Voltage measurement dual-measurement method and device fusing reactance and capacitor

Abstract

The embodiment of the invention provides a reactance and capacitor fused voltage measurement dual-measurement method and device, and the method comprises the steps: carrying out the fast Fourier transform of a preprocessed induced electromotive force signal and a preprocessed capacitive displacement current signal, and generating a frequency domain characteristic decomposition result, the inherent difference of the reactance channel and the capacitance channel in amplitude-frequency and phase-frequency characteristics is analyzed, and a frequency-variable transfer function matrix is constructed; performing amplitude and phase compensation on fundamental components and harmonic components of subsequently input induced electromotive force signals and capacitive displacement current signals according to the frequency-dependent transfer function matrix; performing complex plane vector synthesis on the compensated reactance signal and the compensated capacitance signal, and calculating a confidence index; and the weight factors of the two paths of signals in fusion are adjusted according to the confidence index, and a fusion voltage measurement value is output, so that the overall precision, reliability and anti-interference capability of the high-voltage measurement system are effectively improved, and the broadband measurement requirement in a complex power grid environment can be met.

Description

TECHNICAL FIELD

[0001] The embodiment of the present specification relates to the technical field of electrical measurement, in particular to a voltage measurement method fusing electric reactance and capacitor. BACKGROUND

[0002] In the field of electrical measurement, the capacitor voltage divider and the electromagnetic voltage transformer are traditional voltage measurement means, but each has its own limitations. The capacitor voltage divider has good response characteristics at high frequencies, but is easily disturbed by environmental temperature and external electric field; the electromagnetic transformer has high power frequency measurement accuracy, but has the risk of ferromagnetic resonance and narrow frequency band, and is difficult to meet the new demands of wideband measurement and harmonic analysis of power systems. In order to solve the inherent defects of single measurement principle, in recent years, the idea of fusing electric reactance and capacitor double measurement has been proposed, aiming to improve the system reliability through information complementation. However, the core challenge of realizing this technology is how to perform high-precision synchronous acquisition and processing on the output signals of the integrated device (electric reactance and capacitor) with two different physical characteristics, and effectively overcome the significant differences in amplitude-frequency and phase-frequency characteristics. The traditional method usually processes two signals independently, lacks deep cross-validation and bidirectional dynamic compensation mechanisms based on frequency domain characteristics, resulting in poor data fusion effect and difficulty in achieving accurate measurement results.

[0003] Therefore, a better solution is needed. SUMMARY

[0004] Therefore, the embodiment of the present specification provides a voltage measurement method fusing electric reactance and capacitor. One or more embodiments of the present specification also relate to a voltage measurement device fusing electric reactance and capacitor, a computing device, a computer-readable storage medium, and a computer program to solve the technical defects in the prior art.

[0005] According to a first aspect of the embodiment of the present specification, a voltage measurement method fusing electric reactance and capacitor is provided, comprising: Capture the induced electromotive force signal and the capacitive displacement current signal, and isolate and standardize the induced electromotive force signal and the capacitive displacement current signal to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the electric reactance branch, and the capacitive displacement current signal is generated in the electric capacitor branch; Perform fast Fourier transform on the preprocessed signal to decouple the fundamental component and the harmonic component, and generate a frequency domain feature decomposition result; Based on the frequency domain feature decomposition result, analyze the differences in amplitude-frequency and phase-frequency characteristics between the electric reactance channel and the electric capacitor channel to construct a frequency-varying transfer function matrix for bidirectional error compensation; Load the frequency-varying transfer function matrix into the real-time signal processor, compensate the fundamental component and harmonic component of the input induced electromotive force signal and capacitive displacement current signal, and generate a compensated reactance signal and a compensated capacitance signal; In a measurement cycle, the compensated reactance signal and the compensated capacitance signal are complex plane vector synthesized, and a confidence index is calculated; According to the confidence index, the weight factor of the two signals in fusion is adjusted, and the fusion voltage measurement value is output.

[0006] In a possible implementation, the induced electromotive force signal and the capacitive displacement current signal are captured and preprocessed by isolation and standardization to obtain a preprocessed signal, including: Synchronously capture the voltage signal flowing through the integrated integrated device, and obtain the original induced electromotive force analog signal of the reactance branch and the original capacitive displacement current analog signal of the capacitance branch through the high-bandwidth differential amplifier and the current sensor, respectively; The original induced electromotive force analog signal and the original capacitive displacement current analog signal are processed by photoelectric isolation and electromagnetic shielding to generate an isolated analog signal; The isolated analog signal is synchronously sampled and quantized to convert it into a synchronous digital isolated signal; Based on the preset reference value, the synchronous digital isolated signal is subjected to amplitude normalization and DC bias elimination processing to generate a standardized digital signal.

[0007] In a possible implementation, the preprocessed signal is subjected to fast Fourier transform to decouple the fundamental component and the harmonic component, and generate a frequency domain feature decomposition result, including: The preprocessed induced electromotive force signal and the capacitive displacement current signal are respectively subjected to Hanning window function to generate a windowed time domain signal sequence; The discrete frequency spectrum analysis is performed on the windowed time domain signal sequence to convert it into a discrete complex frequency spectrum containing real part and imaginary part information; according to the real part and imaginary part information of the discrete complex frequency spectrum, the amplitude spectrum and the phase spectrum corresponding thereto are calculated; The fundamental frequency index is determined based on the grid nominal frequency, and the fundamental amplitude component and the fundamental phase component at the fundamental frequency are extracted from the amplitude spectrum and the phase spectrum according to the determined fundamental frequency index; According to the fundamental frequency index, the harmonic frequency index corresponding to the specific harmonic order is calculated, and the harmonic amplitude component and the harmonic phase component of each specific harmonic are extracted from the amplitude spectrum and the phase spectrum; Finally, the frequency domain feature decomposition result composed of the fundamental amplitude component, the fundamental phase component, the harmonic amplitude component and the harmonic phase component is output.

[0008] In a possible implementation, based on the frequency domain feature decomposition result, differences between the reactance channel and the capacitance channel in amplitude-frequency and phase-frequency characteristics are analyzed to construct a frequency-varying transfer function matrix for bidirectional error compensation, including: Based on the frequency domain feature decomposition result, complex form fundamental amplitude component, fundamental phase component, harmonic amplitude component and harmonic phase component of the reactance channel and the capacitance channel at each frequency point are extracted respectively to generate reactance channel complex frequency domain feature vector and capacitance channel complex frequency domain feature vector; A complex number ratio of the reactance channel complex frequency domain feature vector and the capacitance channel complex frequency domain feature vector at the corresponding frequency point is calculated to form a frequency domain transfer ratio vector containing amplitude ratio and phase difference information; Segmented polynomial fitting of the amplitude-frequency characteristic and the phase-frequency characteristic of the frequency domain transfer ratio vector is performed by using a least square fitting algorithm to generate an amplitude compensation coefficient lookup table and a phase compensation coefficient lookup table respectively; The amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are combined according to the frequency dimension to construct a frequency-varying transfer function matrix containing amplitude-phase compound compensation information; Each storage unit of the frequency-varying transfer function matrix corresponds to an amplitude compensation coefficient and a phase compensation coefficient of a specific frequency point.

