A medium and high voltage switch cabinet operation state on-line monitoring system

Abstract

The application relates to the technical field of state monitoring, and discloses a kind of medium and high voltage switch cabinet operating state on-line monitoring system, system includes: collaborative analysis unit, standard analysis unit, distributed computing unit, dielectric attenuation unit and state judging unit, through the collaborative calculation and cooperation of multiple units, realize the deep decoupling and accurate evaluation of mechanical vibration interference and partial discharge ultrasonic signal, in analysis, can effectively inhibit the mechanical vibration noise similar to the frequency of partial discharge, reduce the false alarm rate of dielectric strength monitoring, ensure that the medium and high voltage switch cabinet under vibration environment can still have stable and accurate operating state monitoring effect.

Description

Technical Field

[0001] This invention relates to the field of condition monitoring technology, and specifically to an online monitoring system for the operating status of medium and high voltage switchgear. Background Technology

[0002] Currently, during the operation of medium and high voltage switchgear, it is usually necessary to monitor the dielectric strength of the insulating components inside the switchgear online. This is often done by using different sensors to collect partial discharge signals inside the switchgear, and judging whether the dielectric performance of the insulating components is normal based on whether the signal amplitude exceeds a preset threshold, thereby determining the operating status of the medium and high voltage switchgear.

[0003] However, the above monitoring methods still have the following drawbacks: In large factories, large equipment near medium and high voltage switchgear will generate mechanical vibration interference. This vibration will produce noise with a frequency similar to that of partial discharge ultrasonic signals, which will be superimposed on the partial discharge ultrasonic signals of insulating parts. Existing technologies cannot specifically suppress this type of noise, making it difficult to effectively distinguish between mechanical vibration noise and partial discharge ultrasonic signals. This increases the false alarm rate of dielectric strength monitoring, thus making it impossible to effectively monitor the operating status of high voltage switchgear online. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an online monitoring system for the operating status of medium and high voltage switchgear, which solves the aforementioned problems.

[0005] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0006] An online monitoring system for the operating status of medium and high voltage switchgear includes:

[0007] The collaborative analysis unit is used to acquire the partial discharge signal of the target component and the vibration signal of the target object in real time, and to perform fusion calculation on the partial discharge signal and the vibration signal of the target object to obtain the aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise.

[0008] The standard analysis unit is used to analyze vibration interference in the aliased signal vector and generate a vibration interference threshold representing the standard for judging mechanical vibration noise.

[0009] The distributed computing unit is used to analyze the aliased signal vector based on the vibration interference threshold, perform signal separation, and generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component.

[0010] The dielectric attenuation unit is used to analyze the correlation of dielectric properties of the target component based on the partial discharge ultrasonic sequence and generate dielectric attenuation characteristic values ​​representing the dielectric strength state of the target component.

[0011] The status determination unit is used to acquire the partial discharge ultrasonic signal under normal operating conditions of the target component, and to perform collaborative analysis on the partial discharge ultrasonic signal, partial discharge ultrasonic sequence and dielectric attenuation characteristic value to obtain the status identifier of the target object.

[0012] Furthermore, the partial discharge signal and the vibration signal of the target object are fused and calculated to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise, including:

[0013] Transmission delay analysis is performed on the preprocessed partial discharge signal and vibration signal to generate a synchronization calibration vector representing the correlation between the partial discharge of the target component and the vibration of the target object.

[0014] Furthermore, the partial discharge signal and the vibration signal of the target object are fused and calculated to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise, which also includes:

[0015] Based on the synchronous calibration vector, the preprocessed partial discharge signal and vibration signal are normalized to generate a dielectric vibration amplitude sequence.

[0016] Based on the dielectric vibration amplitude sequence, the fluctuation consistency between partial discharge and vibration interference is analyzed, and a correlation factor representing the dynamic correlation between the dielectric state of the target component and vibration interference is obtained.

[0017] Furthermore, the partial discharge signal and the vibration signal of the target object are fused and calculated to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise, which also includes:

[0018] Based on the correlation factor, the superposition characteristics of partial discharge signal and mechanical vibration interference noise are integrated to obtain an aliased signal vector representing the superposition characteristics of partial discharge signal and mechanical vibration interference noise.

[0019] Furthermore, vibration interference in the aliased signal vector is analyzed to generate a vibration interference threshold representing the standard for judging mechanical vibration noise, including:

[0020] Based on the aliased signal vector, the frequency ranges of the partial discharge signal and the vibration signal are extracted to obtain the vibration screening coefficient representing the matching degree between the partial discharge frequency band and the vibration interference.

[0021] Based on the vibration screening coefficient, the amplitude of the selected vibration signal frequency range is calculated to obtain the vibration interference threshold representing the standard for judging mechanical vibration noise.

[0022] Furthermore, based on the vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge in the target component, including:

[0023] Based on the vibration interference threshold and the aliasing signal vector, the intersection analysis of the dielectric signal and the interference signal is performed to obtain the discrimination coefficient representing the distinguishability between the partial discharge signal and the vibration interference signal.

[0024] The aliased signal vector is processed by the discrimination coefficient to obtain the separation purity coefficient, which represents the purity of the two types of signals after separation.

[0025] Furthermore, based on the vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component. This also includes:

[0026] Based on the separation purity coefficient, the separated partial discharge signal is corrected to obtain a partial discharge ultrasonic sequence that represents the time-domain distribution of the effective ultrasonic signal generated by the partial discharge of the target component.

