Ultrahigh-order harmonic signal processing method and device in power supply system and electronic equipment

Abstract

The invention discloses an ultra-high-order harmonic signal processing method and device in a power supply system and electronic equipment. Relates to the field of intelligent power grids, and the method comprises the steps: obtaining an ultra-high-order harmonic signal in a power supply system, modeling the ultra-high-order harmonic signal into a discrete sampling signal, and enabling the ultra-high-order harmonic signal to be a harmonic signal of which the frequency is greater than a preset frequency threshold value; performing windowing processing and truncation processing on the discrete sampling signal to obtain a first signal frequency spectrum; fourier transform processing is carried out on the first signal frequency spectrum, initial harmonic parameters of the ultra-high-order harmonic signal are obtained, and the initial harmonic parameters comprise the initial amplitude, the initial frequency and the initial phase of the ultra-high-order harmonic signal; and correcting the initial harmonic parameter of the ultra-high-order harmonic signal to obtain a target harmonic parameter of the ultra-high-order harmonic signal. According to the invention, the technical problems of difficult processing and low accuracy of ultra-high harmonic signals in a power supply system are solved.

Description

Technical Field

[0001] The present invention relates to the field of smart grids, and in particular to a method, device and electronic equipment for processing ultra-high harmonic signals in a power supply system. Background Art

[0002] In low-voltage power supply systems, increased radiation from power line communications and power electronic converters has led to the generation of a large number of ultra-high harmonics in the frequency range of 2 to 150 kilohertz (kHz). With the widespread adoption of new power electronic devices such as insulated gate bipolar transistors (IGBTs) and gate turn-off transistors (GTOs), the switching frequencies of high-frequency power electronic devices have continued to increase, injecting a large number of ultra-high harmonics into the power grid. Photovoltaic inverters and electric vehicle chargers are typical sources of ultra-high harmonics. The harmonic currents of photovoltaic inverters are primarily concentrated in the 2-20 kHz frequency band, while electric vehicle chargers generate a large amount of harmonic currents in the 3-29 kHz band. Therefore, the International Electrotechnical Commission (IEC) standard 61000-2-2 specifies the emission levels of ultra-high harmonics at different frequencies in low-voltage power supply systems. Accurately measuring these ultra-high harmonics is crucial to determining whether system signal transmission meets the standard.

[0003] In related technologies, power quality analysis directly relies on techniques such as discrete Fourier transform (DFT) to estimate the frequency, amplitude, and phase of harmonic signals. However, DFT has inherent limitations when processing high-frequency signals. In particular, when the frequency of the signal component is not at the fundamental frequency of the DFT spectrum, spectrum leakage and fence effects will occur, resulting in inaccurate harmonic parameter measurements. In addition, for signals such as ultra-high harmonics with close frequencies and potentially small amplitudes, simply calculating the spectrum and related parameters through DFT often cannot provide measurement results with sufficient accuracy, resulting in the problem of difficult and accurate low-precision processing of ultra-high harmonic signals in power supply systems in related technologies.

[0004] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0005] The embodiments of the present invention provide a method, device and electronic equipment for processing ultra-high harmonic signals in a power supply system, so as to at least solve the technical problem that ultra-high harmonic signals in the power supply system are difficult to process and accurately determine.

[0006] According to one aspect of an embodiment of the present invention, a method for processing ultra-high-order harmonic signals in a power supply system is provided, including: obtaining an ultra-high-order harmonic signal in the power supply system, modeling the ultra-high-order harmonic signal as a discrete sampling signal, wherein the ultra-high-order harmonic signal is a harmonic signal having a frequency greater than a preset frequency threshold; performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high-order harmonic signal; and correcting the initial harmonic parameters of the ultra-high-order harmonic signal to obtain target harmonic parameters of the ultra-high-order harmonic signal.

[0007] According to another aspect of an embodiment of the present invention, a device for processing ultra-high-order harmonic signals in a power supply system is also provided, including: a signal acquisition module for acquiring ultra-high-order harmonic signals in the power supply system, and modeling the ultra-high-order harmonic signals as discrete sampling signals, wherein the ultra-high-order harmonic signals are harmonic signals having a frequency greater than a preset frequency threshold; a signal processing module for performing windowing and truncation processing on the discrete sampling signals to obtain a first signal spectrum; a spectrum conversion module for performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include the initial amplitude, initial frequency and initial phase of the ultra-high-order harmonic signal; a parameter correction module for correcting the initial harmonic parameters of the ultra-high-order harmonic signal to obtain target harmonic parameters of the ultra-high-order harmonic signal.