[0009] In a possible implementation, the frequency-varying transfer function matrix is loaded into a real-time signal processor to compensate for the fundamental component and the harmonic component of the input induced electromotive force signal and the capacitive displacement current signal to generate a compensated reactance signal and a compensated capacitance signal, including: The frequency-varying transfer function matrix is loaded into the cache of the real-time signal processor; The subsequent input induced electromotive force signal and capacitive displacement current signal are also subjected to fast Fourier transform and feature decoupling processing to obtain real-time fundamental component, real-time harmonic component and real-time frequency identification thereof in real time; Real-time amplitude compensation coefficients and real-time phase compensation coefficients corresponding to the real-time frequency identification are obtained by real-time addressing and querying the frequency-varying transfer function matrix according to the real-time frequency identification of the real-time fundamental component and the real-time harmonic component respectively; The real-time amplitude compensation coefficients and the real-time phase compensation coefficients are used to perform scalar multiplication and vector rotation operation on the amplitude and phase of the real-time fundamental component and the real-time harmonic component respectively to generate compensated fundamental component and compensated harmonic component; Inverse Fourier transform is performed on all the compensated fundamental component and the compensated harmonic component to reconstruct the compensated reactance signal and the compensated capacitance signal with consistent frequency response characteristics.

[0010] In a possible implementation, in a measurement period, the compensated reactance signal and the compensated capacitance signal are complex plane vector synthesized, and a confidence index is calculated, including: In a measurement period, the compensated reactance signal and the compensated capacitance signal are respectively converted into complex reactance vectors and complex capacitance vectors; The vector difference mode value between the complex reactance vector and the complex capacitance vector is calculated; The vector difference mode value is compared with a preset threshold value, and an instantaneous confidence factor is generated to represent the consistency of the two signals; The instantaneous confidence factors in a plurality of continuous measurement periods are slidingly weighted and averaged, and a confidence index for final fusion judgment is output.

[0011] In a possible implementation, the weight factor of the two signals in fusion is adjusted according to the confidence index, and a fused voltage measurement value is output, including: According to the confidence index, a preset weight-confidence mapping relationship table is queried to obtain an initial weight distribution coefficient corresponding to the corresponding confidence level; The initial weight distribution coefficient is subjected to recursive average processing based on a sliding window to generate a set of steady-state fusion weight factors; The steady-state fusion weight factors are used for complex scalar multiplication operation on the compensated reactance signal and the compensated capacitance signal respectively to obtain a pair of weight-adjusted signals; The two signal components in the pair of weight-adjusted signals are complex plane vector summed to generate a final fusion complex vector; The mode value of the final fusion complex vector is obtained, and the obtained mode value is output as a cross-validated fused voltage measurement value.

[0012] According to a second aspect of the embodiments of the present specification, a fused reactance and capacitor measuring device is provided, including: A signal capture module is configured to capture an induced electromotive force signal and a capacitive displacement current signal, and to isolate and standardize the induced electromotive force signal and the capacitive displacement current signal to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the reactance branch, and the capacitive displacement current signal is generated in the capacitance branch; A signal decomposition module is configured to perform fast Fourier transform on the preprocessed signal to decouple the fundamental component and the harmonic component, and generate a frequency domain feature decomposition result; A function construction module is configured to analyze the differences in amplitude-frequency and phase-frequency characteristics of the reactance channel and the capacitance channel based on the frequency domain feature decomposition result, to construct a frequency-varying transfer function matrix for bidirectional error compensation; The signal compensation module is configured to load the frequency-varying transfer function matrix into the real-time signal processor, compensate for fundamental wave components and harmonic wave components of the input induced electromotive force signal and the capacitive displacement current signal, and generate a compensated reactance signal and a compensated capacitance signal; The index determination module is configured to perform complex plane vector synthesis on the compensated reactance signal and the compensated capacitance signal in one measurement period, and calculate a confidence index. The result output module is configured to adjust a weight factor of the two signals in fusion according to the confidence index, and output a fused voltage measurement value.

[0013] According to a third aspect of the embodiments of the present specification, a computing device is provided, comprising: a memory and a processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, which realize the steps of the above-mentioned fused reactance and capacitor voltage measurement method.

[0014] According to a fourth aspect of the embodiments of the present specification, a computer readable storage medium is provided, which stores computer executable instructions, which realize the steps of the above-mentioned fused reactance and capacitor voltage measurement method when executed by a processor.

[0015] According to a fifth aspect of the embodiments of the present specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer executes the steps of the above-mentioned fused reactance and capacitor voltage measurement method.

[0016] The embodiments of the present specification provide a fused reactance and capacitor voltage measurement method and device, wherein the method comprises: performing fast Fourier transform on the preprocessed induced electromotive force signal and capacitive displacement current signal respectively to generate frequency domain feature decomposition results, and analyzing the inherent differences between the reactance channel and the capacitance channel in amplitude-frequency and phase-frequency characteristics to construct a frequency-varying transfer function matrix; compensating the amplitude and phase of the fundamental wave components and harmonic wave components of the subsequent input induced electromotive force signal and capacitive displacement current signal according to the frequency-varying transfer function matrix; performing complex plane vector synthesis on the compensated reactance signal and the compensated capacitance signal, and calculating a confidence index thereof; adjusting a weight factor of the two signals in fusion according to the confidence index, and outputting a fused voltage measurement value, which effectively improves the overall precision, reliability and anti-interference ability of the high-voltage measurement system, and can adapt to the wideband measurement demand in complex power grid environment. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a flowchart of a fused reactance and capacitor voltage measurement method provided by an embodiment of the present specification; Figure 2 is a structural diagram of a fused voltage and capacitance measurement device provided by one embodiment of the present specification; Figure 3 is a structural block diagram of a computing device provided by one embodiment of the present specification. DETAILED DESCRIPTION

[0018] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present specification. However, the present specification can be practiced without the specific details, other than in the examples, and it is understood that the scope of the present specification is not limited to the details below.

[0019] The terminology used in one or more embodiments of the present specification is for the purpose of describing particular embodiments only and is not intended to be limiting of one or more embodiments of the present specification. As used in one or more embodiments of the present specification and the accompanying claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in one or more embodiments of the present specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0020] It will be understood that, although the terms first, second, etc. can be used herein to describe various information, these terms are not intended to denote a temporal or chronological order. Rather, these terms are used solely to distinguish one from another only. For example, without departing from the scope of one or more embodiments of the present specification, first can be termed second, and similarly, second can be termed first. Depending on the context, the word "if' as used herein can be interpreted to mean "when" or "in response to determining" or "in response to a determination".

[0021] In the present specification, a fused voltage and capacitance measurement method is provided, and the present specification also relates to a fused voltage and capacitance measurement device, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0022] Referring to Figure 1 , Figure 1 A flowchart of a fused voltage and capacitance measurement method provided by one embodiment of the present specification is shown, which specifically includes the following steps.

[0023] Step 101: capture the induced electromotive force signal and the capacitive displacement current signal, and isolate and normalize the induced electromotive force signal and the capacitive displacement current signal for preprocessing to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the reactance branch, and the capacitive displacement current signal is generated in the capacitor branch.

