosis model based on big data and advanced algorithms of the present invention can more comprehensively and accurately analyze the operating status of the voltage transformer, provide early warning of potential faults, and improve the safety and reliability of the power system. The state diagnosis coefficient is obtained through the state diagnosis model and compared with the pre-set state diagnosis threshold to determine whether the voltage transformer has an abnormality. This quantitative diagnosis method has clear judgment criteria, avoids the influence of subjective factors, and improves the accuracy and consistency of the diagnosis results. At the same time, the state diagnosis threshold can be flexibly adjusted according to different application scenarios and the importance of the voltage transformer to achieve personalized state diagnosis, better meeting the actual needs of power system operation and maintenance. The present invention integrates the on-site calibration and status diagnosis functions of voltage transformers into a single system, eliminating the cumbersome steps required to use multiple independent devices and perform multiple operations during traditional calibration and diagnosis. Workers can complete all tasks from calibration to diagnosis on a single system platform, significantly improving work efficiency and saving time and labor costs. Accurate status diagnosis enables the early detection of potential faults in voltage transformers, allowing timely maintenance measures to be taken, avoiding power outages and equipment damage caused by equipment failure. This not only reduces the economic losses caused by power outages, but also lowers the cost of equipment repair and replacement, enabling preventive maintenance of the power system and improving the overall economic benefits of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 The present invention is a schematic structural diagram of a voltage transformer on-site calibration system and status diagnosis method. DETAILED DESCRIPTION

[0063] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0064] Example 1, Figure 1 Provided are a voltage transformer on-site calibration system and a state diagnosis method.

[0065] Measure the primary voltage and secondary voltage of the standard voltage transformer, and calculate the voltage transformer ratio and standard voltage transformer phase difference based on the primary voltage and secondary voltage of the standard voltage transformer;

[0066] The process of measuring the primary and secondary voltages of a standard voltage transformer is as follows:

[0067] Use high-precision voltage measuring equipment to measure the primary and secondary voltages of standard voltage transformers;

[0068] Connect the measuring device to the primary and secondary sides of a standard voltage transformer;

[0069] It should be noted that electrical safety regulations must be strictly followed during connection to ensure good electrical connection between the measuring device and the voltage transformer to avoid problems such as poor contact or short circuit.

[0070] When the standard voltage transformer is operating normally, start the measuring equipment and record the measured values of the primary voltage and secondary voltage;

[0071] In order to improve the accuracy of the measurement, multiple measurements were performed and the average value was taken as the final measurement result.

[0072] The specific process of calculating the voltage transformer ratio based on the primary voltage and secondary voltage of the standard voltage transformer is as follows:

[0073] The voltage transformer ratio is obtained by calculating the ratio of the primary voltage to the secondary voltage of the standard voltage transformer;

[0074] The voltage transformer ratio reflects the ability of the voltage transformer to convert high voltage into low voltage. The specific calculation formula is as follows:

[0075] ;

[0076] Where B is the voltage transformer ratio, is the primary voltage measurement value of a standard voltage transformer, It is the secondary voltage measurement value of a standard voltage transformer.

[0077] The process of calculating the standard voltage transformer phase difference is as follows:

[0078] Use the data acquisition system to collect the primary voltage and secondary voltage signals to obtain discrete voltage signal sequences and , where n is the sampling point number;

[0079] Preprocess the collected voltage signal, including filtering and denoising operations, to improve the signal quality;

[0080] Perform Fourier transform on the preprocessed voltage signal to obtain the spectrum of the primary voltage and secondary voltage signals respectively. and , where k is the frequency component number;

[0081] Extract the phase of the fundamental components of the primary and secondary voltages from the spectrum and ;

[0082] According to the phase of the fundamental component of the primary voltage and the secondary voltage and Calculating the Phase Difference of a Standard Voltage Transformer , the formula is: .

