CN113899968A

CN113899968A - Voltage transformer monitoring method

Info

Publication number: CN113899968A
Application number: CN202111111942.3A
Authority: CN
Inventors: 张建; 张方荣; 尹娟
Original assignee: Gauss Electronics Technology Co ltd
Current assignee: Gauss Electronics Technology Co ltd
Priority date: 2021-09-23
Filing date: 2021-09-23
Publication date: 2022-01-07
Anticipated expiration: 2041-09-23
Also published as: CN113899968B

Abstract

The invention discloses a voltage transformer monitoring method, which comprises the following steps: s1, carrying out data acquisition and analysis on a tested mutual inductor, wherein the data acquisition and analysis are divided into the following two conditions: A. when the measured mutual inductor is used for collecting the grounding quantity, the metering error of the mutual inductor is independently calculated according to the secondary quantity and the grounding quantity, and the insulation state is analyzed; B. when the measured mutual inductor does not have the ground connection amount acquisition or the ground connection leakage amount acquisition fails and the data fluctuation amount is large, so that the error calculation of the individual mutual inductor can not be carried out on the data, a mode of joint analysis of a plurality of mutual inductors is adopted; s2, comprehensively evaluating the relevance between the metering error fluctuation and the insulation state: and synchronously evaluating the measurement and insulation states by adopting a neural network algorithm, and evaluating the reason of the measurement over-tolerance according to the insulation index. The invention is a voltage transformer monitoring method without collecting voltage and current signals of a high-voltage side, is compatible with an electromagnetic type voltage transformer and a capacitor voltage transformer, and solves a plurality of problems faced by the conventional voltage transformer metering error monitoring.

Description

Voltage transformer monitoring method

Technical Field

The invention relates to a transformer, in particular to a voltage transformer monitoring method.

Background

The mutual inductor is used as important power equipment and has the characteristics of large quantity, heavy maintenance task, influence on metering and protection due to equipment failure and the like. Early transformer monitoring was mainly insulation monitoring, partial secondary electrical parameter monitoring and primary and secondary combined monitoring means.

The primary and secondary combination is mainly realized by synchronously acquiring the current or voltage of the high-voltage side and synchronously comparing the current or voltage with the current or voltage of a secondary loop; however, the insulation is more sophisticated because of the need to contact a high voltage once, and the technology is only used for low-voltage transformers generally.

With the development of artificial intelligence technology and statistical computing technology, related researches based on secondary voltage analysis relative metering errors are developed in recent years, but the researches mainly stay in the aspect of more remarkable secondary voltage abnormity at present, and a mathematical model is not well established for the relationship between the secondary voltage and the errors; according to part of research results, secondary voltages of a plurality of mutual inductors are synchronously acquired and confidence intervals are analyzed, some data deviating from target confidence intervals can be found, but the method is limited by the number of samples, voltage abnormal fluctuation (such as switch-on of a switch, load adjustment, lightning waves, operation waves, secondary oscillation and various interference waveforms introduced by maintenance) existing in normal system operation is not well processed, the abnormal waves are not the characteristics of faults or defects of the mutual inductors, and misleading is easily formed on the existing statistical calculation method; in addition, in the statistical algorithm, the selection of the confidence interval does not form a calculation method related to the measured data; for the mechanism of the error overrun of the mutual inductor, due to the lack of synchronous insulation parameter analysis means, the timely excavation and analysis of the overrun reason are not carried out, and due to the accumulation and extension of faults, the fault phenomenon can only be found by only depending on the method of carrying out power failure and disassembly test on the mutual inductor after the overrun occurs, and the true source of the fault cannot be reasonably explained. There is thus a need for improvement of the above practical problems.

Disclosure of Invention

The invention aims to overcome the defects of the prior art, provides a voltage transformer monitoring method, does not need a voltage transformer monitoring method for collecting voltage and current signals at a high-voltage side, and solves the problems of the conventional voltage transformer metering error monitoring.

The purpose of the invention is realized by the following technical scheme: a voltage transformer monitoring method comprises the following steps:

s1, carrying out data acquisition and analysis on a tested mutual inductor, wherein the data acquisition and analysis are divided into the following two conditions:

A. when the measured mutual inductor is used for collecting the grounding quantity, the metering error of the mutual inductor is independently calculated according to the secondary quantity and the grounding quantity, and the insulation state is analyzed;

B. when the tested mutual inductor does not have the grounding quantity acquisition or the grounding quantity acquisition fails and the data fluctuation quantity is large, so that the error calculation of the individual mutual inductor can not be carried out on the data, a mode of joint analysis of a plurality of mutual inductors is adopted;

s2, comprehensively evaluating the relevance between the metering error fluctuation and the insulation state: and synchronously evaluating the measurement and insulation states by adopting a neural network algorithm, and evaluating the reason of the measurement over-tolerance according to the insulation index.

Further, the measured transformers in step S1 include electromagnetic voltage transformers and capacitive voltage transformers.

When the mutual inductor to be tested is provided with the grounding capacity acquisition, the acquisition and analysis mode is as follows:

the method comprises the following steps of firstly, collecting secondary quantity, grounding quantity and auxiliary quantity of a tested mutual inductor; the auxiliary quantity comprises temperature, humidity and vibration data;

if the mutual inductor to be tested is an electromagnetic voltage mutual inductor, at least one path of secondary voltage and one path of overall grounding current of the voltage mutual inductor are collected when the secondary quantity and the grounding quantity are collected;

if the mutual inductor is a capacitance voltage mutual inductor, at least one path of secondary voltage, one path of integral grounding leakage current and one path of low-voltage capacitance grounding current are collected when the secondary quantity and the grounding quantity are collected; or at least collecting one path of secondary voltage, one path of low-voltage capacitor grounding current and one path of step-down transformer primary grounding current;

and secondly, respectively calculating the error of the voltage transformer and evaluating the insulation state according to the acquired secondary quantity and the grounding quantity.