[0027] Furthermore, based on the partial discharge ultrasonic sequence, the dielectric properties of the target component are analyzed to generate dielectric attenuation characteristic values ​​representing the dielectric strength state of the target component, including:

[0028] Based on the partial discharge ultrasonic sequence, the correlation between the dielectric properties of the target component and the time-domain signal is analyzed to obtain the dielectric signal correlation degree, which represents the correlation between the partial discharge signal and the dielectric state of the target component.

[0029] Based on the correlation of dielectric signals, the time-series decay law of the dielectric properties of the target component is fitted to obtain the dielectric decay characteristic value representing the dielectric strength state of the target component.

[0030] Furthermore, a collaborative analysis of the partial discharge ultrasonic signal, partial discharge ultrasonic sequence, and dielectric attenuation characteristic values ​​is performed to obtain the status identifier of the target object, including:

[0031] The dielectric reference coefficient, representing the reference reference corresponding to the normal dielectric strength of the target component, is obtained by calculating the partial discharge ultrasonic signal and the partial discharge ultrasonic sequence.

[0032] Furthermore, a collaborative analysis of the partial discharge ultrasonic signal, partial discharge ultrasonic sequence, and dielectric attenuation characteristic values ​​is performed to obtain the status identifier of the target object, which also includes:

[0033] The state identifier of the target object is obtained by comparing the dielectric attenuation characteristic value with the dielectric reference coefficient.

[0034] In summary, the present invention has the following main beneficial effects:

[0035] By adaptively aligning the partial discharge signal and vibration signal with time and scaling the amplitude using synchronous calibration vectors and correlation factors, superposition distortion caused by transmission path differences is effectively eliminated, allowing the aliased signal vector to truly reflect the actual working condition of the insulation component. A vibration interference threshold and vibration screening coefficient are dynamically constructed based on the absolute median difference of the instantaneous frequency value, enabling adaptive adjustment of the judgment criteria according to the vibration environment, thus avoiding frequent false alarms caused by fixed thresholds. Simultaneously, intersection analysis and precise separation of the aliased signal vector are performed using the discrimination coefficient and separation purity coefficient. Combined with adaptive neighborhood correction, a high-purity partial discharge ultrasonic sequence is generated, improving the detection rate of partial discharge pulses under strong vibration backgrounds and further reducing residual vibration interference. Finally, dielectric sensitivity factors and dielectric signal correlation are extracted from pulse peak value, pulse width, and pulse energy to obtain dielectric attenuation characteristic values, which are compared with the dielectric reference coefficient to ultimately obtain a status indicator reflecting the target object's state. This scheme can effectively suppress mechanical vibration noise similar to the partial discharge frequency, reduce the false alarm rate of dielectric strength monitoring, and ensure the monitoring effect of medium and high voltage switchgear operation status under vibration environments. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of an online monitoring system for the operating status of medium and high voltage switchgear according to the present invention. Detailed Implementation

[0037] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] refer to Figure 1 An online monitoring system for the operating status of medium and high voltage switchgear includes:

[0039] The collaborative analysis unit is used to acquire the partial discharge signal of the target component and the vibration signal of the target object in real time, and to perform fusion calculation on the partial discharge signal and the vibration signal of the target object to obtain the aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise.

[0040] The target object is a medium- and high-voltage switchgear, and the target component is an insulating component;

[0041] The standard analysis unit is used to analyze vibration interference in the aliased signal vector and generate a vibration interference threshold representing the standard for judging mechanical vibration noise.

[0042] The distributed computing unit is used to analyze the aliased signal vector based on the vibration interference threshold, perform signal separation, and generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component.

[0043] The dielectric attenuation unit is used to analyze the correlation of dielectric properties of the target component based on the partial discharge ultrasonic sequence and generate dielectric attenuation characteristic values ​​representing the dielectric strength state of the target component.

[0044] The status determination unit is used to acquire the partial discharge ultrasonic signal under normal operating conditions of the target component, and to perform collaborative analysis on the partial discharge ultrasonic signal, partial discharge ultrasonic sequence and dielectric attenuation characteristic value to obtain the status identifier of the target object.

[0045] In one embodiment, the partial discharge signal and the vibration signal of the target object are fused to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise, including:

[0046] Transmission delay analysis is performed on the preprocessed partial discharge signal and vibration signal to generate a synchronization calibration vector representing the correlation between the partial discharge of the target component and the vibration of the target object. Specifically, this includes: extracting the start time of each pulse from the partial discharge signal in seconds, and extracting all zero-crossing moments from the vibration signal in seconds.

[0047] Calculate the absolute value of the time difference between the start time and the zero-crossing time of each pair of pulses, and select pairs with a time difference of no more than 1 microsecond as valid association pairs. For each pair of valid association pairs, calculate the difference between the vibration zero-crossing time and the start time of the partial discharge pulse to obtain multiple time delay values. Sort all time delay values ​​in ascending order of value, and then select the time delay value in the middle position after sorting as the inherent transmission delay. If the total number of time delay values ​​is even, take the arithmetic mean of the two middle time delay values ​​as the inherent transmission delay.