[0083] The voltage transformer secondary voltage is obtained according to the voltage transformer primary voltage and the voltage transformer ratio combined with the adaptive frequency adjustment, and the voltage transformer phase difference is obtained in combination with the voltage transformer primary voltage;

[0084] A high-precision voltage sensor is connected to the primary side of the voltage transformer with a certain initial sampling frequency. Primary voltage of voltage transformer Sampling is performed to obtain a discrete voltage sequence ,in N is the number of sampling points;

[0085] Perform spectrum analysis on the collected primary voltage sequence, use fast Fourier transform to obtain the signal spectrum, and analyze the frequency components and intensity distribution of the interference signal in the spectrum;

[0086] Determine the interference frequency range based on the frequency components and intensity distribution of the interference signal and the interference signal strength;

[0087] The process of obtaining the interference signal strength is as follows:

[0088] For narrowband interference, the amplitude value of the interference signal at its center frequency is directly read as a measure of the interference signal strength;

[0089] For broadband interference, it is necessary to integrate the power within the frequency band occupied by the interference signal to obtain the interference signal strength. The specific process is as follows:

[0090] The power spectrum density function is measured by a spectrum analyzer, and the interference signal strength is obtained by integration calculation based on the main interference frequency range. The specific calculation formula is as follows:

[0091] ;

[0092] Where, is the interference signal strength, and the interference frequency range is , is the power spectral density function;

[0093] The corresponding spectrum index is obtained according to the main interference frequency range, and the sampling frequency is adjusted based on the interference signal strength and the initial sampling frequency. The calculation formula is as follows:

[0094] ;

[0095] Where, is to adjust the sampling frequency; is the initial sampling frequency; is the interference signal strength; is the reference interference signal strength; is the spectrum of the signal; Interference frequency The corresponding spectrum index; 、 To adjust the coefficient, it is necessary to calibrate and determine it according to the actual situation;

[0096] Use the adjusted sampling frequency to resample the primary voltage of the voltage transformer to obtain a new primary voltage sequence ; It can capture the characteristics of the primary voltage signal more accurately and reduce the impact of interference;

[0097] When calculating the secondary voltage, not only the voltage transformer ratio k should be considered, but also the impact of environmental factors on the ratio;

[0098] Obtain the ambient temperature and humidity when measuring the primary voltage, and combine the new primary voltage sequence and the voltage transformer ratio to calculate the voltage transformer secondary voltage sequence. The specific calculation formula is as follows:

[0099] ;

[0100] Where, is the voltage transformer secondary voltage sequence, is the new primary voltage sequence, N is the number of sampling points, B is the voltage transformer ratio, T is the ambient temperature, is the ambient temperature reference value, is the ambient humidity, is the ambient humidity reference value, 、 are the weight coefficients of ambient temperature and humidity, respectively, which are determined by the historical environment.

[0101] The specific process of obtaining the voltage transformer phase difference based on the voltage transformer secondary voltage and the voltage transformer primary voltage is as follows:

[0102] By comparing the signs of adjacent sampling points, the zero-crossing points of the new primary voltage sequence and the secondary voltage sequence of the voltage transformer are found respectively. The zero-crossing point refers to the point where the signal passes through the zero level from negative to positive or from positive to negative.

[0103] Record the sampling moments of adjacent zero crossing points of the primary and secondary voltage signals and , combined with the signal period t to calculate the voltage transformer phase difference, the formula is .

[0104] The voltage error rate is calculated based on the standard voltage transformer secondary voltage and the voltage transformer secondary voltage. A comprehensive calibration index model is constructed by combining the standard voltage transformer phase difference and the voltage transformer phase difference to obtain the voltage transformer on-site calibration coefficient.

[0105] The voltage transformer secondary voltage is calculated by weighted summation of the voltage transformer secondary voltage sequence. The voltage error rate is calculated by combining the standard voltage transformer secondary voltage. The specific formula is as follows:

[0106] ;

[0107] Where, is the voltage error rate, is the standard voltage transformer secondary voltage, is the voltage transformer secondary voltage;

[0108] The expression of the comprehensive verification index model is:

[0109] ;

[0110] Where X is the voltage transformer field calibration coefficient, is the standard voltage transformer phase difference, is the voltage transformer phase difference, w is the voltage error rate, , , is the calibration index, determined by historical calibration data.