[0008] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided. The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded and executed by a processor for any one of the methods for processing ultra-high harmonic signals in a power supply system.

[0009] According to another aspect of an embodiment of the present invention, an electronic device is also provided, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement any one of the methods for processing ultra-high harmonic signals in a power supply system.

[0010] In an embodiment of the present invention, by acquiring an ultra-high-order harmonic signal in a power supply system, the ultra-high-order harmonic signal is modeled as a discrete sampling signal, wherein the ultra-high-order harmonic signal is a harmonic signal having a frequency greater than a preset frequency threshold; the discrete sampling signal is windowed and truncated to obtain a first signal spectrum; the first signal spectrum is Fourier transformed to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high-order harmonic signal; the initial harmonic parameters of the ultra-high-order harmonic signal are corrected to obtain target harmonic parameters of the ultra-high-order harmonic signal, thereby achieving the purpose of implementing signal preprocessing combining windowing, truncation, and Fourier transform, and subsequent accurate correction of harmonic parameters, thereby achieving the technical effect of improving the measurement accuracy and analysis accuracy of ultra-high-order harmonic signals, ensuring reliable evaluation of power quality, and thus solving the technical problem of difficult and accurate low-precision processing of ultra-high-order harmonic signals in power supply systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0012] Figure 1 is a flow chart of a method for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention;

[0013] Figure 2 is a flow chart of an optional method for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention;

[0014] Figure 3 is an optional test result comparison chart according to an embodiment of the present invention;

[0015] Figure 4 3 is a schematic diagram of a device for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0017] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] According to an embodiment of the present invention, an embodiment of a method for processing very high harmonic signals in a power supply system is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0019] Figure 1 FIG. 1 is a flow chart of a method for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0020] Step S102: acquiring a super-high harmonic signal in the power supply system, and modeling the super-high harmonic signal as a discrete sampling signal;

[0021] Optionally, the ultra-high harmonic signal is a harmonic signal with a frequency greater than a preset frequency threshold, for example, it can be a harmonic signal with a frequency between several thousand hertz and several megahertz. Use high-precision current and voltage sensors to monitor the current and voltage signals in the power supply system in real time. The sensor needs to have a sufficiently high sampling rate to ensure that harmonic signals in the range of several thousand hertz to hundreds of kilohertz can be captured. Discretely sampled signals can be analyzed using digital signal processing technology. Digital signal processing (DSP) methods can provide flexible, accurate and programmable signal analysis tools that can handle complex harmonic signals, especially in the detection and analysis of ultra-high harmonics. Through digital sampling and modeling, accurate recording of signals can be ensured, avoiding distortion and drift problems that may be encountered in analog signal processing, which is crucial for subsequent harmonic parameter estimation.

[0022] In an optional embodiment, the ultra-high harmonic signal is modeled as a discrete sampling signal, including: preprocessing the ultra-high harmonic signal to obtain a preprocessed signal, wherein the preprocessing includes at least low-pass filtering and noise suppression; and converting the preprocessed signal into a discrete sampling signal including multiple signal components.

[0023] Optionally, the collected ultra-high harmonic signal may contain a large amount of noise and interference signals. Therefore, preprocessing and filtering techniques, such as digital filtering or analog filtering, are required to remove unnecessary noise and low-frequency signals, retaining only signal components with frequencies above a preset frequency threshold. The preprocessed analog signal (i.e., the preprocessed signal) can be converted into a digital signal and discretely sampled using an analog-to-digital converter (ADC) to form a series of digital sample points. The sampling frequency can satisfy the Nyquist sampling theorem, that is, it must be at least twice the highest frequency component in the signal to avoid frequency aliasing and ensure complete capture of signal information. The sampled digital signal is represented as a discrete sampled signal, that is, a series of signal values arranged in a time series, which can be expressed in the form {x(n)}, where n is the index of the sampling point. This modeling process lays the foundation for subsequent signal processing steps, such as windowing, truncation, and spectral analysis.

[0024] Optionally, the discrete sampling signal x(n) of the ultra-high harmonic signal containing M signal components can be expressed as:

[0025]

[0026] Where M is the total number of signal components and i is the number of the signal component. i is the amplitude of the i-th signal component, f i is the frequency of the i-th signal component, is the phase of the i-th signal component. Δt is the sampling interval, and the sampling points are n=1,2,…,N-1.