Further, when the voltage transformer to be measured is an electromagnetic voltage transformer, the acquisition and analysis method comprises the following steps:

(a) the method comprises the steps of collecting secondary voltage V2 and the waveform Ig of the integral grounding current of the mutual inductor at regular time, and calculating amplitude, phase and frequency spectrum; temperature, humidity, vibration data;

(b) calculating a metering instantaneous error: windowing is carried out on V2 and Ig waveform data, and wavelet or short-time Fourier transform STFT is adopted to calculate V2, DC components V2dc and Igdc of Ig and the ratio kdc of the DC components V2dc and the Igdc to V2 dc/Igdc; when the Igdc, V2dc is increased by more than 10% compared with the mean value data of the fault-free history or kdc is smaller than 90% of the mean value data of the fault-free history, kdc is recorded as an abnormal value, the circuit is considered to have an operation overvoltage or a lightning overvoltage or circuit resonance, therefore, the voltage V2 is not used as a basis for calculating errors, and the data of the collected V2 is abandoned; when the ratio V2/Ig of an effective value or a root mean square value V2 and the Ig is increased by more than 10 percent compared with a non-fault historical mean value, the secondary voltage of the voltage transformer is considered to be open-circuit, the voltage V2 is not used as a basis for metering error, collected data of V2 are abandoned, when Igdc, V2dc is lower than the historical mean value by 110 percent or the absolute quantity of the difference between kdc and the historical value is larger than the historical mean value by 95 percent, kdc is recorded as a normal value, and the phase difference between V2 and the Ig is calculated

The difference in the ratio of V2 and Ig × M, Vr0 ═ (V2 × Nr-Ig × M)/Ig × M ═ V2 × Nr/(Ig × M) -1 ═ kg × Nr/M-1,

dielectric loss

Nr is a rated transformation ratio or a transformation ratio value of a historical test, M is a reference insulation resistance value or a historical test value, and kg is V2/Ig; when the M value cannot be determined, Vr0 cannot be calculated, and the step (c) is entered, and the ratio difference and the insulation evaluation are completed by (c) + (d).

(c) Calculating the error offset of the measurement mean value:

at least acquiring kdc a plurality of time point secondary voltage V2N and grounding current Ign, N is 1 and 2 … N when the data is normal data, calculating kgn-V2N/Ign, wherein the voltage phase angle of V2 is marked as theta 2N, the phase angle of grounding current Ig is marked as theta gn,

calculating a normal distribution P of kgn (kg0) based on kg0 and δ kg with reference standard values V20, Ig0 amplitude ratio kg0 ═ V20/Ig0 as expected values μ and δ kg as a standard deviation of kgn;

based on V2n, the amplitude ratio of the Ign mean kgn0 ═ the average of V2avg/Igavg as expected value μ, δ kg is the standard deviation of kgn, and the normal distribution p (kgn) was calculated for kgn.

Respectively by reference values

The average values are taken as the expected values mu respectively,

standard deviation of (2)

Computing

Is normally distributed to obtain

Setting a confidence interval, calculating a difference offset delta P (kgn) -P (kg0) and recording the difference offset delta P as the difference offset; offset of angular difference

When the confidence interval can not be set, carrying out Fourier transformation on the amplitude or phase angle difference of N (N >8) secondary voltages V2N and the grounding current Ign to obtain frequency domain data, and calculating the proportion of the maximum absolute value of the frequency domain data to the absolute value of all data to be arithmetically summed, wherein the proportion corresponds to the proportion coefficient Sv2 and Sign corresponding to the secondary voltages and the grounding current, and the minimum value in [ Sv2 and Sign ] is taken as the confidence interval.

(d) Introducing a specific difference and an angular difference absolute quantity, and calculating the specific difference angular difference absolute quantity of the current running state;

and D1, recording ratio difference and angle difference data of the power failure state check, if the power failure data are missing, replacing the power failure data mean value of the ratio difference and the angle difference of other voltage transformers with the same specification in the same operating substation environment, recording the obtained power failure check ratio difference and angle difference data or the calculated ratio difference and angle difference data as Vr0 and delta 0, and then calculating the ratio difference V2 of the current measured voltage transformer to be Vr0+ delta P and the angle difference delta to be delta 0+ delta. Wherein Δ P, Δ δ is the data obtained in step (c);

d2: when the specific difference and the angular difference obtained by D1 are in the standard value range, and the vibration data continuously increase or the vibration amplitude is larger than the historical normal value, the external bolt of the voltage transformer is considered to be loose; when the specific difference and the angular difference obtained by D1 exceed the standard value range, the vibration data continuously increase or the vibration amplitude is larger than the historical normal value, and the voltage transformer is considered to have overvoltage, discharge or insulation abnormality;

(e) considering the environmental influence, the historical data of the specific difference, the angular difference, the temperature, the humidity and the vibration of the voltage transformer are analyzed at regular time, and the normal distribution is calculated

And drawing a normal distribution curve based on the ratio difference, the angle difference, the temperature, the humidity and the vibration.

When the specific difference and the angular difference exceed the limits, the temperature and humidity data are in the historical mean value or the 95% confidence interval, and the metering error of the voltage transformer is considered to be out of limits due to internal reasons; when the specific difference and the angular difference exceed the limit, and at least one of temperature, humidity and vibration data exceeds the historical mean value or the 95% confidence interval, the voltage transformer is considered to have the metering error which is influenced by the environment and exceeds the limit or the error is caused by external insulation or internal insulation.

Further, when the voltage transformer to be measured is a capacitor voltage transformer, the acquisition and analysis method comprises the following steps:

(a) the method comprises the steps of safely collecting waveforms of secondary voltage V2, low-voltage capacitor grounding current IC2, primary side grounding current IP1 of an excitation transformer and integral grounding current Ig of a transformer at fixed time, and calculating amplitudes, phases and frequency spectrums of V2, IC2, IP1 and Ig; temperature, humidity, vibration data;

(b) judging whether a fault exists;

b1, calculating the voltage, the specific difference and the angular difference of the high-voltage capacitor end of the capacitor transformer;

firstly, the current magnitude of the high-voltage capacitor is calculated, wherein the current magnitude is IC 1-Ig, or when Ig collection fails, fails or has no data, the current magnitude is calculated through IC2 and IP1, and the current magnitude is IC 1-IC 2+ IP1, namely, the current magnitude IC1 and the phase of the high-voltage capacitor current are obtained through vector addition

Secondly, calculating the amplitudes and phases of capacitor terminal voltages VC1 and VC2, wherein the calculation formula is as follows:

VC is IC × Zc, Zc is 1/(2 × 3.141592 × f × C), f is a calculated frequency value, C is a high-voltage capacitor C1, and a low-voltage capacitor C2 is a nameplate nominal value or history check data; the IC is a low-voltage capacitor IC2, and the high-voltage capacitor current IC1 ═ Ig or IC1 ═ IC2+ IP 1.