[0111] It should be noted that constructing a comprehensive calibration index model and obtaining the voltage transformer field calibration coefficient plays many important roles, mainly reflected in the following aspects:

[0112] Accurately assess transformer performance: Voltage transformer performance evaluation cannot rely solely on a single metric. A comprehensive calibration index model considers multiple key factors, including voltage error rate and phase difference. By rationally integrating these factors, the resulting on-site calibration coefficient comprehensively and accurately reflects the voltage transformer's overall performance under actual operating conditions, including its transformation ratio accuracy and phase characteristics. This allows for a more precise assessment of whether the transformer meets the power system's operational requirements.

[0113] Improved calibration accuracy: Traditional calibration methods may focus only on a subset of parameters, often overlooking factors that significantly impact transformer performance, leading to biased calibration results. The comprehensive calibration index model, however, uses a mathematical model to comprehensively analyze multiple parameters, more comprehensively considering the interrelationships between various factors. This effectively improves calibration accuracy, reduces errors, and provides more reliable assurance for the safe and stable operation of power systems.

[0114] Facilitates fault diagnosis and location: When a voltage transformer experiences an anomaly, the calibration coefficient derived from the comprehensive calibration index model can help personnel more quickly locate the fault type and location. For example, if the voltage error rate or phase difference is abnormal, by analyzing the changes in the calibration coefficient and the relationship between these parameters, it can be determined whether the transformer has a winding fault, an iron core problem, or another related component failure. This provides a strong basis for subsequent maintenance and commissioning, shortens fault resolution time, and improves power system reliability.

[0115] Providing a basis for condition assessment: Combined with voltage transformer operating status data, the field calibration coefficient is an important foundation for building a condition diagnosis model. It provides a quantitative indicator for condition diagnosis. By comparing it with historical data and standard values under normal operating conditions, it can promptly identify performance trends of voltage transformers and predict potential failure risks in advance. This allows for condition monitoring and preventive maintenance of voltage transformers, reducing operational risks in the power system and improving equipment lifespan and efficiency.

[0116] Meeting the needs of diverse application scenarios: Different power system applications may place varying performance requirements on voltage transformers. The comprehensive calibration index model adjusts the weights of various parameters based on the specific application scenario and requirements, resulting in a field calibration coefficient tailored to the specific scenario. This ensures accurate performance assessment of voltage transformers under varying operating conditions, meeting the diverse operational needs of power systems.

[0117] The working status data of the voltage transformer is collected. Combined with the on-site calibration coefficient of the voltage transformer, the support vector machine algorithm is used to construct a status diagnosis model to obtain the status diagnosis coefficient. The status diagnosis coefficient is compared and analyzed with the status diagnosis threshold to diagnose whether there is any abnormality in the voltage sensor status.

[0118] The working status data includes current fluctuation coefficient and load power factor change rate;

[0119] The process of obtaining the current fluctuation coefficient is as follows:

[0120] In the secondary side circuit of the voltage transformer, a high-precision current transformer is connected in series to collect the load current in real time and obtain the load current sequence ;

[0121] According to the load current sequence, the maximum and minimum values of the load current are obtained, and the average value of the load current is calculated to obtain the current fluctuation coefficient. The specific calculation formula is as follows:

[0122] ;

[0123] Where, is the current fluctuation coefficient, Average load current, is the maximum load current, is the minimum load current;

[0124] The process of obtaining the load power factor change rate is as follows:

[0125] Use a power factor meter combined with power to calculate the load power factor at multiple time points. Calculate the load power factor change rate based on the load power factor and time points. The formula is as follows:

[0126] ;

[0127] Where, is the load power factor change rate, is the load power factor measured for the k+1th time, is the time point of the k+1th measurement, is the load power factor measured for the kth time, is the time point of the kth measurement.