[0024] In one possible implementation, capturing the induced electromotive force signal and the capacitive displacement current signal, and isolating and normalizing the induced electromotive force signal and the capacitive displacement current signal for preprocessing to obtain a preprocessed signal, includes: synchronously capturing a voltage signal flowing through an integrated integrated device, and obtaining an original induced electromotive force analog signal of the reactance branch and an original capacitive displacement current analog signal of the capacitor branch through a high-bandwidth differential amplifier and a current sensor respectively; performing photoelectric isolation and electromagnetic shielding processing on the original induced electromotive force analog signal and the original capacitive displacement current analog signal to generate an isolated analog signal; performing synchronous sampling and quantization on the isolated analog signal to convert it into a synchronous digital isolated signal; and performing amplitude normalization and DC bias elimination processing on the synchronous digital isolated signal based on a preset reference value to generate a normalized digital signal.

[0025] In actual application, under the action of high voltage, the integrated integrated device (integrated resonant reactor and voltage divider capacitor) will generate an induced electromotive force in the reactance branch due to electromagnetic induction principle, and will generate a capacitive displacement current in the capacitor branch due to electric field effect. A high-bandwidth (for example, the bandwidth is not less than 1 MHz) differential amplifier is used to collect the original induced electromotive force analog signal (voltage signal) at both ends of the reactance branch. At the same time, a current sensor is used to be connected in series in the capacitor branch to non-contactly obtain the original capacitive displacement current analog signal flowing through the capacitor branch. The signal collection ends of the two sensors are as close as possible to the corresponding terminals of the integrated integrated device in physical structure, so as to maximize the synchronization and authenticity of signal collection.

[0026] Since the original induced electromotive force analog signal and the original capacitive displacement current analog signal come from the high-voltage side, in order to prevent high voltage from damaging the subsequent low-voltage measurement circuit and further improve the anti-interference ability, the two original analog signals need to be isolated. In this step, an opto-isolator is used to isolate the voltage signal, and high insulation between the primary and secondary is used to realize electrical isolation. For the current signal, since it has been converted and isolated by the current sensor, one level of magnetic isolation or an isolated operational amplifier can be used for signal conditioning. At the same time, all signal transmission lines are connected into a shielded box by using coaxial shielded cables to effectively suppress external electromagnetic interference, and a pure isolated analog signal is generated.

[0027] The two isolated analog signals after isolation and shielding are connected to a multi-channel synchronous sampling analog-to-digital converter (ADC), all channels are driven by the same sampling clock, ensuring that the sampling time of the two signals is strictly synchronized, thereby avoiding the phase error introduced by the sampling time difference, quantizing the isolated analog signals, and converting them into timestamp-aligned synchronous digital isolated signals.

[0028] To eliminate the signal amplitude inconsistency caused by the sensor variable ratio, amplifier gain and ADC reference voltage difference, and to remove the possible DC bias component in the signal, the synchronous digital isolated signal needs to be standardized. Based on the preset reference value (determined by the standard source during system calibration), in the digital signal processor (DSP) or field programmable gate array (FPGA), the following steps are executed for each digital signal in turn: first, subtract the calculated DC bias (obtained by calculating the arithmetic mean of the signal in a power frequency period); second, multiply a normalization coefficient (the ratio of the reference value to the rated amplitude of the signal) to scale the signal amplitude to a unified unit value range, and finally generate a standardized digital signal with consistent amplitude and no DC component that can be used for subsequent advanced signal processing.

[0029] Step 102: Perform fast Fourier transform on the preprocessed signal to decouple the fundamental component and the harmonic component, and generate a frequency domain feature decomposition result.

[0030] In one possible implementation, the preprocessed signal is subjected to fast Fourier transform to decouple the fundamental component and the harmonic component, and generate a frequency domain feature decomposition result, including: applying a Hanning window function to the preprocessed induced electromotive force signal and capacitive displacement current signal respectively to generate a windowed time domain signal sequence; performing discrete spectral analysis on the windowed time domain signal sequence to convert it into a discrete complex spectrum containing real and imaginary information; calculating the amplitude spectrum and phase spectrum corresponding to the discrete complex spectrum according to the real and imaginary information of the discrete complex spectrum; determining the fundamental frequency index based on the nominal frequency of the power grid, and extracting the fundamental amplitude component and the fundamental phase component at the fundamental frequency from the amplitude spectrum and the phase spectrum according to the determined fundamental frequency index; calculating the harmonic frequency index corresponding to a specific harmonic order according to the fundamental frequency index, and then extracting the harmonic amplitude component and the harmonic phase component of each specific harmonic from the amplitude spectrum and the phase spectrum; finally outputting the frequency domain feature decomposition result composed of the fundamental amplitude component, the fundamental phase component, the harmonic amplitude component and the harmonic phase component.

[0031] In practical applications, in order to suppress spectral leakage and improve spectral analysis accuracy, a window function needs to be applied to the pre-processed induced electromotive force signal and the capacitive displacement current signal (both are time domain discrete sequences with a length of N). By multiplying the time domain discrete sequence with the Hanning window function point by point, a windowed time domain signal sequence is generated, which can effectively reduce the spectral leakage caused by non-synchronous sampling and make the spectral energy more concentrated.

[0032] Discrete spectral analysis is performed on the windowed time domain signal sequence, i.e. fast Fourier transform is performed to convert it from time domain to frequency domain, obtaining a discrete complex spectrum containing real and imaginary information. Then, according to the real and imaginary information of the discrete complex spectrum, the amplitude spectrum and the phase spectrum corresponding thereto are calculated. The calculation formula of the amplitude spectrum is: ; and the calculation formula of the phase spectrum is: [ ] In the formula, k is the frequency index (frequency sequence number); is the real part of the discrete complex spectrum at the kth frequency point; is the imaginary part of the discrete complex spectrum at the kth frequency point; is the amplitude spectrum value at the kth frequency point; is the phase spectrum value at the kth frequency point.

[0033] Determine the fundamental frequency index k based on the nominal frequency of the power grid fund , which can be calculated by the formula , where is the frequency index (frequency sequence number) corresponding to the fundamental frequency; is the nominal frequency of the power grid, usually 50 Hz or 60 Hz; N is the number of points (data length) of the fast Fourier transform, which is a positive integer; is the signal sampling frequency; is the rounding function, which rounds the calculation result to the nearest integer.

[0034] According to the fundamental frequency index k fund , the harmonic frequency index k harm corresponding to a specific harmonic number h is calculated, and the calculation formula is: .

[0035] The frequency domain feature decomposition result represents the amplitude and phase information of the fundamental wave and each harmonic contained in the original signal, providing a data basis for subsequent construction of a frequency-varying transfer function matrix and bidirectional error compensation.

[0036] Step 103: Based on the frequency domain feature decomposition result, analyze the differences in amplitude-frequency and phase-frequency characteristics between the reactance channel and the capacitance channel to construct a frequency-varying transfer function matrix for bidirectional error compensation.

[0037] In a possible implementation, based on the frequency domain feature decomposition result, differences in amplitude-frequency and phase-frequency characteristics of the inductive channel and the capacitive channel are analyzed to construct a frequency-varying transfer function matrix for bidirectional error compensation, including: based on the frequency domain feature decomposition result, complex-form fundamental amplitude component, fundamental phase component, harmonic amplitude component and harmonic phase component of the inductive channel and the capacitive channel at each frequency point are extracted respectively to generate inductive channel complex frequency domain feature vectors and capacitive channel complex frequency domain feature vectors; a complex number ratio of the inductive channel complex frequency domain feature vectors and the capacitive channel complex frequency domain feature vectors at the corresponding frequency points is calculated to form a frequency domain transfer ratio vector containing amplitude ratio and phase difference information; a least square fitting algorithm is applied to perform segmented polynomial fitting on the amplitude-frequency characteristics and the phase-frequency characteristics of the frequency domain transfer ratio vector to generate an amplitude compensation coefficient lookup table and a phase compensation coefficient lookup table respectively; the amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are combined according to the frequency dimension to construct a frequency-varying transfer function matrix containing amplitude-phase compound compensation information; and each storage unit of the frequency-varying transfer function matrix corresponds to an amplitude compensation coefficient and a phase compensation coefficient of a specific frequency point.