Zc1＝1/(2*3.141592*f×C1)，Zc2＝1/(2*3.141592*f×C2)。

VC1＝IC1×Zc1,VC2＝IC2×Zc2,

The line voltage is then calculated: VLine ═ VC1+ VC 2;

the phase angle of the line voltage Vline is noted

And finally calculating the ratio difference: vr (Nr V2-VLINE)/VLINE

The angular difference is as follows:

is the phase angle of the secondary voltage; nr is the rated transformation ratio or the transformation ratio value of the historical test.

b2, judging whether the partial discharge phenomenon exists according to the harmonic content:

when harmonic parameters appear in the frequency spectrums of the low-voltage capacitor grounding current IC2 in a plurality of acquisition time periods and the harmonic content is more than 2% of the total frequency spectrum, or the harmonic parameters appear in the Ig frequency spectrums and the harmonic content is more than 3% of the total frequency spectrum, judging that the measured capacitor type voltage transformer has a partial discharge phenomenon; or when the harmonic parameters appear in the Ig frequency spectrum, the harmonic content is more than 3% of the total frequency spectrum, and the IP1 harmonic content is more than the IC2 harmonic content, judging that the voltage-reducing transformer has a partial discharge phenomenon; otherwise go to b 3;

b 3: based on whether there is a fault in the phase angle difference:

calculating phase angle differences delta vc of V2, IC2, V2 and IP 1; phase angle difference δ cp for IC2, IP 1; if the IC2 is larger than 10% of the rated value and |90- δ vc | is smaller than the threshold value, the capacity reduction of the high-voltage capacitor C1 is indicated; if the IP1 is more than the rated value by 20 percent and the absolute value of 90-delta cp is less than the threshold value, the failure of the primary winding of the step-down transformer or the smoothing compensation reactor or the lightning arrester or the high-voltage capacitor C1 is indicated; when IP1 is larger than the rated value by 20% and all |90- δ cp | are larger than the threshold value, the step-down transformer is indicated to be in failure;

b 4: estimating capacitance

Carrying out time domain to frequency domain conversion on the waveform of a transformer secondary voltage V2, or a low-voltage capacitor grounding current IC2, or a voltage reduction transformer primary side grounding current IP1 or a transformer integral grounding current Ig, searching whether a stable non-power frequency signal fr exists in the range of 20Hz to 150Hz on frequency domain data, if the fr exists, calculating the deviation delta f of the fr and a power frequency signal f0, and taking the power frequency signal f0 as a frequency value corresponding to the maximum gain on 50Hz or 60Hz or the frequency domain data:

when the IC2 deviates from the standard value by more than 5 percent and the Ig or V2 deviates from the standard value by less than 2 percent, the capacitor C2 is considered to have deviation; when IC2 is deviating, C2 is reduced, and deltaC is less than 0; when IC2 is negatively deviated, C2 is increased, and deltaC is larger than 0; Δ C ═ 0, Fr ═ f 0;

first, bringing the standard value f0, C2 nominal capacitance,

calculating the L value:

then the L value, the C2 value, and the Fr value are substituted for f0 and are substituted into the following equation,

c2 in the equation directly replaces C, so that only Δ C needs to be calculated to obtain the latest value of C2 ═ C2+ Δ C;

when the IC2 is deviating more than 5% from the standard value and the Ig or V2 deviates more than 2% from the standard value, the reduction of the high-voltage capacitor C1 is considered to cause the reduction of the transformation ratio N of the voltage transformer, which causes the output voltage to rise and the IC2 to rise; the high-voltage capacitor and the low-voltage capacitor are not supposed to be failed at the same time, so that the condition belongs to the condition that the high-voltage capacitor is failed;

the same method is used to calculate C1 next.

Firstly, a standard value f0 is brought, C is the nominal capacitance of the high-voltage capacitor C1,

calculate L ═ L value.

Then the values of L', C1, Fr expected f0 are put into the following equations,

calculate Δ C'. The latest value of the high-voltage capacitor C1 'is C1+ delta C';

the above standard values refer to design manufacturing values or average values of historical test data or fault-free historical operating data.

It can be seen that the key point of the above algorithm is the image frequency fr, and the capacitance variation can be calculated according to the equation only when the image frequency is present, i.e., fr ≠ f 0. When no mirror frequency exists, the capacitance is considered to be unchanged, and the estimated capacitance value is the capacitance of the original known test.

Of course, the above algorithm is premised on that C1 and C2 do not have simultaneous magnitude shifts, where the calculated L inductance value is also an equivalent value to C1 and C2, and the calculated equivalent inductance values are different when calculating C1 and C2. Obviously, if the capacitance is determined or assumed to be constant and an accurate capacitance is obtained, the equivalent equation can be substituted into f0, C is substituted to calculate the fault-free inductance L, and fr and C are substituted to calculate the offset of the equivalent inductance. Since the equivalent inductance comes mainly from the electromagnetic unit and the compensation reactor, the deviation of the equivalent inductance can be used to find defects or faults of the electromagnetic unit and the compensation reactor.

When the measured mutual inductor does not have the ground connection amount acquisition or the ground connection leakage amount acquisition is failed and the data fluctuation amount greatly causes data which can not be subjected to individual mutual inductor error calculation, a plurality of mutual inductors with the same voltage level are adopted for joint analysis, namely, the probability distribution calculation errors of the secondary voltages of the plurality of voltage mutual inductors are specifically included:

(1) setting transformer signals acquired synchronously as Ak, wherein k is 1,2 … N, k is data of a plurality of transformers acquired at the same time point, and N is the maximum number of acquisition time points; ak is the phase and amplitude of the secondary voltage of the electromagnetic voltage transformer or the secondary voltage of the capacitor voltage transformer and the C2 current waveform signal; or the phases and amplitudes of secondary voltage and grounding current Ig waveform signals of the capacitor voltage transformer;

(2) performing quantization processing on Ak to obtain Bk, wherein Bk is Ak/Akmax, and Akmax is the maximum numerical value in Ak, so that the quantized range of Bk is 0-1, then performing windowing processing on Bk by applying a window function, and performing time domain-frequency domain conversion to obtain frequency domain characteristic data Ck; obtaining Ck by taking the modulus of Ck, calculating the sum of modulus

Finding the maximum value | Ckmax | in | Ck |, and calculating the ratio p | Ckmax |/SAU when p is>When λ, the overall data is considered to be in a good state, and when p<Lambda considers that the data volatility is increased, abnormal data exist, and p is used as a confidence interval; the lambda value interval is 0.8000-0.9999, and the default value is 0.9600.