[0128] Combine the current fluctuation coefficient, the load power factor change rate and the voltage transformer field calibration coefficient into a characteristic vector A;

[0129] Label each feature vector with the corresponding state category y, where the normal state is marked as +1 and the abnormal state is marked as -1;

[0130] The feature vector A and the corresponding state category y form a data set, and the data set is divided into a training set and a test set according to a certain ratio;

[0131] The decision function value of the samples in the test set is obtained based on the sequential minimum optimization algorithm, and the absolute value of the decision function value is calculated to obtain the state diagnosis coefficient.

[0132] By analyzing the training set and a large amount of historical data, a suitable status diagnostic threshold is determined using methods such as cross-validation and receiver operating characteristic (ROC) analysis.

[0133] Compare the calculated state diagnosis coefficient with the state diagnosis threshold:

[0134] If the status diagnosis coefficient is greater than or equal to the status diagnosis threshold, the diagnosis voltage sensor status is not abnormal;

[0135] If the status diagnosis coefficient is less than or equal to the status diagnosis threshold, it is diagnosed that the voltage sensor status is abnormal, and the specific cause of the abnormal voltage sensor status is analyzed so that corresponding maintenance measures can be taken.

[0136] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0137] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0138] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0139] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0140] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

[0141] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for on-site calibration and status diagnosis of a voltage transformer, characterized in that: The following steps are involved: Measure the primary voltage and secondary voltage of the standard voltage transformer, and calculate the voltage transformer ratio and standard voltage transformer phase difference based on the primary voltage and secondary voltage of the standard voltage transformer; The voltage transformer secondary voltage is obtained according to the voltage transformer primary voltage and the voltage transformer ratio combined with the adaptive frequency adjustment, and the voltage transformer phase difference is obtained in combination with the voltage transformer primary voltage; The voltage error rate is calculated based on the standard voltage transformer secondary voltage and the voltage transformer secondary voltage. A comprehensive calibration index model is constructed by combining the standard voltage transformer phase difference and the voltage transformer phase difference to obtain the voltage transformer on-site calibration coefficient. The expression of the comprehensive calibration index model is: ； Where X is the voltage transformer field calibration coefficient, is the standard voltage transformer phase difference, is the voltage transformer phase difference, w is the voltage error rate, , , is the calibration index, determined by historical calibration data; The working status data of the voltage transformer is collected. Combined with the on-site calibration coefficient of the voltage transformer, the support vector machine algorithm is used to construct a status diagnosis model to obtain the status diagnosis coefficient. The status diagnosis coefficient is compared and analyzed with the status diagnosis threshold to diagnose whether there is any abnormality in the voltage sensor status.

2. A voltage transformer on-site calibration and status diagnosis method according to claim 1, characterized in that: The process of calculating the standard voltage transformer phase difference is as follows: The primary and secondary voltage signals are collected to obtain discrete voltage signal sequences. and , where n is the sampling point number; Preprocess the collected voltage signal, including filtering and denoising operations; Perform Fourier transform on the preprocessed voltage signal to obtain the spectrum of the primary voltage and secondary voltage signals respectively. and , where k is the frequency component number; Extract the phase of the fundamental components of the primary and secondary voltages from the spectrum and ; According to the phase of the fundamental component of the primary voltage and the secondary voltage and Calculating the Phase Difference of a Standard Voltage Transformer , the formula is: .

3. A voltage transformer on-site calibration and status diagnosis method according to claim 2, characterized in that: The process of adaptively adjusting the frequency is as follows: At the initial sampling frequency Primary voltage of voltage transformer Sampling is performed to obtain a discrete voltage sequence ,in N is the number of sampling points; Perform spectrum analysis on the collected primary voltage sequence, use fast Fourier transform to obtain the signal spectrum, and analyze the frequency components and intensity distribution of the interference signal in the spectrum; Determine the interference frequency range based on the frequency components and intensity distribution of the interference signal and the interference signal strength; The corresponding spectrum index is obtained according to the main interference frequency range, and the sampling frequency is adjusted based on the interference signal strength and the initial sampling frequency. The calculation formula is as follows: ； Where, is to adjust the sampling frequency; is the initial sampling frequency; is the interference signal strength; is the reference interference signal strength; is the spectrum of the signal; Interference frequency The corresponding spectrum index; 、 is the adjustment factor.