[0038] In actual applications, due to the different physical characteristics, the inductive channel and the capacitive channel have inherent differences in frequency response characteristics. The output signal of the inductive channel is proportional to the rate of change of voltage, the amplitude increases with the increase of frequency, and the phase always leads; while the output signal of the capacitive channel is related to the instantaneous value of voltage, the amplitude is relatively stable at different frequencies, and the phase always lags. This inherent difference leads to the inconsistency of the amplitude ratio and the phase relationship of the two signals at different frequencies. If a fixed compensation coefficient is used for signal fusion, a large error will be introduced under non-power frequency conditions, especially under complex working conditions containing harmonics, the measurement accuracy of the traditional method will be greatly reduced.

[0039] The application realizes the construction of the frequency-varying transfer function matrix through the following steps: first, based on the frequency domain feature decomposition result obtained in the foregoing embodiment, the feature components of the reactance channel and the capacitance channel at each frequency point are extracted respectively. For the reactance channel, the fundamental wave amplitude component, the fundamental wave phase component, and each harmonic amplitude component and harmonic phase component are combined into a complex frequency domain feature vector of the reactance channel in complex number form. Similarly, the corresponding components are also extracted for the capacitance channel to form a complex frequency domain feature vector of the capacitance channel. The amplitude and phase characteristics of the respective channels at different frequency points are completely characterized. Second, in order to quantify the inherent difference between the two channels, the complex number ratio of the complex frequency domain feature vectors of the reactance channel and the capacitance channel at the corresponding frequency points needs to be calculated. This complex number ratio contains both amplitude ratio information and phase difference information, thereby forming a frequency domain transfer ratio vector. Then, the least square fitting algorithm is applied to perform segmented polynomial fitting on the amplitude-frequency characteristics and the phase-frequency characteristics of the frequency domain transfer ratio vector respectively. For the amplitude ratio characteristics, the segmented fitting is performed by using the cubic spline interpolation method to generate an amplitude compensation coefficient lookup table; for the phase difference characteristics, the segmented fitting is performed by using the quintic polynomial fitting method to generate a phase compensation coefficient lookup table. Finally, the amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are combined according to the frequency dimension to construct a two-dimensional frequency-varying transfer function matrix.

[0040] Step 104: loading the frequency-varying transfer function matrix into the real-time signal processor to compensate for the fundamental wave components and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, and generating a compensated reactance signal and a compensated capacitance signal.

[0041] In a possible implementation, loading the frequency-varying transfer function matrix into the real-time signal processor to compensate for the fundamental wave components and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, and generating a compensated reactance signal and a compensated capacitance signal, includes: loading the frequency-varying transfer function matrix into the cache of the real-time signal processor; performing fast Fourier transform and feature decoupling processing on the subsequent input induced electromotive force signal and capacitive displacement current signal to obtain real-time fundamental wave components, real-time harmonic components, and real-time frequency identifiers thereof in real time; querying the frequency-varying transfer function matrix in real time according to the real-time frequency identifiers of the real-time fundamental wave components and the real-time harmonic components to obtain real-time amplitude compensation coefficients and real-time phase compensation coefficients corresponding to the real-time frequency identifiers; performing scalar multiplication and vector rotation operations on the amplitudes and phases of the real-time fundamental wave components and the real-time harmonic components by using the obtained real-time amplitude compensation coefficients and real-time phase compensation coefficients to generate compensated fundamental wave components and compensated harmonic components; and performing inverse Fourier transform on all the compensated fundamental wave components and the compensated harmonic components to reconstruct the compensated reactance signal and the compensated capacitance signal with consistent frequency response characteristics.

[0042] In practical applications, the frequency-varying transfer function matrix is loaded into the cache of a real-time signal processor and stored in the form of a lookup table, where each storage unit corresponds to the amplitude compensation coefficient and the phase compensation coefficient of a specific frequency point. Using the cache storage method can improve the data access speed and ensure the real-time processing requirements. Field programmable gate arrays (FPGAs) or digital signal processors (DSPs) can be used as real-time signal processing platforms because they have parallel processing capabilities and cache architectures and can meet the real-time requirements.

[0043] Fast Fourier transform and characteristic decoupling processing are performed on the induced electromotive force signals and the capacitive displacement current signals collected in real time subsequently, and the fundamental component, the harmonic components, and the corresponding frequency identifiers of the signals are extracted in real time. The frequency identifier contains not only the frequency band information of the component but also the accurate frequency quantization value, which provides a basis for subsequent query of the compensation coefficients.

[0044] According to the frequency identifiers obtained in real time, real-time addressing and querying are performed in the frequency-varying transfer function matrix. An efficient address mapping mechanism is established to map the continuous frequency values to discrete matrix indexes, and the nearest neighbor interpolation algorithm is used to ensure the accuracy of the query. For the frequency identifier of each real-time component, the system can quickly retrieve the corresponding amplitude compensation coefficient and phase compensation coefficient.

[0045] The real-time compensation coefficients obtained by querying are used to accurately compensate the frequency components. For amplitude compensation, scalar multiplication is used to multiply the original amplitude by the compensation coefficient; for phase compensation, vector rotation is used to accurately adjust the phase through complex exponential multiplication. This process simultaneously compensates the signals in the reactance channel and the capacitance channel in both directions, ensuring that the two channels have consistent frequency response characteristics after compensation.

[0046] Inverse Fourier transform is performed on all the compensated fundamental components and harmonic components to reconstruct the time-domain signals. The reconstructed compensated reactance signals and compensated capacitance signals not only maintain the waveform characteristics of the original signals but also eliminate the frequency response differences between the two channels.

[0047] Step 105: In a measurement period, the compensated reactance signals and the compensated capacitance signals are vector synthesized in the complex plane, and a confidence index is calculated. In one possible implementation, in one measurement period, the compensated reactance signal and the compensated capacitance signal are complex plane vector synthesized, and a confidence index is calculated, including: in one measurement period, the compensated reactance signal and the compensated capacitance signal are respectively converted into complex reactance complex vectors and capacitance complex vectors; a vector difference mode value between the reactance complex vector and the capacitance complex vector is calculated; the vector difference mode value is compared with a preset threshold value, and an instantaneous confidence factor used to represent consistency of the two signals is generated; the instantaneous confidence factors in continuous multiple measurement periods are sliding weighted average calculated, and a confidence index used for final fusion judgment is output.