The Bk is subjected to windowing treatment by applying a window function, and any one of a Hamming window, a Hanning window, a Gaussian window, a BlackHarries window, a Keseph window, a flat top window, a rectangular window and a triangular window is adopted.

(3) The Ak normal distribution is then calculated.

(4) Calculating the data of Ak corresponding to the confidence interval p and the Ak average value as error offset; the data obtained include:

electromagnetic voltage transformer: the amplitude offset and the angle offset of the secondary voltage V2 are denoted by PT [. DELTA.. epsilon.1,. DELTA.. epsilon.2 ], and Δ epsilon.1 is regarded as the specific difference offset and Δ epsilon.2 is the angle difference offset.

A capacitor voltage transformer: the amplitude offset of the secondary voltage V2 and the amplitude offset of IC2 or Ig are marked as [. DELTA.. epsilon.1,. DELTA.. epsilon.2 ]; the V2 angular offset, IC2 or Ig angular offset [. DELTA.. epsilon.3,. DELTA.. epsilon.4 ], and then the specific and angular difference offsets are calculated:

the offset of the ratio difference: delta epsilon 1-Delta epsilon 2 (direct subtraction arithmetic difference)

Angular difference offset: delta epsilon 3-Delta epsilon 4 (direct subtraction arithmetic difference)

The idea here to calculate the offset of the ratio difference and the angular difference is that the synchronicity of the secondary voltage and the ground quantity in response to the primary voltage change deviates, which synchronicity deviation will be reflected at least in the ratio difference or the angular difference.

And when the calculated specific difference and angular difference offset exceed the specified values of the precision grade of the voltage transformer, the error is regarded as exceeding the limit.

Further, the step S2 includes:

A. neural network frame for establishing following parameters

A1, when the device to be tested is a universal voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Igpeak, Igrms,

frg,Mfg,N

the output quantity is as follows: verr, delta err, Z, tan delta, PD, YN

A2. When the tested device is a capacitor voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Ic2, Ip1,

Igpeak,Igrms,frg,Mfg,C10,C20,N

the output quantity is as follows: verr, delta err, Z, C2, C1, tan delta, PD, YN

Wherein, V2peak is the secondary voltage peak; v2rms is the effective value of the secondary voltage; v2dc ═ secondary voltage dc voltage; igpeak is the voltage transformer grounding current peak value, Igrms is the voltage transformer grounding current effective value, frg is the mirror frequency of current Ig, and is the non-system power frequency signal of the frequency of the second large gain with the frequency in the range of 20-150 Hz; the Mfg is the ratio of the sum of the gains of other frequencies larger than the power frequency signal to the sum of all the gains of the frequencies, so that 0 ═ Mfg ═ 1;

ic2 is the effective value or root mean square value or peak value of the current of the low-voltage capacitor of the capacitor voltage transformer;

ip1 is the primary grounding current of the electromagnetic transformer of the capacitor voltage transformer;

is the phase angle of the secondary voltage V2,

the phase angle of the low voltage capacitor current IC2,

is the ground current Ig phase angle;

c10 is a nameplate or a high-voltage capacitance value of a historical test;

c20 is a low voltage capacitance value for nameplate or historical testing.

Low-voltage capacitance value output by the C2 neural network;

the high-voltage capacitance value output by the C1 neural network;

whether YN has insulation abnormality or integral state abnormality or not is 1, and whether YN has 0 value or not is judged;

PD partial discharge capacity in pc or mV or dB;

B. training the samples by adopting a neural network algorithm, establishing training sample frames with different input quantities and output quantities under the condition of known output quantity, wherein the number of the training samples is not less than 3; if the input quantity is partially missing, recording as 0 value or taking other uniform fixed numbers, if the known output quantity is partially missing, recording as 0 value or taking other uniform fixed numbers;

C. b, according to the input quantity monitored on line, calling a neural network algorithm trained in the step B to calculate an output quantity, observing measurement error data and insulation indexes of discharge quantity and capacitance according to the output quantity, comparing the synchronism of error overrun and insulation abnormal parameters, and explaining the reason of error overrun;

the basic classifications are as follows:

(c1) when the metering error and the dielectric loss simultaneously exceed the standard and YN is equal to 1, judging the metering over-tolerance caused by the aging of an insulating medium, the wetting of the medium or the sealing defect;

(c2) when the metering error and the partial discharge capacity PD simultaneously exceed the standard and YN is equal to 0, judging that the error over-tolerance is caused by insulation discharge or temperature rise of discharge;

(c3) when the metering error and the partial discharge capacity PD exceed the standard simultaneously and YN is equal to 1, judging that the error over-tolerance is caused by heat loss and aging caused by insulation discharge or accumulated temperature rise of discharge;

(c4) when the insulation resistance Z is normal, the metering error is out of tolerance, but PD exceeds the standard, YN is 0, and the metering error is out of tolerance caused by discharging or vibration clearance caused by dirt on the surface of the mutual inductor or poor contact of the wiring terminals of the high-voltage layer and the low-voltage layer of the mutual inductor.

The invention has the beneficial effects that: (1) the problem of algorithm defects caused by single distribution monitoring of the synchronous data of the secondary voltages of a plurality of mutual inductors is solved; because the samples lack standard values, the confidence interval can be changed when any voltage transformer fails, and as the number of the samples increases, even if the individual samples are changed obviously, the failed equipment cannot be captured sensitively in the total samples, and only the difference quantity of the overall confidence and probability distribution can be reflected; (the analysis method can be attributed to a horizontal statistical algorithm)

(2) The problem of longitudinal data analysis of a single device at multiple times is solved;

(3) the problem of confidence interval calculation error bigger due to insufficient samples of the monitored mutual inductor is solved.

(4) The problem of value taking of the optimal confidence interval is solved;

(5) the problem of the timing risk that the secondary quantity of a plurality of mutual inductors excessively depends on a GPS system is solved, and once the GPS system fails, such as interference, shielding, satellite signal failure and failure of a GPS module of a monitoring terminal, or under the condition that GPS synchronous monitoring is not configured, error data can still be obtained through the algorithm of the patent.

