CN-121995098-A - Self-repairing method and system for measuring error of magnetic array type current sensor

CN121995098ACN 121995098 ACN121995098 ACN 121995098ACN-121995098-A

Abstract

The invention discloses a self-repairing method and a system for measuring errors of a magnetic array type current sensor, and mainly relates to the technical field of error measurement and repair of current sensors. The method comprises the steps of obtaining a linear relation coefficient between output of a magnetic field sensing unit and current to be measured, calculating a covariance matrix of training data, carrying out singular value decomposition, determining the number of principal elements according to the singular value, carrying out normalization processing on test data, judging whether error abnormal magnetic field sensing units exist or not through whether statistics exceeds a control threshold value, combining all magnetic field sensing units in pairs, comparing the statistics, screening out two magnetic field sensing units with normal errors, and identifying all abnormal magnetic field sensing units through whether the combined statistics exceeds the threshold value. The invention has the beneficial effects that the self-repairing of the measurement error of the magnetic array type current sensor is realized, and the long-term measurement stability of the magnetic array type current sensor is ensured to a certain extent.

Inventors

DUAN XU
ZHAI JINKUI
MA WEN
LI LONG
HUANG QIYAN
LI HAO
ZHANG YONGKAI
LI SHISONG
LIU XIAOHU
YU HONG
YANG SEN
GU YANFENG
LIU SHU
XIE YUANYUAN
JU YI
FENG HAIQING
LIU HONGPU

Assignees

国网山东省电力公司济南供电公司
清华大学

Dates

Publication Date: 20260508
Application Date: 20251231

Claims (15)