[0048] In actual application, in one measurement period, the compensated time domain reactance signal and the capacitance signal are respectively converted into complex reactance complex vectors and capacitance complex vectors. The conversion method adopts Hilbert transform or analytic signal method, and converts the real signal into a complex signal containing a real part and an imaginary part, wherein the real part represents the original signal, and the imaginary part represents the Hilbert transform result of the original signal, so that each signal is represented as a vector with clear amplitude and phase information on the complex plane. Then, a vector difference mode value between the two complex vectors is calculated, and the mode value is obtained by calculating the absolute value of the difference between the two complex vectors, and the numerical value directly reflects the consistency degree of the reactance channel and the capacitance channel in the current measurement period. The smaller the mode value is, the better the consistency of the two signals is; the larger the mode value is, the greater the difference between the two signals is. The calculated vector difference mode value is compared with a preset threshold value (which can be set as 2 times of the measurement error allowed by the system). An instantaneous confidence factor is generated through the comparison result, and the factor adopts a numerical value between 0 and 1 to represent that when the vector difference mode value is less than the threshold value, the confidence factor is close to 1, indicating that the signal consistency is high; when the vector difference mode value exceeds the threshold value, the confidence factor tends to 0, indicating that the signal consistency is low. Moreover, in order to improve the reliability of the confidence evaluation, the instantaneous confidence factors in continuous multiple measurement periods are sliding weighted average calculated. The exponential weighted moving average method is adopted, and the recent data is given a greater weight, which can quickly reflect the change trend of the signal quality and smooth the fluctuations caused by accidental interference. The finally output confidence index is used as an important basis for subsequent signal fusion weight distribution.

[0049] Step 106: adjusting the weight factor of the two signals in fusion according to the confidence index, and outputting a fusion voltage measurement value.

[0050] In one possible implementation, the weighting factors of the two signals in the fusion are adjusted according to the confidence index, and the fused voltage measurement value is output. This includes: querying a preset weight-confidence mapping table according to the confidence index to obtain the initial weight allocation coefficients corresponding to the corresponding confidence levels; applying a sliding window-based recursive averaging process to the initial weight allocation coefficients to generate a set of steady-state fusion weighting factors; using the steady-state fusion weighting factors, performing complex scalar multiplication operations on the compensated reactance signal and the compensated capacitance signal respectively to obtain a weighted signal pair; performing complex plane vector summation on the two signal components in the weighted signal pair to generate a final fused complex vector; obtaining the magnitude of the final fused complex vector, and outputting the obtained magnitude as the cross-validated fused voltage measurement value.

[0051] In practical applications, based on the confidence index calculated in the aforementioned embodiments, a preset weight-confidence mapping table is consulted to obtain the corresponding initial weight allocation coefficients. The weight-confidence mapping table is established in advance, including mapping information between the confidence index value range and the corresponding initial weight allocation coefficients for reactance and capacitance signals. A nonlinear mapping strategy is adopted: when the confidence index is high (e.g., greater than 0.8), approximately equal weight allocation is used; when the confidence index is low, the weight proportion of channels with higher reliability is increased to form the initial weight allocation coefficients. Furthermore, to avoid drastic fluctuations in weights due to instantaneous interference, a recursive averaging process based on a sliding window is applied to the initial weight allocation coefficients. A sliding window with a length of 5-10 measurement periods is used to calculate the weight coefficients using a weighted average, assigning higher weights to recent data, thereby generating a set of smooth and stable steady-state fusion weight factors. This processing method ensures both the timeliness of weight adjustment and avoids unnecessary oscillations. Next, using a steady-state fusion weighting factor, complex scalar multiplication is performed on the compensated reactance and compensated capacitance signals respectively, while simultaneously adjusting the amplitude and phase of the two signals to obtain a weighted signal pair. This ensures that the two signals have consistent dimensions and phase references before fusion. Then, the two signal components in the weighted signal pair are summed using a complex plane vector summation. Since the two signals have undergone weight adjustment and phase alignment, this vector summation operation can retain effective information to the maximum extent, suppress random errors, and generate an optimal final fused complex vector. Finally, the magnitude of the final fused complex vector is calculated, which is the cross-validated fused voltage measurement value. The fusion result output through complex plane vector synthesis takes into account both the amplitude and phase information of the two channels, exhibiting higher accuracy and reliability compared to a simple arithmetic average.

[0052] In one embodiment, the measurement method further includes: The compensated reactance signal and compensated capacitance signal are continuously acquired for multiple measurement cycles, and the synthesis process of the two signals in each cycle is characterized as a time-varying vector trajectory on the complex plane. Homology group analysis is performed on the time-varying vector trajectory set, that is, by calculating its persistent homology, a set of topological invariant features that characterize the macroscopic topological structure of the trajectory set is extracted. The set of features includes, but is not limited to, the evolution of ring structure, number of holes and connected components. The topology invariant feature set is compared with the ideal reference topology model to obtain the matching degree between the two, and a topology consistency factor is generated based on the matching degree. Based on the magnitude and characteristics of the topology consistency factor, it is determined whether the system is in a steady state or a transient state. If the factor indicates that the topology is highly consistent and stable, the weight of historical data in the confidence index calculation is increased. Otherwise, the online update process of the frequency-varying transfer function matrix is ​​triggered, and the amplitude and phase compensation coefficients in the matrix are locally iteratively optimized using the vector trajectory data of the current period. The optimized new matrix or the adjusted confidence calculation logic is then applied to the signal processing and fusion process in subsequent measurement cycles.

[0053] In practice, compensated reactance and compensated capacitance signals are continuously acquired over multiple measurement cycles (typically 10-50 cycles). These signals are represented as time-varying vector trajectories on the complex plane. The signal fusion process of each cycle forms a unique trajectory, and the trajectories of multiple cycles constitute a trajectory set. These trajectories reflect the dynamic characteristics of the system under different operating conditions. Homology group analysis is performed on the time-varying vector trajectory set, and a continuous homology calculation method is used to extract a set of topologically invariant features characterizing the macroscopic topological structure of the trajectory set. The extracted set of topologically invariant features is compared with a pre-established ideal reference topology model. By calculating the degree of matching between the two, a topological consistency factor is generated to characterize the degree of conformity between the current system state and the ideal state; a higher value indicates that the system is closer to the ideal operating state.

[0054] The system's steady-state or transient state is determined based on the magnitude and characteristics of the topology consistency factor. If the factor indicates a highly consistent and stable topology, the weight of historical data in the confidence index calculation is increased, improving measurement stability. If the factor indicates a change in the topology, an online update process for the frequency-varying transfer function matrix is ​​triggered, using vector trajectory data from the current period to perform local iterative optimization of the amplitude and phase compensation coefficients in the matrix. The optimized new matrix or the adjusted confidence calculation logic is applied to the signal processing and fusion processes of subsequent measurement periods, forming a closed-loop optimization system. Through this continuous adaptive adjustment, the measurement system is ensured to maintain optimal operating conditions over a long period, achieving intelligent identification of steady-state and transient states, enabling autonomous parameter adjustment based on system status, and maintaining long-term measurement accuracy.

[0055] In another embodiment, the measurement method further includes: The amplitude, phase, and frequency parameters of each harmonic are extracted from the frequency domain feature decomposition results of the compensated signal to form the initial harmonic feature vector. In the early stage of steady-state operation of the system, the initial harmonic feature vector is subjected to long-term statistical learning to establish a "self" harmonic feature library that represents the normal operating condition. The feature library records the reference range of the amplitude and phase of each harmonic and its probability distribution model. In real-time measurement, the real-time harmonic feature vector decoupled from the current cycle is matched with the "self" harmonic feature library. If the feature of a certain harmonic exceeds the reference range and does not conform to the probability distribution, it is marked as a "non-self" harmonic feature. The marked "non-self" harmonic features are continuously verified. If they appear continuously for multiple consecutive cycles, the suppression mechanism is activated. By adjusting the compensation coefficient of the corresponding frequency point in the frequency-varying transfer function matrix, the weight of the harmonic in the fusion process is selectively attenuated. The verified "non-self" harmonic features are updated to the blacklist of the feature library, and the immune recognition threshold and suppression strategy in subsequent cycles are optimized accordingly.