(6) The problem of correlation analysis of errors and insulation is solved; and a timely and reasonable explanation is provided for the reason of the error out-of-tolerance. And the method can be used for continuous online monitoring, short-time online monitoring or field live-line inspection of portable devices, laboratory simulation error testing, simulation, training systems and the like of the mutual inductor.

Drawings

FIG. 1 is a flow chart of the method of the present invention.

Detailed Description

The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.

As shown in fig. 1, a voltage transformer monitoring method includes the following steps:

The tested transformer in the step S1 includes an electromagnetic voltage transformer and a capacitor voltage transformer.

(b) calculating a metering instantaneous error: windowing is carried out on V2 and Ig waveform data, and wavelet or short-time Fourier transform STFT is adopted to calculate V2, DC components V2dc and Igdc of Ig and the ratio kdc of the DC components V2dc and the Igdc to V2 dc/Igdc; when the Igdc, V2dc is increased by more than 10% compared with the mean value data of the fault-free history or kdc is smaller than 90% compared with the mean value data of the fault-free history, kdc is marked as an abnormal value, the circuit is considered to have an operation overvoltage or a lightning overvoltage or a circuit resonance, and therefore the voltage V2 is not taken as a meterCalculating the basis of the error, and discarding the data of the collected V2; when the ratio V2/Ig of an effective value or a root mean square value V2 and the Ig is increased by more than 10 percent compared with a non-fault historical mean value, the secondary voltage of the voltage transformer is considered to be open-circuit, the voltage V2 is not used as a basis for metering error, collected data of V2 are abandoned, when Igdc, V2dc is lower than the historical mean value by 110 percent or the absolute quantity of the difference between kdc and the historical value is larger than the historical mean value by 95 percent, kdc is recorded as a normal value, and the phase difference between V2 and the Ig is calculated

The ratio difference, angle difference and dielectric loss of V2 and Ig xM are calculated as follows:

the difference Vr0 (V2 Nr-Ig M)/(Ig M) V2 Nr/(Ig M) -1 kg Nr/M-1

Angular difference

Dielectric loss

Nr is a rated transformation ratio or a transformation ratio value of a historical test, M is a reference insulation resistance value or a historical test value, and kg is V2/Ig;

in the embodiment of the present application, the CVT is measured with an accuracy of 0.2, a voltage level of 220kV, where M is 11Gohm, V2 is 58.11V, Nr is 3666.7,

Ig＝19.3mA。

the specific difference (58.11 × 3666.7-0.0193 × 11000000)/(0.0193 × 11000000) ═ 0.00364 ═ 0.364%.

Dielectric loss

From the error data analysis, the voltage transformer was greater than 0.2%, and was out of tolerance.

(c) Calculating the error offset of the measurement mean value:

at least when normal data is obtained kdcAt each time point, the secondary voltage V2N, the ground current Ign, N is 1,2 … N, and kgn is V2N/Ign, the voltage phase angle of V2 is denoted as θ 2N, the phase angle of the ground current Ig is denoted as θ gn,

Respectively by reference values

The average value is the desired value mu,

standard deviation of (2)

Calculating corresponding normal distribution to obtain

When the confidence interval can not be set, carrying out Fourier transformation on the amplitude or phase angle difference of N (N >8) secondary voltages V2N and the grounding current Ign to obtain frequency domain data, calculating the proportion of the maximum absolute value of the frequency domain data to the sum of all absolute values of the data, obtaining the ratio coefficients Sv2 and Sign corresponding to the secondary voltages and the grounding current, and taking the minimum value in [ Sv2 and Sign ] as the confidence interval.

The normal distribution algorithm is as follows

The above equation: y represents V2, Ig, P (y) is probability density equation, P (a < y < b) is probability distribution function, mu is expected value of V20 and Ig0 calculated corresponding to P0 or V2a and Iga calculated corresponding to Pa, mean value or set standard value is taken, delta is V2n and standard deviation of Ign, a and b are amplitude and phase of V2n and Ign or ratio V2n/Ign of corresponding confidence interval to be calculated respectively;

the confidence interval is set to 95%, and Δ P ═ P (kgn) -P (kg0) ═ 0.00035 (no units);

unit is divided into

If it is not determined whether 95% is the confidence interval of the best evaluation, a fourier transform method may be adopted, where V2N is collected, the number N of Ign is 64, the fourier transform is performed to obtain the gain in the frequency domain, the maximum value V2N, and the SUM of all arithmetic gains is denoted as SUM (V2N), and V2N/SUM (V2N) is 0.966, the same method is applied to the case where the arithmetic SUM value ratio of the maximum value after the Ign fourier transform and the total gain is 0.959, and the minimum value in [0.066,0.959] is 0.959-95.9%, which is the preferred confidence interval.

The reason for selecting the minimum value here is to sufficiently consider the boundary effect, and to consider the maximum transformation threshold as the confidence interval, the sensitivity of the diagnostic error offset can be further improved.

(e) repeating the above process for multiple voltage transformers, periodically analyzing specific difference, angular difference, temperature, humidity and vibration data of multiple voltage transformers with the same specification, and calculating normal distribution

And (5) drawing a probability curve, a specific difference, an angular difference, a temperature curve and a humidity curve based on time. When the ratio difference and the angle difference do not exceed the limit, the equal time periods respectively correspond to probability distribution functions Pv calculated by the ratio difference and the angle difference, and the deviation delta S of the P delta is Pv-P delta;

when the polarity positive and negative changes occur in a certain time period, the arithmetic mean value is taken as delta Savg;

when the specific difference and the angular difference exceed the limits, the temperature and humidity curves corresponding to the time points are in the historical mean value or the 95% confidence interval, and the metering error of the voltage transformer is considered to be out of limits; when the specific difference and the angular difference exceed the limit, and at least one of the temperature, the humidity and the vibration data of the corresponding time point exceeds the historical mean value or the 95% confidence interval, the voltage transformer is considered to have the metering error limit exceeding and the insulation abnormality. When the specific difference and the angular difference exceed the limit, and the absolute value of the function value deviation Delta Sy-Delta Savg of the probability distribution of the specific difference and the angular difference is more than 0.1 and the kdc is normal, the potential insulation hazard or the insulation fault is considered to occur; in the examples of the present application

Collecting 100 times of data in a time period 1, calculating a ratio difference curve and an angle difference curve, and calculating a ratio deviation distribution function value Pv which is 0.9829 and an angle difference distribution function value Pdelta which is 0.9779; Δ S is 0.005.