4. A voltage transformer on-site calibration and status diagnosis method according to claim 3, characterized in that: The interference signal strength acquisition process is as follows: For narrowband interference, the amplitude value of the interference signal at its center frequency is directly read as a measure of the interference signal strength; For broadband interference, it is necessary to integrate the power within the frequency band occupied by the interference signal to obtain the interference signal strength. The specific process is as follows: The power spectrum density function is measured by a spectrum analyzer, and the interference signal strength is obtained by integration calculation based on the main interference frequency range. The specific calculation formula is as follows: ； Where, is the interference signal strength, and the interference frequency range is , is the power spectral density function.

5. A method for on-site calibration and status diagnosis of a voltage transformer according to claim 4, characterized in that: The specific process of obtaining the voltage transformer phase difference is as follows: By comparing the signs of adjacent sampling points, the zero-crossing points of the new primary voltage sequence and the secondary voltage sequence of the voltage transformer are found respectively; Record the sampling moments of adjacent zero crossing points of the primary and secondary voltage signals and , combined with the signal period t to calculate the voltage transformer phase difference, the formula is .

6. A voltage transformer on-site calibration and status diagnosis method according to claim 5, characterized in that: The secondary voltage sequence acquisition process is as follows: The ambient temperature and humidity when measuring the primary voltage are combined with the new primary voltage sequence and the voltage transformer ratio to calculate the voltage transformer secondary voltage sequence. The specific calculation formula is as follows: ； Where, is the voltage transformer secondary voltage sequence, is the new primary voltage sequence, N is the number of sampling points, B is the voltage transformer ratio, T is the ambient temperature, is the ambient temperature reference value, is the ambient humidity, is the ambient humidity reference value, 、 are the weight coefficients of ambient temperature and humidity respectively.

7. A voltage transformer on-site calibration and status diagnosis method according to claim 6, characterized in that: The working status data includes current fluctuation coefficient and load power factor change rate; The current fluctuation coefficient acquisition process is as follows: In the secondary side circuit of the voltage transformer, a high-precision current transformer is connected in series to collect the load current in real time and obtain the load current sequence ; According to the load current sequence, the maximum and minimum values of the load current are obtained, and the average value of the load current is calculated to obtain the current fluctuation coefficient. The specific calculation formula is as follows: ； Where, is the current fluctuation coefficient, Average load current, is the maximum load current, is the minimum load current; The load power factor change rate acquisition process is as follows: Use a power factor meter combined with power to calculate the load power factor at multiple time points. Calculate the load power factor change rate based on the load power factor and time points. The formula is as follows: ； Where, is the load power factor change rate, is the load power factor measured for the k+1th time, is the time point of the k+1th measurement, is the load power factor measured for the kth time, is the time point of the kth measurement.

8. A voltage transformer on-site calibration and status diagnosis method according to claim 7, characterized in that: The process of obtaining the status diagnosis coefficient is as follows: Combine the current fluctuation coefficient, the load power factor change rate and the voltage transformer field calibration coefficient into a characteristic vector A; Label each feature vector with the corresponding state category y, where the normal state is marked as +1 and the abnormal state is marked as -1; The feature vector A and the corresponding state category y form a data set, and the data set is divided into a training set and a test set according to a certain ratio; The decision function value of the samples in the test set is obtained based on the sequential minimum optimization algorithm, and the absolute value of the decision function value is calculated to obtain the state diagnosis coefficient.

9. A method for on-site calibration and status diagnosis of a voltage transformer according to claim 8, characterized in that: The process of comparing and analyzing the state diagnosis coefficient with the state diagnosis threshold to diagnose whether the voltage sensor state is abnormal is as follows: Compare the calculated state diagnosis coefficient with the state diagnosis threshold: If the status diagnosis coefficient is greater than or equal to the status diagnosis threshold, the diagnosis voltage sensor status is not abnormal; If the status diagnosis coefficient is less than or equal to the status diagnosis threshold, diagnose that the voltage sensor status is abnormal, analyze the cause of the abnormal voltage sensor status, and take corresponding maintenance measures.

Images