[0027] Step S104, performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum;

[0028] Optionally, windowing is a signal preprocessing technology, which is mainly used to reduce spectrum leakage and Gibbs phenomenon in the discrete Fourier transform (DFT) process. In this embodiment, a window function is added to the discrete sampled signal to obtain a windowed signal sequence. Through windowing, the mutation of the signal at the truncation boundary can be effectively reduced, the interference in the spectrum analysis can be reduced, and the frequency resolution can be improved, especially for the ultra-high harmonic signals with dense frequencies. It has a significant improvement effect. Truncation processing is to limit the signal to a specific time window to match the periodic assumption of DFT. Since the signals in the power supply system are usually continuous signals, DFT requires the input signal to be a periodic signal of finite length, so the signal needs to be truncated.

[0029] Optionally, you can select a specific time period for signal truncation, for example, a few power frequency cycles, to ensure periodicity and consistency in spectrum analysis. Truncation not only helps improve frequency resolution but also reduces computational effort, making the analysis more efficient.

[0030] In an optional embodiment, the discrete sampling signal is subjected to windowing processing and truncation processing to obtain a first signal spectrum, including: using a Hamming window function to perform windowing processing on the discrete sampling signal to obtain a windowed processed signal; and truncating the windowed processed signal according to a preset signal length to obtain the first signal spectrum.

[0031] Optionally, the shape of the Hamming window function can reduce spectral leakage caused by signal truncation. When measuring ultra-high harmonics in a power system, the original discretely sampled signal is first windowed using a Hamming window function to generate a windowed signal. Windowing the signal using the Hamming window function allows the signal to decay smoothly at both ends, reducing spectral leakage in the frequency domain caused by signal truncation. After windowing, the signal needs to be truncated according to a preset signal length to accommodate subsequent spectrum analysis algorithms (such as the fast Fourier transform (FFT)). The truncation length is typically selected based on the signal's frequency domain characteristics, such as the harmonic frequency distribution and the sampling rate. Truncation ensures that the signal within the analysis window is self-contained, avoiding periodic continuation effects and reducing fence effects caused by non-periodic signal truncation. The windowed and truncated signal is then passed through a fast Fourier transform (FFT) algorithm to obtain a frequency domain representation of the signal, namely the first signal spectrum. This first signal spectrum provides a preliminary frequency component analysis of the signal, including preliminary amplitude, frequency, and phase information for each harmonic component. Using a Hamming window function and a preset signal length for windowing and truncation can address inherent issues with the discrete Fourier transform when processing non-periodic signals, such as spectral leakage and the fence effect. These preprocessing steps can reduce spectrum analysis errors and provide more accurate spectrum data for subsequent spectral line fitting and parameter correction processes. This is crucial for the accurate analysis and measurement of high-frequency harmonic signals in power supply systems, especially when processing ultra-high harmonics (frequencies typically ranging from 2kHz to 150kHz). It can more effectively capture the details of these signals, improve the overall accuracy and reliability of the measurement system, and ensure accurate assessment of the power quality of the power system.

[0032] Optionally, the sampling sequence {x(n)} can be windowed and truncated with a window function {w(n)} of length N to obtain a new sequence x W (n). After Fourier transform, windowing and truncation are performed to obtain the spectrum corresponding to the sampling sequence, i.e. the first signal spectrum X W (kΔf):

[0033]

[0034] Wherein, the sequence number k = 0, 1, 2, ..., N-1, Δf is the discrete frequency interval, Δf = f s / N, A is the amplitude of the signal component, function W(·) is the window function, f0 is the frequency value at the peak frequency point, k0 is the spectral line number corresponding to the peak frequency point f0, N is the window function length / total number of sampling points, is the phase of the component corresponding to the peak frequency f0.

[0035] Step S106, performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high harmonic signal;

[0036] Optionally, the Fourier transform is a mathematical tool used to convert a time domain signal into a frequency domain signal, that is, to reveal the amplitude and phase information of different frequency components in the signal. In an embodiment, a discrete Fourier transform (DFT) is used, which is suitable for performing spectral analysis on discrete sampled signals. The calculation result of the DFT can provide a spectral representation of the signal, that is, the amplitude and phase values of the signal at different frequency points. After the signal is windowed and truncated, its spectrum will be further transformed by the DFT to obtain the frequency domain expression of the first signal spectrum. This frequency domain representation contains information about all signal components in the power supply system, including fundamental and harmonic signals, and in particular, a preliminary spectral description of ultra-high harmonic signals with a frequency greater than a preset threshold. After the Fourier transform, the peaks of each frequency component can be identified from the first signal spectrum, and these peaks correspond to the frequency points of the harmonic signals. By analyzing these peaks, the initial amplitude, initial frequency and initial phase parameters of the harmonic signal can be obtained. In the power supply system, these parameters are important indicators for evaluating power quality and performing system maintenance.