Setting the temperature and the humidity to be in 95% confidence intervals, wherein the specific difference and the angular difference are not out of limit;

if at least one of the ratio difference or the angle difference exceeds the limit and the temperature and the humidity are in a 95% interval, the metering error of the voltage transformer is considered to exceed the limit; when the specific difference and the angular difference exceed at least one of the limits, but the temperature and the humidity are also outside the 95% confidence interval, the significance of the specific difference and the angular difference is not large, and the end point is to analyze the insulation condition.

(b) judging whether a fault exists;

Zc1＝1/(2*3.141592*f×C1)，Zc2＝1/(2*3.141592*f×C2)。

VC1＝IC1×Zc1,VC2＝IC2×Zc2,

The line voltage is then calculated: VLine ═ VC1+ VC 2;

the phase angle of the line voltage Vline is noted

And finally calculating the ratio difference: vr (Nr V2-VLINE)/VLINE

The angular difference is as follows:

b 3: based on whether there is a fault in the phase angle difference:

calculating phase angle differences delta vc of V2, IC2, V2 and IP 1; phase angle difference δ cp for IC2, IP 1; if the IC2 is larger than 10% of the rated value and |90- δ vc | is smaller than the threshold value, the capacity reduction of the high-voltage capacitor C1 is indicated; if the IP1 is more than the rated value by 20 percent and the absolute value of 90-delta cp is less than the threshold value, the failure of the primary winding of the step-down transformer or the smoothing compensation reactor or the lightning arrester or the high-voltage capacitor C1 is indicated; when the IP1 is larger than the rated value by 20 percent and the delta voltage is larger than the threshold value, indicating that the step-down transformer has faults;

b 4: estimating capacitance

first, bringing the standard value f0, C2 nominal capacitance,

calculating the L value:

then the values of L, C2 and Fr are substituted into the following equation,

calculating deltaC, wherein the latest value of C2' is C2+ deltaC;

the value of L' is calculated.

Then the values of L', C1 and Fr are substituted into the following equation,

(1) setting transformer signals acquired synchronously as Ak, wherein k is 1,2 … N, k is data of a plurality of transformers acquired at the same time point, and N is the maximum number of acquisition time points; ak is the phase and amplitude of the secondary voltage of the electromagnetic voltage transformer or the secondary voltage of the capacitor voltage transformer and the C2 current waveform signal;

Finding the maximum value | Ckmax | in | Ck |, and calculating the ratio p | Ckmax |/SAU when p is>When λ is satisfied, the overall data is considered to be goodState when p is<Lambda considers that the data volatility is increased, abnormal data exist, and p is used as a confidence interval; the lambda value interval is 0.8000-0.9999, and the default value is 0.9600.

(3) The Ak normal distribution is then calculated.

A capacitor voltage transformer: the amplitude offset of the secondary voltage V2 and the amplitude offset of the IC2 are recorded as [. DELTA.. epsilon.1,. DELTA.. epsilon.2 ]; v2 angular offset, IC2 angular offset [. DELTA.. epsilon.3,. DELTA.. epsilon.4 ], and then calculate the specific difference and angular difference offset:

the offset of the ratio difference: delta epsilon 1-Delta epsilon 2

Angular difference offset: delta epsilon 3-Delta epsilon 4

Further, the step S2 includes:

A. neural network frame for establishing following parameters

A1, when the device to be tested is a universal voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Igpeak, Igrms,

frg,Mfg,N

the output quantity is as follows: verr, delta err, Z, tan delta, PD, YN

A2. When the tested device is a capacitor voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Ic2, Ip1,

Igpeak,Igrms,frg,Mfg,C10,C20,N

is the phase angle of the secondary voltage V2,

the phase angle of the low voltage capacitor current IC2,

is the ground current Ig phase angle;

c10 is a nameplate or a high-voltage capacitance value of a historical test;

c20 is a low voltage capacitance value for nameplate or historical testing.

Low-voltage capacitance value output by the C2 neural network;

the high-voltage capacitance value output by the C1 neural network;

PD partial discharge capacity in pc or mV or dB;

the basic classifications are as follows:

Further, a window function is applied to the Bk to perform windowing treatment, and any one of a Hamming window, a Hanning window, a Gaussian window, a Blackman window, a Black-Harries window, a Keseph window, a flat top window, a rectangular window and a triangular window is adopted.

In the embodiment of the application, the neural network algorithm is used as an artificial intelligence processing technology similar to the black box theory, the application is more and more extensive, and the key point is not in the specific algorithm step for explaining the conclusion, but in reasonably building the training sample and constructing the input quantity and the output quantity. The input quantity refers in this embodiment to a parameter that is known or can be obtained by measurement, and the output quantity is a target quantity, i.e., a desired parameter that needs to be inferred by measurement.

And constructing a physical electrical model of the tested equipment, wherein the output quantity is calculated and has an electrical physical relation with the input quantity.

Aiming at a 110kV PT type voltage transformer, a built neural network input and output framework is established as follows:

A1. when the tested device is a general voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Igpeak, Igrms,

frg,Mfg,N

the output quantity is as follows: verr, delta err, Z, tan delta, PD, YN

Setting the unit of three parameters of input quantity V2peak, V2rms and V2dc to be volt, Igpeak and Igrms to be ampere, frg unit Hz and Mfg as percentage;

output Verr unit percent, δ err unit minutes, Z unit G ohms, tan δ unit percent, PD unit picolibrary, YN is 0 or 1 binary number.

And (4) setting the training samples as the front 4 rows of the following table, training by adopting a backward neural network algorithm, and setting the fifth row as prediction data based on the front four groups of data samples.

From the predicted data, Verr is 0.192, δ err is 31, Z is 49.5G, tan δ is 0.018, PD is 235pc, and YN is 1. The specific difference is close to the required value of 0.2%, the angular difference is also serious and large, and the dielectric loss and the partial discharge are both high, so that the insulation discharge problem of the tested transformer obtained by the YN column exists.

When the voltage transformer is a capacitor voltage transformer, the sample input and output structure is

The input quantity is: v2peak, V2rms, V2dc, Ic2, Ip1,

Igpeak,Igrms,frg,Mfg,C10,C20,N

Compared with the electromagnetic transformer, the training sample needs to increase the nominal values of C1 and C2, the actually measured C2 current value, the phase and the like, the training method and the prediction method are the same as the electromagnetic transformer calculation method, and repeated description is omitted here.