[0048] For each valid correlation pair, the amplitude of the vibration signal and the amplitude of the partial discharge signal are read separately, with the amplitude unit being volts. The ratio of the vibration amplitude to the partial discharge amplitude in each valid correlation pair is calculated, and then the arithmetic mean of these ratios is calculated to obtain the amplitude coefficient. The inherent transmission delay and the amplitude coefficient are combined into a two-dimensional vector, which is the synchronization calibration vector representing the correlation between the partial discharge of the target component and the vibration of the target object. The synchronization calibration vector is a composite vector, and the inherent transmission delay and the amplitude coefficient are used for time alignment and amplitude scaling, respectively.

[0049] In one embodiment, the process of fusing the partial discharge signal and the vibration signal of the target object to obtain an aliased signal vector representing the superposition of the partial discharge signal and mechanical vibration interference noise further includes:

[0050] Based on the synchronization calibration vector, the preprocessed partial discharge signal and vibration signal are normalized to generate a dielectric vibration amplitude sequence. Specifically, the vibration signal is shifted along the time axis according to the inherent transmission delay in the synchronization calibration vector, that is, the inherent transmission delay is subtracted from the time values ​​of all sampling points of the vibration signal, so that the vibration signal and the partial discharge signal are precisely aligned in terms of occurrence time.

[0051] The amplitude of the translated vibration signal is scaled by the amplitude coefficient in the synchronous calibration vector, that is, the vibration amplitude at each sampling point is divided by the amplitude coefficient, so that the vibration signal and the partial discharge signal are under the same amplitude reference.

[0052] The aligned and scaled vibration signal is added point by point to the original partial discharge signal at the same sampling time to obtain the aliased signal sequence. The aliased signal sequence is divided according to a fixed time window length, and the maximum amplitude value within each time window is arranged in chronological order to form a dielectric vibration amplitude sequence. The dielectric vibration amplitude sequence is used to reflect the time-domain intensity distribution after the superposition of partial discharge and mechanical vibration.

[0053] Based on the dielectric vibration amplitude sequence, the fluctuation consistency between partial discharge and vibration interference is analyzed to obtain the correlation factor representing the dynamic correlation between the dielectric state of the target component and vibration interference. Specifically, this includes finding the maximum amplitude of each time window from the dielectric vibration amplitude sequence and calculating the rate of change of the maximum amplitude between two adjacent time windows.

[0054] From the original vibration signal, the same time window division method as the aliased signal sequence is used to calculate the effective value of the vibration signal in each time window, i.e., the root mean square value, with the unit being volts, which is the same as the amplitude. Similarly, the relative rate of change of the effective value of vibration between adjacent time windows is calculated.

[0055] The two sets of relative rate of change sequences are matched one-to-one according to the time window number. The number of time windows with the same sign (i.e., both positive or both negative) is divided by the total number of adjacent window pairs. If the calculation result is ≥1, it is 1; if the calculation result is ≤0, it is 0. The adjusted calculation result is the ratio. The ratio is mainly used to reflect the consistency of the direction of the fluctuation of partial discharge intensity and the fluctuation of vibration intensity.

[0056] Calculate the coefficient of variation of all the largest amplitude values ​​in the dielectric vibration amplitude sequence, multiply the directional consistency ratio by the coefficient of variation, and obtain the correlation factor that represents the dynamic correlation between the dielectric state of the target component and vibration interference. The larger the value of the correlation factor, the more the partial discharge intensity changes drastically in the same direction when the mechanical vibration fluctuation is large, which can reflect the degree of dynamic coupling of the dielectric state of the insulating component to vibration interference.

[0057] In one embodiment, the process of fusing the partial discharge signal and the vibration signal of the target object to obtain an aliased signal vector representing the superposition of the partial discharge signal and mechanical vibration interference noise further includes:

[0058] Based on the correlation factor, the superposition characteristics of partial discharge signal and mechanical vibration interference noise are integrated to obtain an aliased signal vector representing the superposition characteristics of partial discharge signal and mechanical vibration interference noise. Specifically, for the aliased signal sequence, within each time window, the absolute average value of the amplitude of all sampling points within that window is calculated to obtain the average amplitude. The correlation factor is multiplied by the average amplitude and then divided by the mean of the average amplitude of all windows to obtain the local enhancement coefficient of each time window.

[0059] Multiply the amplitude of the sampling point within each time window by the local enhancement coefficient of the corresponding window to obtain the aliasing amplitude. Arrange the aliasing amplitudes in chronological order to form a one-dimensional vector, which is the aliasing signal vector representing the superposition characteristics of partial discharge signal and mechanical vibration interference noise.

[0060] By fusing the preprocessed partial discharge signal with the vibration signal of the target object, and generating a synchronous calibration vector containing inherent transmission delay and amplitude coefficient based on the precise matching of the pulse start time and zero-crossing time, the vibration signal and partial discharge signal are precisely aligned and regularized on the time axis and amplitude reference. This allows for the construction of a dielectric vibration amplitude sequence and the calculation of correlation factors and aliasing signal vectors. Consequently, the coupling degree between partial discharge and mechanical vibration can be determined from the time-domain superimposed signal, suppressing false alarms caused by vibration noise, improving the reliability of dielectric strength anomaly detection, and enabling online monitoring of the operating status of high-voltage switchgear.