[0056] It should be noted that traditional voltage measurement methods often use fixed filtering thresholds or simple threshold judgments when faced with high-order harmonic pollution caused by nonlinear loads (such as frequency converters and electric arc furnaces) or random transient interference (such as lightning strikes and switching operations). This makes it difficult to distinguish between normal background harmonics and abnormal characteristic harmonics, resulting in decreased measurement accuracy or instantaneous jumps.

[0057] This embodiment first extracts key parameters such as amplitude, phase, and frequency of each harmonic from the high-precision frequency domain feature decomposition results of the signal after bidirectional error compensation, thus forming an initial harmonic feature vector. In the initial stage when the system is determined to be operating in a steady state, the controller performs long-term statistical learning on a large number of initial harmonic feature vectors to establish a "self-harmonic" feature library characterizing the normal operating condition of the system. This feature library does not simply record average values, but rather records in detail the reference range of each harmonic amplitude and phase (e.g., mean ± 3 standard deviations) and its more complex probability distribution model (e.g., Gaussian mixture model), thereby depicting the digital fingerprint of the "self-harmonic".

[0058] In the real-time measurement cycle, the real-time harmonic feature vector decoupled in the current measurement cycle is matched with the established "self" feature library at high speed and with high accuracy. If the calculation finds that the feature of a certain harmonic exceeds its historical reference range and its occurrence probability is much lower than the expected probability distribution model, it is immediately marked as a suspicious "non-self" harmonic feature. To ensure the reliability of the judgment and avoid false alarms, these marked "non-self" harmonic features are continuously verified and monitored. If the abnormal feature continues to appear in multiple consecutive measurement cycles (e.g., 5 cycles), it is confirmed as persistent interference, and a suppression mechanism is immediately activated: by fine-tuning the amplitude and phase compensation coefficients of the corresponding abnormal frequency point in the loaded frequency-varying transfer function matrix, the weight of the "non-self" harmonic is selectively attenuated before signal fusion, thereby effectively suppressing its contamination of the final fused voltage measurement value. These verified "non-self" harmonic features are updated to the blacklist in the feature library, and the immune recognition threshold (e.g., increasing sensitivity or reducing fault tolerance) and suppression strategies (e.g., adjusting attenuation intensity) in subsequent monitoring cycles are adaptively optimized accordingly. Through this closed-loop, self-learning process, this embodiment achieves highly intelligent management of harmonic pollution, improving the anti-interference capability, stability, and accuracy of voltage measurement in complex electromagnetic environments, thereby making the final output fused voltage measurement value more reliable and accurate.

[0059] This application effectively overcomes the inherent defects of a single measurement principle by synchronously acquiring dual-channel signals of reactance and capacitance, and through frequency domain feature analysis and bidirectional dynamic compensation. It achieves the complementary advantages of two heterogeneous measurement signals and finally outputs a cross-validated high-precision voltage measurement value, thereby improving the overall accuracy, reliability and anti-interference capability of the high-voltage measurement system and enabling it to adapt to the broadband measurement requirements in complex power grid environments.

[0060] Corresponding to the above method embodiments, this specification also provides embodiments of a dual measuring device integrating reactance and capacitor voltage measurement. Figure 2 A schematic diagram of a dual-measurement device integrating reactance and capacitor voltage measurement according to one embodiment of this specification is shown. Figure 2 As shown, the device includes: The signal acquisition module 201 is configured to acquire the induced electromotive force signal and the capacitive displacement current signal, and to isolate and standardize the induced electromotive force signal and the capacitive displacement current signal to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the reactance branch and the capacitive displacement current signal is generated in the capacitor branch. The signal decomposition module 202 is configured to perform a fast Fourier transform on the preprocessed signal, decouple the fundamental component and harmonic components, and generate frequency domain feature decomposition results. The function construction module 203 is configured to analyze the differences in amplitude and phase frequency characteristics of the reactance channel and the capacitor channel based on the frequency domain eigenvalue decomposition results, so as to construct a frequency-varying transfer function matrix for bidirectional error compensation. The signal compensation module 204 is configured to load the frequency-varying transfer function matrix into the real-time signal processor to compensate the fundamental and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, and generate the compensated reactance signal and the compensated capacitance signal. The index determination module 205 is configured to perform complex plane vector synthesis of the compensated reactance signal and the compensated capacitance signal within a measurement cycle, and calculate the confidence index. The result output module 206 is configured to adjust the weighting factor of the two signals in the fusion according to the confidence index and output the fused voltage measurement value.

[0061] In one possible implementation, the induced electromotive force signal and the capacitive displacement current signal are captured, and the induced electromotive force signal and the capacitive displacement current signal are isolated and standardized preprocessed to obtain a preprocessed signal, including: The voltage signal flowing through the integrated device is captured synchronously, and then the original induced electromotive force analog signal of the reactance branch and the original capacitive displacement current analog signal of the capacitor branch are obtained through a high-bandwidth differential amplifier and a current sensor, respectively. The original induced electromotive force simulation signal and the original capacitive displacement current simulation signal are photoelectrically isolated and electromagnetically shielded to generate an isolated simulation signal; The isolated analog signal is synchronously sampled and quantized, and then converted into a synchronous digital isolated signal; Based on a preset reference value, the synchronous digital isolation signal is normalized in amplitude and DC bias is eliminated to generate a standardized digital signal.

[0062] In one possible implementation, the preprocessed signal is subjected to a Fast Fourier Transform to decouple the fundamental and harmonic components, generating a frequency domain eigenvalue decomposition result, including: Hanning window functions are applied to the preprocessed induced electromotive force signal and capacitive displacement current signal respectively to generate windowed time-domain signal sequences; Perform discrete spectrum analysis on the windowed time-domain signal sequence to convert it into a discrete complex spectrum containing real and imaginary part information; calculate the corresponding amplitude spectrum and phase spectrum based on the real and imaginary part information of the discrete complex spectrum; The fundamental frequency index is determined based on the nominal frequency of the power grid, and the fundamental amplitude component and fundamental phase component at the fundamental frequency are extracted from the amplitude spectrum and phase spectrum according to the determined fundamental frequency index. The harmonic frequency index corresponding to a specific harmonic order is calculated based on the fundamental frequency index, and then the harmonic amplitude component and harmonic phase component of each specific harmonic are extracted from the amplitude spectrum and phase spectrum. The final output is the frequency domain feature decomposition result composed of the fundamental amplitude component, the fundamental phase component, the harmonic amplitude component, and the harmonic phase component.