In the embodiment of the application, the following monitoring module can be set up according to the monitoring method of the application, and the monitoring module is composed of a processor, an acquisition module (analog-to-digital converter), a current sampling module, a voltage sampling module, a memory and a communication module.

The acquisition module only needs to acquire voltage and current values, and when the acquisition module is applied to an electromagnetic voltage transformer and a capacitor voltage transformer, the secondary voltage specification is the same 60V or 100V specification, so that a voltage acquisition channel can be completely shared.

The current channel is mainly used for collecting a ground current Ig, IC2, wherein the ground current Ig is also common to electromagnetic voltage transformers and capacitor voltage transformers.

Except for the hardware which only distinguishes the electromagnetic voltage transformer from the capacitor voltage transformer, the hardware also comprises: the capacitor voltage transformer is added with a current collection of a low-voltage capacitor C2 and a primary grounding current Ip1 of an excitation transformer.

Of course, the architecture can be further simplified, in the neural network architecture, the fluctuation performance of Ip1 explains whether a fault or an out-of-tolerance is caused by an excitation unit, but since Ip1+ Ic2 is Ig, if the fault occurrence part does not need to be further determined or the cost is saved, Ip1 does not need to be monitored. This is achieved only by IC2 and Ig.

Therefore, compared with an electromagnetic voltage transformer, the capacitive voltage transformer only increases a current channel, can adopt the same hardware architecture design, and particularly can flexibly select and match the current channel when being applied to monitoring a plurality of sets of transformers, or directly adopts a hardware scheme of the capacitive voltage transformer to be compatible with a scheme of the electromagnetic voltage transformer.

This patent hardware function still compromise temperature, humidity, vibration etc. to the evaluation environment has played fine reference effect to the influence of error and insulating parameter.

A professional can quickly build hardware and realize related algorithms according to the patent specification.

The intelligent voltage transformer electrified error testing device can be widely applied to portable equipment, online monitoring equipment, other online monitoring functional modules and the like for electrified error testing and electrified insulation performance evaluation of voltage transformers.

Of course, the purpose of the hardware architecture described in this embodiment is not limited to this, and it is within the scope of this patent to interpret the isolation and error of the transformer or to make equivalent transformations or conceptual substitutions on the structure and analysis method.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A voltage transformer monitoring method is characterized in that: the method comprises the following steps:

2. The voltage transformer monitoring method according to claim 1, wherein: the tested transformer in the step S1 includes an electromagnetic voltage transformer and a capacitor voltage transformer.

3. The voltage transformer monitoring method according to claim 1, wherein: when the mutual inductor to be tested is provided with the grounding capacity acquisition, the acquisition and analysis mode is as follows:

4. The voltage transformer monitoring method according to claim 3, wherein: when the measured voltage transformer is an electromagnetic voltage transformer, the acquisition and analysis method comprises the following steps:

(b) calculating a metering instantaneous error: windowing is carried out on V2 and Ig waveform data, and wavelet or short-time Fourier transform STFT is adopted to calculate V2, DC components V2dc and Igdc of Ig and the ratio kdc of the DC components V2dc and the Igdc to V2 dc/Igdc; when the Igdc, V2dc is increased by more than 10% compared with the mean value data of the fault-free history or kdc is smaller than 90% compared with the mean value data of the fault-free history, kdc is marked as an abnormal value, the circuit is considered to have an operation overvoltage or a lightning overvoltage or circuit resonance, and therefore the voltage V2 is not used as a calculation errorPoor basis, abandon the data of the collected V2; when the ratio V2/Ig of an effective value or a root mean square value V2 and the Ig is increased by more than 10 percent compared with a non-fault historical mean value, the secondary voltage of the voltage transformer is considered to be open-circuit, the voltage V2 is not used as a basis for metering error, collected data of V2 are abandoned, when Igdc, V2dc is lower than the historical mean value by 110 percent or the absolute quantity of the difference between kdc and the historical value is larger than the historical mean value by 95 percent, kdc is recorded as a normal value, and the phase difference between V2 and the Ig is calculated

Ratio difference, angular difference, dielectric loss of V2 and Ig × M:

the difference Vr0 (V2 Nr-Ig M)/(Ig M) V2 Nr/(Ig M) -1 kg Nr/M-1

Angular difference

Dielectric loss

when M cannot be determined, completing error calculation through steps (c) + (d);

(c) calculating the error offset of the measurement mean value:

when at least kdc is normal data, a plurality of time points of secondary voltage V2N, grounding current Ign, N is 1,2 … N, kgn is V2N/Ign, voltage phase angle of V2 is marked as theta 2N, phase angle of grounding current Ig is marked as theta gn, calculation is carried out

N1, 2 … N, with reference standard value V20, Ig0 amplitude ratio kg 0V 20/Ig0 as expected value μ, δ kg as standard deviation of kgn, normal distribution P (kg0) of kgn is calculated based on kg 0;

based on V2n, the amplitude ratio of the Ign mean kgn ═ the average of V2avg/Igavg as expected value μ, δ kg is the standard deviation of kgn, and the normal distribution p (kgn) was calculated based on kgn.

Respectively by reference values

The average values are taken as the expected values mu respectively,

standard deviation of (2)

Computing

Is normally distributed to obtain

When a confidence interval cannot be set, carrying out Fourier transformation on the amplitude or phase angle difference of N (N >8) secondary voltages V2N and the grounding current Ign to obtain frequency domain data, calculating the proportion of the frequency domain data to the maximum absolute value of the absolute value of all data after absolute value taking, and then carrying out arithmetic sum, wherein the proportion is respectively recorded as Sv2 and Sign corresponding to the secondary voltages and the grounding current, and the minimum value in [ Sv2 and Sign ] is taken as the confidence interval;

(d) introducing a specific difference and an angular difference absolute quantity, and calculating and analyzing the specific difference angular difference absolute quantity of the current operation state;

and D1, recording ratio difference and angle difference data of power failure state verification, if power failure data are missing, replacing the power failure data mean values of ratio differences and angle differences of other voltage transformers of the same operating substation environment with the same specification, recording the obtained power failure verification ratio difference and angle difference data or (a) calculated ratio difference and angle difference data as Vr0 and delta 0, and then calculating the ratio difference V2 of the current voltage transformer to be detected to be Vr0+ delta P and the angle difference delta to be delta 0+ delta. Wherein Δ P, Δ δ is the data obtained in step (c);