1. The self-repairing method for the measurement error of the magnetic array type current sensor is characterized by comprising the following steps of: Obtaining linear relation coefficients between the output of each magnetic field sensing unit and the current to be measured by combining off-line calibration and on-line calibration; Collecting magnetic field data of a magnetic array type current sensor in a normal operation state as a training sample, carrying out normalization processing on the training data based on the linear relation coefficient, constructing a data matrix, calculating a covariance matrix of the data matrix, carrying out singular value decomposition on the covariance matrix, determining the number of principal elements according to singular values, separating principal element subspaces and residual subspaces, and establishing a mathematical model of the normal operation characteristic of the sensor; During the long-term running process of the sensor, collecting magnetic field data in real time as a test sample, processing the test data based on the same linear relation coefficient and normalization method, projecting the test data to the residual subspace, calculating Q statistic, and comparing the Q statistic with a preset control threshold to judge whether a magnetic field sensing unit with abnormal measurement error exists or not; When abnormality is detected, a combination analysis strategy is adopted, every two combinations of all magnetic field sensing units are traversed, the accumulated value of Q statistics of each combination in time is calculated, and two magnetic field sensing units with the smallest Q statistics accumulated value are screened out to be used as reference sensors with normal errors; and eliminating the measured data of the magnetic field sensing unit identified as abnormal, and recalculating the measured current value by using the measured value of the residual normal magnetic field sensing unit and the linear relation coefficient thereof through a weighted fusion algorithm to realize self-repairing of the measured error.
2. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein the obtaining of the linear relation coefficient through off-line calibration and on-line calibration comprises: when in off-line calibration, a high-precision current sensor is adopted to acquire a measured current reference value, output data of each magnetic field sensing unit are synchronously acquired, and a linear relation coefficient between output and reference current is calculated; And during on-line calibration, inverting the measured current through a current inversion algorithm based on the position information of each magnetic field sensing unit, wherein the position information comprises coordinates and magnetosensitive angles, and correcting the linear relation coefficient.
3. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein the normalization processing is performed on training data, specifically: Based on the mean value and standard deviation of the data of each magnetic field sensing unit in the training data, the training data is converted into standardized data with the mean value of 0 and the standard deviation of 1, so that the influence of the data magnitude differences of different magnetic field sensing units on analysis is eliminated.
4. A method for self-repairing a measurement error of a magnetic array type current sensor according to claim 3, wherein the determining the number of principal elements according to the singular values comprises: Calculating the cumulative contribution rate of the singular values, wherein when the cumulative contribution rate reaches a preset threshold value, the number of the singular values is the number of principal elements, and the value range of the preset threshold value is 80% -95%.
5. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein the Q statistic is calculated, specifically: The statistic is used for representing the projection amplitude of the test data in the residual subspace and reflecting the degree of deviation of the measured value of the magnetic field sensing unit from the normal linear correlation, and the value is the square sum of all components of the test data in the residual subspace.
6. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein the determining of the control threshold value comprises: And calculating a threshold value parameter based on residual characteristics of training data, and determining a control threshold value by combining a critical value of normal distribution under a preset confidence level, wherein the value range of the preset confidence level is 90% -99%.
7. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein traversing all combinations of magnetic field sensing units, screening out two magnetic field sensing units with the smallest Q statistic cumulative value as reference sensors with normal errors, comprising: And calculating accumulated values of statistics of each pair of magnetic field sensing unit combinations in the time length of the test data, and selecting the combination with the smallest accumulated value as two magnetic field sensing units with normal errors, wherein the smallest accumulated value indicates that the linear correlation of the combination is closest to a normal state.
8. A magnetic array type current sensor measuring error self-repairing method according to claim 1, wherein said computing the combined Q statistic comprises: And forming a ternary combination with two normal units for each magnetic field sensing unit to be detected, calculating statistics of the combination, judging that the unit to be detected is abnormal in error if the statistics exceed a control threshold value, and otherwise, judging that the error is normal.
9. The method for self-repairing measurement errors of a magnetic array type current sensor according to claim 1, wherein the recalculating the measured current value comprises: Inverting the measured current by a multi-source data fusion algorithm based on the output data of the normal magnetic field sensing unit and the linear relation coefficient of the output data and the measured current, wherein the multi-source data fusion algorithm comprises a weighted least square method or an optimization algorithm based on residual error minimization.
10. A system for implementing a method of self-repairing measurement errors of a magnetic array type current sensor as claimed in any one of claims 1 to 9, comprising: The calibration module is used for obtaining a linear relation coefficient between the output of the magnetic field sensing unit and the current to be measured through off-line calibration and on-line calibration; The training module is used for collecting magnetic field data in a normal running state as training data, carrying out normalization processing on the training data, calculating a covariance matrix and carrying out singular value decomposition, and determining the number of principal elements according to the singular values so as to separate a principal element subspace and a residual subspace; The monitoring module is used for collecting test data in long-term operation and carrying out normalization processing, constructing statistic and a control threshold thereof by combining residual subspace, and judging whether an error abnormal unit exists or not through comparison of the statistic and the threshold; the abnormal identification module is used for screening two normal units through combination of every two units based on a combination strategy, combining the rest units with the two normal units respectively, and identifying all abnormal units through statistics; and the self-repairing module is used for eliminating the abnormal unit, and recalculating the measured current by using the measurement result of the normal unit so as to realize error self-repairing.
11. The magnetic array type current sensor measurement error self-repairing system according to claim 10, wherein the calibration module comprises an offline calibration unit and an online calibration unit; the off-line calibration unit is configured to connect the high-precision reference sensor, synchronously collect the output of the magnetic field sensing unit and the reference current, and calculate the linear relation coefficient; The on-line calibration unit is configured to acquire the position parameters of the magnetic field sensing unit, invert the measured current based on the magnetic field distribution model, and dynamically correct the linear relation coefficient.
12. The magnetic array type current sensor measurement error self-repairing system according to claim 10, wherein the training module comprises a data preprocessing unit and a subspace separation unit; The data preprocessing unit is configured to normalize training data and eliminate data magnitude differences; The subspace separation unit is configured to calculate a covariance matrix of training data and perform singular value decomposition, determine the number of principal elements according to the singular values, and separate to obtain a principal element subspace and a residual subspace.
13. The magnetic array type current sensor measurement error self-repairing system according to claim 10, wherein the monitoring module comprises a test data processing unit and an abnormality early warning unit; The test data processing unit is configured to normalize test data acquired in real time and project the test data into a residual subspace; the abnormal early warning unit is configured to calculate statistics of the test data, compare the statistics with a control threshold, and send out early warning of the abnormal unit if the statistics exceeds the threshold.
14. The magnetic array type current sensor measurement error self-repairing system according to claim 10, wherein the abnormality identifying module comprises a combination analyzing unit and an abnormality determining unit; The combination analysis unit is configured to perform combination of all magnetic field sensing units in pairs, calculate a statistic accumulated value of each combination, and screen out two normal units with the smallest accumulated value; The abnormality determination unit is configured to combine the remaining units with two normal units, respectively, calculate a statistic of the combination, and compare with a threshold value, and determine an abnormal unit.
15. The magnetic array type current sensor measurement error self-repairing system according to claim 10, further comprising an extended application interface for adapting the system to error self-repairing scenes of other array type sensors, wherein the array type sensors comprise a distributed electric field sensor, a temperature sensor and a pressure sensor.