[0061] In one embodiment, vibration interference in the aliased signal vector is analyzed to generate a vibration interference threshold representing the mechanical vibration noise judgment standard, including:

[0062] Based on the aliasing signal vector, the frequency ranges of the partial discharge signal and the vibration signal are extracted to obtain the vibration screening coefficient representing the matching degree between the partial discharge frequency band and the vibration interference. Specifically, this includes: finding all zero-crossing points in the aliasing signal vector where the aliasing amplitude changes from negative to positive or from positive to negative, recording the time corresponding to each zero-crossing point, calculating the time interval between two adjacent zero-crossing points, which corresponds to half a period of the signal, multiplying the half period by 2 to obtain the whole period duration, and taking the reciprocal of the whole period duration as the instantaneous frequency value in Hertz, thereby obtaining multiple instantaneous frequency values.

[0063] Sort multiple instantaneous frequency values ​​according to sampling, calculate the median of all instantaneous frequency values. If the number of instantaneous frequency values ​​is odd, take the middle instantaneous frequency value after sorting as the median. If the number of instantaneous frequency values ​​is even, calculate the arithmetic mean of the two middle instantaneous frequency values ​​as the median.

[0064] Calculate the absolute deviation of each instantaneous frequency value from the median, and then calculate the median of these absolute deviations to obtain the absolute median difference. Subtract the absolute median difference from the median to obtain the lower frequency limit, and add the absolute median difference to the median to obtain the upper frequency limit. The interval formed by these two values ​​is the main frequency interval of the partial discharge signal. Apply the same calculation method to the original vibration signal to obtain the main frequency interval of the vibration signal.

[0065] The instantaneous frequency values ​​obtained through calculation include not only the true frequency components of the partial discharge signal but also abnormal frequency values ​​caused by interference such as mechanical vibration and environmental noise. Since abnormal frequency values ​​often deviate significantly from the center, and the absolute median is a statistical measure that reflects the typical fluctuation range of frequency values ​​around the median, an interval can be adaptively constructed by extending the median to the left and right by an absolute median distance. Frequency values ​​within this interval deviate from the median by no more than 1 times the typical fluctuation range of all frequency values, and belong to the main distribution area in statistics. Frequency values ​​outside the interval deviate by more than 1 times the typical fluctuation range and can be regarded as outliers or interference components that need to be removed. Therefore, the above-mentioned main frequency interval is entirely determined by the central tendency and dispersion of the current data itself.

[0066] Divide the total width of the intersection of the main frequency range of partial discharge frequency and the main frequency range of vibration frequency by the width of the main frequency range of partial discharge frequency. If the calculation result is ≥1, then it is 1; if the calculation result is ≤0, then it is 0. The adjusted calculation result is the vibration screening coefficient, which represents the matching degree between the partial discharge frequency band and the vibration interference. The closer the vibration screening coefficient is to 1, the higher the frequency band matching degree between the vibration interference and the partial discharge signal.

[0067] Based on the vibration screening coefficient, the amplitude of the selected vibration signal frequency range is calculated to obtain the vibration interference threshold representing the standard for judging mechanical vibration noise. Specifically, this includes: for the vibration signal after amplitude scaling, only the signal segments whose instantaneous frequency is located in the main frequency range of the vibration signal are retained. The absolute values ​​of the amplitudes of all sampling points in these segments are sorted according to the sampling time to obtain a set of vibration amplitude sequences belonging to the target frequency components. The median and absolute median difference of the vibration amplitude sequence are calculated. The median and absolute median difference are added to the absolute median difference to obtain the basic threshold.

[0068] Calculate the ratio of the median to the absolute median difference of all instantaneous frequency values ​​within the main frequency range of the vibration signal. Then multiply the ratio by the vibration screening coefficient to obtain the adjustment factor. Divide the basic threshold by the sum of the adjustment factor and the vibration screening coefficient to obtain the vibration interference threshold, which represents the mechanical vibration noise judgment standard similar to the frequency of the partial discharge signal.

[0069] By calculating the instantaneous frequency value and adaptively constructing the main frequency ranges of partial discharge signals and vibration signals using the absolute median difference, a vibration screening coefficient is obtained. This coefficient can dynamically reflect the matching degree between the vibration frequency band and the partial discharge frequency band, and retain only the vibration amplitude sequence of the target frequency component. The vibration interference threshold is calculated by combining the time with the adjustment factor. This allows for the accurate separation of mechanical vibration noise with frequencies similar to the partial discharge ultrasonic signal, avoiding misjudging vibration as discharge, reducing the false alarm rate of dielectric strength monitoring, and ensuring accurate monitoring of the operating status of high-voltage switchgear under strong vibration environments.

[0070] In one embodiment, based on a vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component, including:

[0071] Based on the vibration interference threshold and the aliasing signal vector, the intersection analysis of the dielectric signal and the interference signal is performed to obtain the discrimination coefficient representing the distinguishability between the partial discharge signal and the vibration interference signal. Specifically, this includes: extracting the absolute value of the aliasing amplitude of all sampling points from the aliasing signal vector to obtain the first sequence, and simultaneously extracting the absolute value of the amplitude of all sampling points from the original vibration signal to obtain the second sequence.

[0072] Using the vibration interference threshold as a comparison benchmark, find all sampling point times in the first sequence whose absolute value is greater than the vibration interference threshold, and find all sampling point times in the second sequence whose absolute value is greater than the vibration interference threshold. Two sets of time are obtained respectively. The length of the two sets of time is counted, which is the number of points that exceed the vibration interference threshold in each set. These are the first count and the second count.