(e) considering environmental influence, analyzing historical data of ratio difference, angle difference, temperature, humidity and vibration of the voltage transformer at regular time, and calculating normal distribution;

drawing a normal distribution curve based on the ratio difference, the angle difference, the temperature, the humidity and the vibration;

5. The voltage transformer monitoring method according to claim 3, wherein: when the voltage transformer to be measured is a capacitor voltage transformer, the acquisition and analysis method comprises the following steps:

(b) judging whether a fault exists;

firstly, the current magnitude of the high-voltage capacitor is calculated, wherein the current magnitude is IC1 Ig, or when Ig collection fails, fails or has no data, the current magnitude is calculated through IC2 and IP1, and the current magnitude is IC1 IC2 IP1, namely, the current magnitude IC1 and the phase of the high-voltage capacitor current are obtained through vector addition

VC is IC × Zc, Zc is 1/(2 × 3.141592 × f × C), f is a frequency value calculated by a V2 or Ig or IC2 waveform or specifies a 50Hz or 60Hz power frequency value, C is a high voltage capacitor C1, and a low voltage capacitor C2 nameplate nominal value or history check data; the IC is a low-voltage capacitor IC2, and the high-voltage capacitor current IC1 ═ Ig or IC1 ═ IC2+ IP 1.

Zc1＝1/(2*3.141592*f×C1)，Zc2＝1/(2*3.141592*f×C2)。

VC1＝IC1×Zc1,VC2＝IC2×Zc2,

The line voltage is then calculated: VLine ═ VC1+ VC 2;

the phase angle of the line voltage Vline is noted

And finally calculating the ratio difference: vr (Nr V2-VLINE)/VLINE

The angular difference is as follows:

is the phase angle of the secondary voltage; nr is a rated transformation ratio or a transformation ratio value of a historical test;

when harmonic parameters appear in the frequency spectrums of the low-voltage capacitor grounding current IC2 in a plurality of acquisition time periods and the harmonic content is more than 2% of the total frequency spectrum, or the harmonic content in the Ig frequency spectrum is more than 3% of the total frequency spectrum, judging that the tested capacitor type voltage transformer has a partial discharge phenomenon; or when the harmonic parameters appear in the Ig frequency spectrum, the harmonic content is more than 3% of the total frequency spectrum, and the IP1 harmonic content is more than the IC2 harmonic content, judging that the voltage-reducing transformer has a partial discharge phenomenon; otherwise go to b 3;

b 3: based on whether there is a fault in the phase angle difference:

calculating the phase angle difference delta vc of V2 and IC 2; phase angle difference δ vp of V2, IP 1; phase angle difference δ cp for IC2, IP 1; if the IC2 is larger than 10% of the rated value and |90- δ vc | is smaller than the threshold value, the capacity reduction of the high-voltage capacitor C1 is indicated; if the IP1 is more than the rated value by 20 percent and the absolute value of 90-delta cp is less than the threshold value, the failure of the primary winding of the step-down transformer or the smoothing compensation reactor or the lightning arrester or the high-voltage capacitor C1 is indicated; when IP1 is larger than the rated value by 20% and all |90- δ cp | are larger than the threshold value, the step-down transformer is indicated to be in failure;

b 4: estimating capacitance

first, bringing the standard value f0, C2 nominal capacitance,

calculating the L value:

then, the values of L, C2 and Fr are substituted into the following equation,

calculating deltaC, wherein the latest value of C2' is C2+ deltaC;

the same method is used to calculate C1 next.

calculate L ═ L value.

Then, the values of L', C1 and Fr are substituted into the following equation,

calculating delta C ', wherein the latest value of the high-voltage capacitor C1 ' is C1+ delta C ';

6. The voltage transformer monitoring method according to claim 1, wherein: when the measured mutual inductor does not have the ground connection amount acquisition or the ground connection leakage amount acquisition is failed and the data fluctuation amount greatly causes data which can not be subjected to individual mutual inductor error calculation, a plurality of mutual inductors with the same voltage level are adopted for joint analysis, namely, the probability distribution calculation errors of the secondary voltages of the plurality of voltage mutual inductors are specifically included:

Finding the maximum value | Ckmax | in | Ck |, and calculating the ratio p | Ckmax |/SAU when p is>When λ, the overall data is considered to be in a good state, and when p<Lambda considers that the data volatility is increased, abnormal data exist, and p is used as a confidence interval; the lambda value interval is 0.8000-0.9999, and the default value is 0.9600;

(3) then calculating Ak normal distribution;

(4) calculating the difference between the Ak data corresponding to the confidence interval p and the Ak average value as an error offset; or calculating the difference between the Ak data corresponding to the confidence interval p and a set standard value as an error offset;

the data obtained include:

electromagnetic voltage transformer: the amplitude offset and the angle offset of the secondary voltage V2 are recorded as [. DELTA.. epsilon.1,. DELTA.. epsilon.2 ], and the. DELTA.. epsilon.1 is taken as the specific difference offset, and the. DELTA.. epsilon.2 is taken as the angle difference offset;

the offset of the ratio difference: delta epsilon 1-Delta epsilon 2

Angular difference offset: delta epsilon 3-Delta epsilon 4

7. The voltage transformer monitoring method according to claim 1, wherein: the step S2 includes:

A. neural network frame for establishing following parameters

A1, when the device to be tested is a universal voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Igpeak, Igrms,

frg,Mfg,N

the output quantity is as follows: verr, delta err, Z, tan delta, PD, YN

A2. When the tested device is a capacitor voltage transformer:

the input quantity is: v2peak, V2rms, V2dc, Ic2, Ip1,

Igpeak,Igrms,frg,Mfg,C10,C20,N

is the phase angle of the secondary voltage V2,

the phase angle of the low voltage capacitor current IC2,

is the ground current Ig phase angle;

c10 is a nameplate or a high-voltage capacitance value of a historical test;

c20 is a low voltage capacitance value for nameplate or historical testing.

Low-voltage capacitance value output by the C2 neural network;

the high-voltage capacitance value output by the C1 neural network;

PD partial discharge capacity in pc or mV or dB;

the basic classifications are as follows:

8. The voltage transformer monitoring method according to claim 7, wherein: and applying a window function to the Bk to perform windowing treatment, wherein any one of a Hamming window, a Hanning window, a Gaussian window, a BlackHarries window, a Keseph window, a flat top window, a rectangular window and a triangular window is adopted.