Description

Self-repairing method and system for measuring error of magnetic array type current sensor Technical Field The invention relates to the technical field of error measurement and repair of current sensors, in particular to a data-driven magnetic array type current sensor measurement error self-repair method and system. Background The current sensing equipment mainly used in the power system comprises an electromagnetic current transformer, an optical fiber current transformer, a shunt, a rogowski coil, a zero-flux current sensor and the like, and the performance of the electromagnetic current transformer, the optical fiber current transformer, the shunt, the rogowski coil, the zero-flux current sensor and the like have obvious differences in the aspects of frequency bands, insulation, cost and the like of current measurement. For example, an electromagnetic current transformer is mainly applied to low-frequency (< 1 kHz) current measurement, and is outstanding in long-term measurement stability, however, as the voltage level increases, the complexity, cost, weight and the like of an insulation structure also increase sharply, measurement of direct current cannot be achieved, the optical fiber current transformer has obvious performance advantages, can achieve alternating current and direct current measurement, has the characteristics of wide frequency band (DC-hundred kHz), good insulating property, strong anti-interference capability, light weight and the like, but a core optical device for magnetic field sensing is sensitive to environmental factors such as temperature, vibration and the like, long-term measurement stability is to be further enhanced, the cost is high, a shunt achieves current measurement based on a resistance sampling principle, can achieve wide-frequency (DC-MHz) current measurement, but needs to be connected into an electric circuit, the measured current value cannot be further improved due to resistance heating, a rogue coil has natural advantages in high-frequency current measurement, but needs a complex integrating circuit, cannot measure direct current, and has poor low-frequency current measurement precision, a zero current sensor is based on zero-phase magnetic flux compensation, and a secondary coil generates a magnetic flux sensor, and has a compensation magnetic flux, and a magnetic flux sensor is in a high-feedback state, a high-phase current dynamic state is to be controlled, and has a high-current feedback state, and a high-current dynamic state is required to be balanced, and has a high-state, and a magnetic flux sensor is required to be in a high-state is required to be in a magnetic-phase-current feedback circuit, and a high-state magnetic-current sensor. The magnetic array type current sensor calculates the measured current through a reverse inversion algorithm based on the measurement of the measured current conductor space multipoint magnetic field. Broadband and redundancy are two of the technical features that they possess. Compared with the traditional single-source signal current sensing technical means, the magnetic array type current sensor has the technical characteristics of self-monitoring and self-repairing capability of self-measuring errors due to the redundancy of measured magnetic field information. During long-term operation, the measurement errors of part of the magnetic field sensing units in the magnetic array type current sensor can drift remarkably under the influence of environmental factors (temperature and the like) and the performance difference among different magnetic field sensing units, so that the current measurement accuracy of the magnetic array type current sensor is deteriorated or even exceeds the accuracy. Therefore, a method and a system for self-repairing measurement errors of a magnetic array type current sensor based on data driving are needed to solve the above problems. Disclosure of Invention The invention aims to provide a data-driven self-repairing method and system for measuring errors of a magnetic array type current sensor, which realize the self-repairing of the measuring errors of the magnetic array type current sensor and ensure the long-term measuring stability of the magnetic array type current sensor to a certain extent. The invention aims to achieve the aim, and the aim is achieved by the following technical scheme: in one aspect, a method for self-repairing measurement errors of a magnetic array current sensor is provided, which comprises the following steps: Acquiring an initial linear relation coefficient between the output of the magnetic field sensing unit and the current to be measured by combining off-line calibration and on-line calibration, and providing a basic parameter for subsequent error analysis; collecting magnetic field data of a magnetic array type current sensor in a normal running state as a training sample, carrying out normalization processing on the training data based on an initial linear rela