[0073] Calculate the number of intersection points of the two sets of time points, that is, the number of times when both the aliasing signal and the vibration signal exceed the vibration interference threshold at the same time, and obtain the count intersection. Then calculate the size of the union of the two sets of time points, that is, the number of all non-repeating time points in the two sets, and obtain the count union.

[0074] Divide the intersection of counts by the union of counts to obtain the overlap ratio. Then divide the absolute value of the difference between the first and second counts by the maximum value of the first and second counts to obtain the difference ratio. Multiply the overlap ratio by the difference ratio. If the calculation result is ≥1, it is 1; if the calculation result is ≤0, it is 0. The adjusted calculation result is the discrimination coefficient representing the distinction between partial discharge signal and vibration interference signal. The closer the discrimination coefficient is to 1, the more the part of the aliased signal exceeding the threshold and the part of the vibration interference signal exceeding the threshold overlap in spatiotemporal distribution and have a large difference in quantity, thus effectively distinguishing partial discharge from vibration interference. If the discrimination coefficient is close to 0, it means that the two are difficult to distinguish.

[0075] The aliased signal vector is processed by a discrimination coefficient to obtain a separation purity coefficient representing the purity of the two types of signals after separation. Specifically, the process includes: taking the median of all sampling points in the vibration amplitude sequence as the vibration reference value; multiplying the vibration reference value by the discrimination coefficient to obtain the dynamic offset; adding the vibration interference threshold to the dynamic offset to obtain the separation boundary value; the separation boundary value is a signal separation critical value obtained by dynamically adjusting the discrimination coefficient based on the vibration interference threshold, which is used to more accurately distinguish between partial discharge signals and vibration interference.

[0076] For each sampling point in the aliased signal vector, if the aliasing amplitude is less than or equal to the separation boundary value, the sampling point is directly classified as the separated partial discharge signal without any modification. If the aliasing amplitude is greater than the separation boundary value, the vibration amplitude of the corresponding point is checked to see if it is greater than the vibration reference value. If the vibration amplitude is greater than the vibration reference value, the product of the vibration amplitude and the square of the discrimination coefficient is subtracted from the aliasing amplitude of the point to obtain the aliasing amplitude after separation processing of the sampling point. If the vibration amplitude is less than or equal to the vibration reference value, the aliasing amplitude remains unchanged. After the above calculation, all the processed aliasing amplitudes are arranged in chronological order to form the separated partial discharge signal sequence.

[0077] The number of sampling points in the separated partial discharge signal sequence whose aliasing amplitude is still greater than the vibration interference threshold is counted as the residual points. Then, the total number of points in the original aliased signal sequence whose amplitude is greater than the vibration interference threshold is counted. The residual points are divided by the total number of points. If the calculation result is ≥1, it is 1; if the calculation result is ≤0, it is 0. The adjusted calculation result is the separation purity coefficient, which represents the purity of the two types of signals after separation. The closer the separation purity coefficient is to 1, the less residual vibration interference and the higher the purity of the two types of signals after separation.

[0078] In one embodiment, based on a vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component. The method further includes:

[0079] Based on the separation purity coefficient, the separated partial discharge signal is corrected to obtain a partial discharge ultrasonic sequence representing the time-domain distribution of the ultrasonic effective signal generated by the partial discharge of the target component. Specifically, for each sampling point in the separated partial discharge signal sequence, with it as the center, it is extended to the nearest zero crossing point in each direction to the left and right respectively to form a complete fluctuation period containing the sampling point. All sampling points in the period are taken as the adaptive neighborhood of the point.

[0080] Calculate the arithmetic mean of the amplitude of each sampling point in its adaptive neighborhood to obtain the local background estimate. At the same time, calculate the median of the absolute deviations of all amplitudes in the adaptive neighborhood from the arithmetic mean of the amplitudes in the adaptive neighborhood to obtain the local fluctuation intensity.

[0081] The correction factor is obtained by dividing the local fluctuation intensity by the product of the local fluctuation intensity and the separation purity coefficient. Then, the product of the correction factor and the local background estimate is subtracted from the aliasing amplitude after separation at each sampling point to obtain the corrected amplitude. All the corrected amplitudes are arranged in order of sampling time to obtain the partial discharge ultrasonic sequence representing the time domain distribution of the ultrasonic effective signal generated by the partial discharge of the target component.

[0082] By dynamically adjusting the separation boundary value using the discrimination coefficient, the aliasing amplitude is differentiated. When the vibration amplitude exceeds the vibration reference value and the aliasing amplitude is large, the product of the vibration amplitude and the square of the discrimination coefficient is subtracted to effectively remove strong vibration interference. Combined with local background estimation in the adaptive neighborhood and the separation purity coefficient for correction, residual noise can be suppressed and the time-domain waveform of the real discharge pulse can be preserved. Furthermore, it can adaptively distinguish between vibration and discharge signals with similar frequencies, reduce the false alarm rate of dielectric strength monitoring in medium and high voltage switchgear, and ensure the effectiveness of online monitoring under strong vibration environment.