[0063] In one possible implementation, based on the frequency domain eigenvalue decomposition results, the differences in amplitude-frequency and phase-frequency characteristics between the reactance channel and the capacitance channel are analyzed to construct a frequency-varying transfer function matrix for bidirectional error compensation, including: Based on the frequency domain feature decomposition results, the complex form of the fundamental amplitude component, fundamental phase component, harmonic amplitude component, and harmonic phase component at each frequency point are extracted for the reactance channel and the capacitor channel, respectively, to generate the complex frequency domain feature vector of the reactance channel and the complex frequency domain feature vector of the capacitor channel. Calculate the complex ratio of the complex frequency domain eigenvector of the reactance channel to the complex frequency domain eigenvector of the capacitor channel at the corresponding frequency points to form a frequency domain transfer ratio vector containing amplitude ratio and phase difference information; The least squares fitting algorithm is used to perform piecewise polynomial fitting on the amplitude-frequency and phase-frequency characteristics of the frequency domain transfer ratio vector, generating amplitude compensation coefficient lookup tables and phase compensation coefficient lookup tables respectively. The amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are combined according to the frequency dimension to construct a frequency-varying transfer function matrix containing amplitude and phase composite compensation information; Each storage cell in the frequency-variable transfer function matrix corresponds to the amplitude compensation coefficient and phase compensation coefficient at a specific frequency point.

[0064] In one possible implementation, the frequency-varying transfer function matrix is ​​loaded into a real-time signal processor to compensate for the fundamental and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, generating compensated reactance and capacitance signals, including: The frequency-varying transfer function matrix is ​​loaded into the cache of the real-time signal processor; The induced electromotive force signal and capacitive displacement current signal that are subsequently input are also subjected to fast Fourier transform and feature decoupling processing to obtain the corresponding real-time fundamental component, real-time harmonic component and their real-time frequency identifier. Based on the real-time frequency identifiers of the real-time fundamental component and the real-time harmonic component, the frequency-varying transfer function matrix is ​​queried in real time to obtain the real-time amplitude compensation coefficient and the real-time phase compensation coefficient corresponding to the real-time frequency identifier. Using the obtained real-time amplitude compensation coefficient and real-time phase compensation coefficient, scalar multiplication and vector rotation operations are performed on the amplitude and phase of the real-time fundamental component and the real-time harmonic component, respectively, to generate the compensated fundamental component and the compensated harmonic component. Perform inverse Fourier transform on all compensated fundamental and harmonic components to reconstruct the compensated reactance and capacitance signals with consistent frequency response characteristics.

[0065] In one possible implementation, within one measurement cycle, the compensated reactance signal and the compensated capacitance signal are combined using a complex plane vector synthesis, and a confidence index is calculated, including: Within one measurement cycle, the compensated reactance signal and the compensated capacitance signal are converted into complex reactance vector and complex capacitance vector in complex form, respectively. Calculate the vector difference magnitude between the complex reactance vector and the complex capacitance vector; The vector differential value is compared with a preset threshold to generate an instantaneous confidence factor that characterizes the consistency between the two signals. A moving weighted average is calculated for the instantaneous confidence factors over multiple consecutive measurement periods, and a confidence index is output for the final fusion decision.

[0066] In one possible implementation, the weighting factors of the two signals in the fusion are adjusted according to a confidence index, and the fused voltage measurement value is output, including: Based on the confidence index, a preset weight-confidence mapping table is queried to obtain the initial weight allocation coefficients corresponding to the corresponding confidence level; A set of steady-state fusion weight factors is generated by applying a sliding window-based recursive averaging process to the initial weight allocation coefficients. Using the steady-state fusion weighting factor, complex scalar multiplication is performed on the compensated reactance signal and the compensated capacitance signal respectively to obtain the weighted signal pair. The two signal components in the weighted signal pair are summed by complex plane vector summation to generate a final fused complex vector. Obtain the magnitude of the final fused complex vector and output the obtained magnitude as the cross-validated fused voltage measurement.

[0067] The above is a schematic scheme of a dual-measurement device integrating reactance and capacitor voltage measurement according to this embodiment. It should be noted that the technical solution of this dual-measurement device integrating reactance and capacitor voltage measurement belongs to the same concept as the technical solution of the dual-measurement method integrating reactance and capacitor voltage measurement described above. For details not described in detail in the technical solution of the dual-measurement device integrating reactance and capacitor voltage measurement, please refer to the description of the technical solution of the dual-measurement method integrating reactance and capacitor voltage measurement described above.

[0068] Figure 3A structural block diagram of a computing device 300 according to one embodiment of this specification is shown. The components of the computing device 300 include, but are not limited to, a memory 310 and a processor 320. The processor 320 is connected to the memory 310 via a bus 330, and a database 350 is used to store data.

[0069] The computing device 300 also includes an access device 340, which enables the computing device 300 to communicate via one or more networks 360. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 340 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0070] In one embodiment of this specification, the aforementioned components of the computing device 300 and Figure 3 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 3 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0071] The computing device 300 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 300 can also be a mobile or stationary server.

[0072] The processor 320 executes computer-executable instructions, which, when executed by the processor, implement the steps of the aforementioned dual-measurement method for merging reactance and capacitor voltage. The above is a schematic representation of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the aforementioned dual-measurement method for merging reactance and capacitor voltage belong to the same concept. Details not described in detail in the technical solution of the computing device can be found in the description of the technical solution of the aforementioned dual-measurement method for merging reactance and capacitor voltage.

[0073] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described dual measurement method for merging reactance and capacitor voltage measurement.

[0074] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium belongs to the same concept as the technical solution of the above-described dual measurement method for merging reactance and capacitor voltage measurement. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the above-described dual measurement method for merging reactance and capacitor voltage measurement.

[0075] An embodiment of this specification also provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the above-described dual measurement method for merging reactance and capacitor voltage measurement.

[0076] The above is an illustrative scheme of a computer program according to this embodiment. It should be noted that the technical solution of this computer program belongs to the same concept as the technical solution of the above-mentioned dual measurement method for merging reactance and capacitor voltage measurement. For details not described in detail in the technical solution of the computer program, please refer to the description of the technical solution of the above-mentioned dual measurement method for merging reactance and capacitor voltage measurement.

[0077] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0078] The computer instructions include computer program code, which may be in the form of source code, object code, executable file, or certain intermediate forms. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media may not include electrical carrier signals and telecommunication signals.

[0079] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0080] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0081] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A dual measurement method integrating reactance and capacitor voltage measurement, characterized in that, include: The induced electromotive force signal and the capacitive displacement current signal are captured, and the induced electromotive force signal and the capacitive displacement current signal are isolated and standardized preprocessed to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the reactance branch and the capacitive displacement current signal is generated in the capacitor branch. The preprocessed signal is subjected to a fast Fourier transform to decouple the fundamental component and harmonic components, generating a frequency domain feature decomposition result. Based on the frequency domain eigenvalue decomposition results, the differences in amplitude and phase frequency characteristics between the reactance channel and the capacitor channel are analyzed to construct a frequency-varying transfer function matrix for bidirectional error compensation. The frequency-varying transfer function matrix is ​​loaded into the real-time signal processor to compensate the fundamental and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, generating compensated reactance signal and compensated capacitance signal. Within one measurement cycle, the compensated reactance signal and the compensated capacitance signal are combined using a complex plane vector synthesis, and a confidence index is calculated. The weighting factors of the two signals in the fusion are adjusted according to the confidence index, and the fused voltage measurement value is output.