[0083] In one embodiment, based on the partial discharge ultrasonic sequence, the dielectric properties of the target component are analyzed to generate a dielectric attenuation characteristic value representing the dielectric strength state of the target component, including:

[0084] Based on the partial discharge ultrasonic sequence, the correlation between the dielectric properties of the target component and the time-domain signal is analyzed to obtain the dielectric signal correlation degree, which represents the correlation between the partial discharge signal and the dielectric state of the target component. Specifically, this includes: identifying all partial discharge pulses from the partial discharge ultrasonic sequence, that is, finding all zero-crossing points in the partial discharge ultrasonic sequence where the amplitude changes from negative to positive or from positive to negative. The interval between two adjacent zero-crossing points is one half-cycle, and the interval between two consecutive half-cycles, that is, three consecutive zero-crossing points, constitutes a complete pulse. For each complete pulse, three parameters are extracted: pulse peak value, pulse width, and pulse energy. The pulse peak value is the maximum amplitude within the pulse, the pulse width is the time interval from the start zero-crossing point to the end zero-crossing point of the pulse, in seconds, and the pulse energy is the sum of the squares of the amplitudes of all sampling points within the pulse.

[0085] For each pulse, multiply the pulse peak value by the square of the pulse width, and then divide by the pulse energy. If the calculated result is ≥1, then it is 1; if the calculated result is ≤0, then it is 0. The adjusted calculated result is the dielectric sensitivity factor. The dielectric sensitivity factor reflects the distribution characteristics of pulse energy relative to the peak value and width, and is related to the dielectric loss of the insulating material.

[0086] Sort all the dielectric sensitivity factors of the pulses in ascending order of value. Take the dielectric sensitivity factor at the quarter position after sorting as the lower quartile value and the dielectric sensitivity factor at the three-quarter position after sorting as the upper quartile value. Calculate the difference between the upper and lower quartile values, i.e. the interquartile range. Divide all the dielectric sensitivity factors by the interquartile range and sort them in ascending order of value to obtain the distribution sequence. Calculate the ratio of the arithmetic mean to the geometric mean of the distribution sequence.

[0087] The number of pulses whose peak value exceeds the arithmetic mean of all pulse peak values ​​is counted. The proportion of this number to the total number of pulses is calculated. The ratio is multiplied by the proportion to obtain the dielectric signal correlation degree, which represents the correlation between the partial discharge signal and the dielectric state of the target device. The larger the value of the dielectric signal correlation degree, the stronger the correlation between the partial discharge signal and the dielectric state degradation.

[0088] Based on the dielectric signal correlation, the temporal decay law of the dielectric properties of the target component is fitted to obtain the dielectric decay characteristic value representing the dielectric strength state of the target component. Specifically, the process includes: dividing the partial discharge ultrasonic sequence into fixed time windows of the same length as the aliasing signal sequence; calculating the dielectric signal correlation of each window; and arranging the dielectric signal correlation of multiple windows in chronological order to form a time series of correlation.

[0089] Calculate the difference between two adjacent values ​​in the time series to obtain multiple first-order difference values. Divide the difference values ​​into two groups according to their positive and negative values: positive difference and negative difference. Calculate the arithmetic mean of all values ​​in the time series, and then subtract the mean from each value to obtain a zero-mean series. ;

[0090] In the formula, The dielectric attenuation characteristic value, representing the dielectric strength state of the target component, ranges from 0 to 1. This represents the cumulative sum and absolute value of all negative differences in the time series. This is the cumulative sum of all positive differences in the time series. This represents the number of times the product of two consecutive terms in a zero-mean sequence is negative. This represents the total length of the time series.

[0091] In one embodiment, a collaborative analysis is performed on the partial discharge ultrasonic signal, the partial discharge ultrasonic sequence, and the dielectric attenuation characteristic value to obtain the status identifier of the target object, including:

[0092] The dielectric reference coefficient representing the normal dielectric strength of the target component is calculated by analyzing the partial discharge ultrasonic signal and the partial discharge ultrasonic sequence. Specifically, this involves: taking the absolute value of the amplitude of all sampling points for each signal and sorting them in ascending order to obtain a sorted amplitude sequence; starting from the minimum amplitude, the amplitude is accumulated sequentially until the sum reaches one percent of the total amplitude of the signal, and the number of sampling points accumulated at this point is recorded; at the same time, the number of sampling points corresponding to the sum reaching 50% and 99% are recorded respectively.

[0093] Subtract the number of points corresponding to 1% from the number of points corresponding to 50% to obtain the width of the middle interval. Subtract the number of points corresponding to 50% from the number of points corresponding to 99% to obtain the width of the upper tail interval. Divide the width of the middle interval by the width of the upper tail interval to obtain the energy concentration of the signal.

[0094] Calculate the energy concentration of the two signals respectively to obtain the reference energy concentration and the current energy concentration. At the same time, calculate the maximum value of the absolute value of the amplitude of all sampling points in the two signals to obtain the reference maximum amplitude and the current maximum amplitude. Divide the current maximum amplitude by the reference maximum amplitude to obtain the amplitude expansion coefficient.

[0095] Divide the current energy concentration by the reference energy concentration, and then multiply by the amplitude expansion coefficient. If the calculation result is ≥1, then it is 1; if the calculation result is ≤0, then it is 0. The adjusted calculation result is the dielectric reference coefficient that represents the normal dielectric strength of the target component corresponding to the reference reference.

[0096] In one embodiment, the method of co-analyzing the partial discharge ultrasonic signal, the partial discharge ultrasonic sequence, and the dielectric attenuation characteristic value to obtain the status identifier of the target object further includes:

[0097] The dielectric attenuation characteristic value is compared with the dielectric reference coefficient to obtain the status identifier of the target object. Specifically, if the dielectric attenuation characteristic value is greater than or equal to the dielectric reference coefficient, it is determined that the dielectric strength of the insulating component is abnormal, and the status identifier of the target object is unstable; otherwise, the status identifier is stable.

[0098] By analyzing the pulse parameters of the partial discharge ultrasonic sequence, the correlation between the dielectric sensitivity factor and the dielectric signal is calculated, and the dielectric attenuation characteristic value is calculated. The dielectric attenuation characteristic value is combined with the dielectric reference coefficient for analysis to obtain the status identifier of the target object. This improves the accuracy and anti-interference capability of online monitoring of the dielectric strength of medium and high voltage switchgear insulation components, effectively avoids misjudgment of amplitude fluctuations caused by mechanical vibration interference, reduces the false alarm rate, and ensures the online monitoring effect of the target object.

[0099] In one embodiment, simultaneous testing was conducted on 10 groups of 10kV epoxy resin insulation components with different aging levels. The experimental results showed that the dielectric sensitivity factor and the dielectric loss value exhibited a strong positive correlation. When the dielectric loss increased, the dielectric sensitivity factor also increased synchronously, fully demonstrating that the dielectric sensitivity factor can effectively represent the dielectric loss state of the insulation component. The experimental data table is shown below:

[0100] As can be seen from the table above, as the aging of the insulation components deepens, the dielectric loss value, a core indicator of insulation aging, continues to rise from 0.002 to 0.04, and the dielectric sensitivity factor also rises synchronously from 0.12 to 0.98. The two show a synchronous growth trend and have a very high linear correlation.

[0101] Therefore, the dielectric sensitivity factor in this application has a direct physical positive correlation with dielectric loss, and can effectively represent dielectric loss.

[0102] In one embodiment, 10 groups of 10kV epoxy resin insulators with different aging levels were tested. The experimental results show that the constraint relationship between the dielectric attenuation characteristic value and the dielectric reference coefficient can effectively determine the abnormal state of the dielectric strength of the insulator. The experimental data comparison chart is shown below:

[0103] As shown in the table above, when the dielectric attenuation characteristic value is greater than or equal to the dielectric reference coefficient (0.5), the dielectric strength of all test samples decreases by more than 30%, which is completely consistent with the actual aging failure state. The judgment method has a high accuracy rate, which indicates that the dielectric attenuation characteristic value and the actual dielectric strength decrease ratio have a very strong positive correlation. The larger the characteristic value, the more serious the dielectric strength decrease, which can accurately reflect the degree of aging attenuation of the insulating component.

[0104] Experimental results fully demonstrate that the constraint relationship between the dielectric attenuation characteristic value and the dielectric reference coefficient proposed in this application for determining dielectric strength anomalies can effectively and accurately determine the abnormal dielectric strength state of insulating components. Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An online monitoring system for the operating status of medium and high voltage switchgear, characterized in that, include: The collaborative analysis unit is used to acquire the partial discharge signal of the target component and the vibration signal of the target object in real time, and to perform fusion calculation on the partial discharge signal and the vibration signal of the target object to obtain the aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise. The standard analysis unit is used to extract the frequency range of the partial discharge signal based on the aliasing signal vector, and to extract the frequency range of the vibration signal based on the vibration signal of the target object. The total width of the intersection of the frequency range of the partial discharge signal and the frequency range of the vibration signal is divided by the width of the frequency range of the partial discharge signal to obtain the vibration screening coefficient representing the matching degree between the partial discharge frequency band and the vibration interference. Only signal segments with instantaneous frequency values ​​within the vibration signal frequency range are retained. The absolute values ​​of the amplitudes of all sampling points within the signal segment are sorted according to the sampling time to obtain the vibration amplitude sequence. The sum of the median and the absolute median difference of the vibration amplitude sequence is calculated as the basic threshold. The ratio of the median to the absolute median difference of all instantaneous frequency values ​​within the vibration signal frequency range is calculated. This ratio is multiplied by the vibration screening coefficient to obtain the adjustment factor. The basic threshold is divided by the sum of the adjustment factor and the vibration screening coefficient to obtain the vibration interference threshold representing the standard for judging mechanical vibration noise. The distributed computing unit is used to analyze the aliased signal vector based on the vibration interference threshold, perform signal separation, and generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component. The dielectric attenuation unit is used to identify all partial discharge pulses from the partial discharge ultrasound sequence. For each pulse, the pulse peak value, pulse width, and pulse energy parameters are extracted. The pulse peak value is multiplied by the square of the pulse width and then divided by the pulse energy to obtain the dielectric sensitivity factor. Sort all the dielectric sensitivity factors of the pulses in ascending order of value, calculate the difference between the upper quartile and the lower quartile values ​​to obtain the interquartile range, divide all the dielectric sensitivity factors by the interquartile range and sort them in ascending order of value to obtain the distribution sequence, and calculate the ratio of the arithmetic mean to the geometric mean of the distribution sequence. The proportion of pulses whose peak value exceeds the arithmetic mean of all pulse peak values ​​is counted out of the total number of pulses. The ratio of the arithmetic mean to the geometric mean of the distribution sequence is multiplied by the proportion to obtain the dielectric signal correlation degree, which represents the correlation between the partial discharge signal and the dielectric state of the target device. Based on the correlation of dielectric signals, the time-series decay law of the dielectric properties of the target component is fitted to obtain the dielectric decay characteristic value representing the dielectric strength state of the target component. The status determination unit is used to acquire the partial discharge ultrasonic signal under normal operating conditions of the target component, and to perform collaborative analysis on the partial discharge ultrasonic signal, partial discharge ultrasonic sequence and dielectric attenuation characteristic value to obtain the status identifier of the target object.

2. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 1, characterized in that, The partial discharge signal and the vibration signal of the target object are fused to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise, including: Transmission delay analysis is performed on the preprocessed partial discharge signal and vibration signal to generate a synchronization calibration vector representing the correlation between the partial discharge of the target component and the vibration of the target object.

3. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 2, characterized in that, The partial discharge signal and the vibration signal of the target object are fused and calculated to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise. This also includes: Based on the synchronous calibration vector, the preprocessed partial discharge signal and vibration signal are normalized to generate a dielectric vibration amplitude sequence. Based on the dielectric vibration amplitude sequence, the fluctuation consistency between partial discharge and vibration interference is analyzed, and a correlation factor representing the dynamic correlation between the dielectric state of the target component and vibration interference is obtained.

4. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 3, characterized in that, The partial discharge signal and the vibration signal of the target object are fused and calculated to obtain an aliased signal vector representing the superposition of the partial discharge signal and the mechanical vibration interference noise. This also includes: Based on the correlation factor, the superposition characteristics of partial discharge signal and mechanical vibration interference noise are integrated to obtain an aliased signal vector representing the superposition characteristics of partial discharge signal and mechanical vibration interference noise.

5. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 4, characterized in that, Based on the vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge in the target component, including: Extract the absolute values ​​of the aliasing amplitudes of all sampling points from the aliasing signal vector to obtain the first sequence. Extract the absolute values ​​of the amplitudes of all sampling points from the vibration signal of the target object to obtain the second sequence. Find the sampling point times when the absolute values ​​of the first and second sequences are greater than the vibration interference threshold to obtain two sets of times. Count the lengths of the two sets of times to obtain the first count and the second count, respectively. Calculate the number of intersection points of the two sets of time points to obtain the count intersection, and then calculate the number of union points of the two sets of time points to obtain the count union. Divide the count intersection by the count union to obtain the overlap ratio, and then divide the absolute value of the difference between the first count and the second count by the maximum value of the first count and the second count to obtain the difference ratio. Multiply the overlap ratio by the difference ratio to obtain the discrimination coefficient representing the distinction between the partial discharge signal and the vibration interference signal. The median of all sampling points in the vibration amplitude sequence is used as the vibration reference value. The vibration reference value is multiplied by the discrimination coefficient to obtain the dynamic offset. The vibration interference threshold is added to the dynamic offset to obtain the separation boundary value. For each sampling point in the aliased signal vector, if the aliasing amplitude is less than or equal to the separation boundary value, the sampling point is directly classified as the separated partial discharge signal. If the aliasing amplitude is greater than the separation boundary value, the vibration amplitude of the corresponding point is checked to see if it is greater than the vibration reference value. If the vibration amplitude is greater than the vibration reference value, the product of the vibration amplitude and the square of the discrimination coefficient is subtracted from the aliasing amplitude of the point to obtain the aliasing amplitude after separation processing for that sampling point. If the vibration amplitude is less than or equal to the vibration reference value, the aliasing amplitude remains unchanged. All the processed aliasing amplitudes are arranged in chronological order to form the separated partial discharge signal sequence. The number of sampling points in the separated partial discharge signal sequence whose aliasing amplitude is still greater than the vibration interference threshold is counted as the residual points. Then, the total number of points in the original aliasing signal sequence whose amplitude is greater than the vibration interference threshold is counted. The residual points are divided by the total number of points to obtain the separation purity coefficient, which represents the purity of the two types of signals after separation.

6. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 5, characterized in that, Based on the vibration interference threshold, the aliased signal vector is analyzed and the signal is separated to generate a partial discharge ultrasonic sequence representing the time-domain distribution of the effective ultrasonic signal generated by partial discharge of the target component. This also includes: Based on the separation purity coefficient, the separated partial discharge signal is corrected to obtain a partial discharge ultrasonic sequence that represents the time-domain distribution of the effective ultrasonic signal generated by the partial discharge of the target component.

7. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 6, characterized in that, A synergistic analysis of partial discharge ultrasonic signals, partial discharge ultrasonic sequences, and dielectric attenuation characteristics yields the target object's status identifier, including: The dielectric reference coefficient, representing the reference reference corresponding to the normal dielectric strength of the target component, is obtained by calculating the partial discharge ultrasonic signal and the partial discharge ultrasonic sequence.

8. The online monitoring system for the operating status of medium and high voltage switchgear according to claim 7, characterized in that, A synergistic analysis of partial discharge ultrasonic signals, partial discharge ultrasonic sequences, and dielectric attenuation characteristics yields the state identifier of the target object, and also includes: The state identifier of the target object is obtained by comparing the dielectric attenuation characteristic value with the dielectric reference coefficient.

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