2. The method according to claim 1, characterized in that, The process involves capturing the induced electromotive force signal and the capacitive displacement current signal, and then isolating and standardizing the induced electromotive force signal and the capacitive displacement current signal to obtain a preprocessed signal, including: The voltage signal flowing through the integrated device is captured synchronously, and then the original induced electromotive force analog signal of the reactance branch and the original capacitive displacement current analog signal of the capacitor branch are obtained through a high-bandwidth differential amplifier and a current sensor, respectively. The original induced electromotive force simulation signal and the original capacitive displacement current simulation signal are subjected to photoelectric isolation and electromagnetic shielding processing to generate an isolated simulation signal; The isolated analog signal is synchronously sampled and quantized to convert it into a synchronous digital isolated signal; Based on a preset reference value, the synchronous digital isolation signal is subjected to amplitude normalization and DC bias elimination processing to generate a standardized digital signal.

3. The method according to claim 1, characterized in that, The step of performing a Fast Fourier Transform on the preprocessed signal to decouple the fundamental and harmonic components and generate a frequency domain feature decomposition result includes: Hanning window functions are applied to the preprocessed induced electromotive force signal and capacitive displacement current signal respectively to generate a windowed time-domain signal sequence; Discrete spectrum analysis is performed on the windowed time-domain signal sequence to convert it into a discrete complex spectrum containing real and imaginary part information; the corresponding amplitude spectrum and phase spectrum are calculated based on the real and imaginary part information of the discrete complex spectrum. The fundamental frequency index is determined based on the nominal frequency of the power grid, and the fundamental amplitude component and fundamental phase component at the fundamental frequency are extracted from the amplitude spectrum and phase spectrum according to the determined fundamental frequency index. The harmonic frequency index corresponding to a specific harmonic order is calculated based on the fundamental frequency index, and then the harmonic amplitude component and harmonic phase component of each specific harmonic are extracted from the amplitude spectrum and phase spectrum. The final output is the frequency domain feature decomposition result composed of the fundamental amplitude component, the fundamental phase component, the harmonic amplitude component, and the harmonic phase component.

4. The method according to claim 1, characterized in that, Based on the frequency domain eigenvalue decomposition results, the differences in amplitude-frequency and phase-frequency characteristics between the reactance channel and the capacitance channel are analyzed to construct a frequency-varying transfer function matrix for bidirectional error compensation, including: Based on the frequency domain feature decomposition results, the complex form of the fundamental amplitude component, fundamental phase component, harmonic amplitude component, and harmonic phase component of the reactance channel and the capacitor channel at each frequency point are extracted respectively to generate the complex frequency domain feature vector of the reactance channel and the complex frequency domain feature vector of the capacitor channel. Calculate the complex ratio of the complex frequency domain feature vector of the reactance channel to the complex frequency domain feature vector of the capacitor channel at the corresponding frequency points to form a frequency domain transfer ratio vector containing amplitude ratio and phase difference information; The least squares fitting algorithm is used to perform piecewise polynomial fitting on the amplitude-frequency characteristics and phase-frequency characteristics of the frequency domain transfer ratio vector, and the amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are generated respectively. The amplitude compensation coefficient lookup table and the phase compensation coefficient lookup table are combined according to the frequency dimension to construct a frequency-varying transfer function matrix containing amplitude and phase composite compensation information. Each storage unit of the frequency-varying transfer function matrix corresponds to the amplitude compensation coefficient and phase compensation coefficient at a specific frequency point.

5. The method according to claim 1, characterized in that, The step of loading the frequency-varying transfer function matrix into the real-time signal processor to compensate for the fundamental and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, generating compensated reactance and compensated capacitance signals, includes: The frequency-varying transfer function matrix is ​​loaded into the cache of the real-time signal processor; The induced electromotive force signal and capacitive displacement current signal that are subsequently input are also subjected to fast Fourier transform and feature decoupling processing to obtain the corresponding real-time fundamental component, real-time harmonic component and their real-time frequency identifier. Based on the real-time frequency identifiers of the real-time fundamental component and the real-time harmonic component, the frequency-varying transfer function matrix is ​​queried in real time to obtain the real-time amplitude compensation coefficient and the real-time phase compensation coefficient corresponding to the real-time frequency identifier. Using the obtained real-time amplitude compensation coefficient and real-time phase compensation coefficient, scalar multiplication and vector rotation operations are performed on the amplitude and phase of the real-time fundamental component and the real-time harmonic component, respectively, to generate the compensated fundamental component and the compensated harmonic component. Perform inverse Fourier transform on all compensated fundamental and harmonic components to reconstruct the compensated reactance and capacitance signals with consistent frequency response characteristics.

6. The method according to claim 1, characterized in that, Within one measurement cycle, the compensated reactance signal and the compensated capacitance signal are combined using a complex plane vector synthesis method, and a confidence index is calculated, including: Within one measurement cycle, the compensated reactance signal and the compensated capacitance signal are respectively converted into complex reactance vector and complex capacitance vector in complex form; Calculate the vector difference magnitude between the complex reactance vector and the complex capacitance vector; The vector differential value is compared with a preset threshold to generate an instantaneous confidence factor that characterizes the consistency strength of the two signals. A moving weighted average is calculated for the instantaneous confidence factors over multiple consecutive measurement periods to output a confidence index for final fusion determination.

7. The method according to claim 1, characterized in that, The step of adjusting the weighting factors of the two signals in the fusion process according to the confidence index and outputting the fused voltage measurement value includes: Based on the confidence index, a preset weight-confidence mapping table is queried to obtain the initial weight allocation coefficients corresponding to the corresponding confidence level; A set of steady-state fusion weight factors are generated by applying a sliding window-based recursive averaging process to the initial weight allocation coefficients. Using the steady-state fusion weighting factor, complex scalar multiplication operations are performed on the compensated reactance signal and the compensated capacitance signal respectively to obtain the weighted signal pair. The two signal components in the weighted signal pair are summed by complex plane vector summation to generate a final fused complex vector. Obtain the magnitude of the final fused complex vector and output the obtained magnitude as the cross-validated fused voltage measurement value.

8. A dual-measurement device integrating reactance and capacitor for voltage measurement, characterized in that, include: The signal acquisition module is configured to acquire induced electromotive force signal and capacitive displacement current signal, and to isolate and standardize the induced electromotive force signal and the capacitive displacement current signal to obtain a preprocessed signal; wherein the induced electromotive force signal is generated in the reactance branch and the capacitive displacement current signal is generated in the capacitor branch. The signal decomposition module is configured to perform a fast Fourier transform on the preprocessed signal to decouple the fundamental component and harmonic components, and generate a frequency domain feature decomposition result. The function construction module is configured to analyze the differences in amplitude-frequency and phase-frequency characteristics of the reactance channel and the capacitor channel based on the frequency domain eigenvalue decomposition results, so as to construct a frequency-varying transfer function matrix for bidirectional error compensation. The signal compensation module is configured to load the frequency-varying transfer function matrix into the real-time signal processor to compensate the fundamental and harmonic components of the input induced electromotive force signal and capacitive displacement current signal, and generate a compensated reactance signal and a compensated capacitance signal. The index determination module is configured to perform complex plane vector synthesis of the compensated reactance signal and the compensated capacitance signal within a measurement cycle, and calculate the confidence index. The result output module is configured to adjust the weighting factors of the two signals in the fusion according to the confidence index and output the fused voltage measurement value.

9. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the dual measurement method for fusion reactance and capacitor as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the dual-measurement method for measuring fused reactance and capacitor as described in any one of claims 1 to 7.

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