[0037] The initial amplitude represents the strength or magnitude of the ultra-high harmonic signal at a specific frequency, expressed in units of voltage or current. In the spectrum, the vertical height of the peak represents the initial amplitude of the signal. The initial frequency determines the location and properties of the ultra-high harmonic signal, while the horizontal position of the peak in the spectrum indicates the initial frequency of the signal. The initial phase reflects the phase difference between ultra-high harmonic signal components and is crucial for understanding the signal's composition and the presence of phase distortion in the power supply system. The Fourier transform not only provides amplitude information but also the phase angle of the signal components, thereby determining the initial phase.

[0038] Step S106 not only reveals the frequency components present in the power supply system, but also provides a preliminary estimate of their strength and phase relationships, providing foundational data for subsequent signal analysis and power supply system evaluation. The initial harmonic parameters obtained through DFT, combined with subsequent correction steps, enable more accurate monitoring and analysis of power quality within the power supply system, particularly for hard-to-capture ultra-high-order harmonic signals. This provides a scientific basis for maintaining power system stability and improving power quality.

[0039] Step S108 , correcting the initial harmonic parameters of the ultra-high-order harmonic signal to obtain target harmonic parameters of the ultra-high-order harmonic signal.

[0040] It should be noted that the initial harmonic parameters obtained based on the preliminary analysis of the first signal spectrum are preliminary, uncorrected estimates. Due to the DFT fence effect and spectrum leakage, these parameters may not be completely accurate. This is especially true when processing high-frequency, low-amplitude, ultra-high-order harmonic signals, which can lead to deviations in frequency and amplitude estimates. Therefore, by correcting these initial parameters, more accurate target harmonic parameters can be obtained, ensuring the reliability of power quality monitoring in the power supply system.

[0041] In an optional embodiment, the initial harmonic parameters of the ultra-high-order harmonic signal are corrected to obtain the target harmonic parameters of the ultra-high-order harmonic signal, including: performing spectral line fitting on the first signal spectrum to generate a fitting function; based on the fitting function, correcting the initial amplitude and initial phase to obtain the target frequency and target phase; based on the target frequency and target phase, obtaining the second signal spectrum; based on the second signal spectrum, correcting the initial amplitude to obtain the target amplitude, wherein the target harmonic parameters include the target frequency, target amplitude and target phase.

[0042] Optionally, for each detected ultra-high-order harmonic component in the initially calculated first signal spectrum, spectral line fitting is performed. This process involves mathematically fitting the spectral data of the peak frequency and its adjacent frequency points to generate a fitting function that describes the signal's spectral characteristics. The generation of this fitting function is based on analysis and mathematical modeling of the spectral data. It can more accurately reflect the signal's true frequency characteristics and overcome the fence effect and spectrum leakage issues of the discrete Fourier transform. Based on the generated fitting function, the initially calculated initial frequency and initial phase can be corrected. Frequency correction involves polynomial approximation using the inverse function of the fitting function to obtain a more accurate target frequency. Phase correction is performed based on the corrected target frequency to ensure accurate correspondence between phase and frequency information. This correction process improves the accuracy of harmonic parameter estimation and is particularly important for ultra-high-order harmonic signals with dense frequency density and small amplitudes. After frequency and phase correction, a new signal spectrum, namely the second signal spectrum, is generated based on the corrected parameters. This spectrum more accurately reflects the signal's true frequency components and phase relationships, providing a more precise basis for subsequent amplitude correction. Based on the second signal spectrum, amplitude correction is performed to ensure that the estimation of signal strength also reaches high accuracy.

[0043] Through this correction process, the target harmonic parameters ultimately obtained include target frequency, target amplitude, and target phase. These parameters are closer to the true properties of the signal, thereby improving the accuracy of harmonic measurement. By introducing spectral line fitting and parameter correction steps, the accuracy of harmonic parameter estimation can be further improved based on the initial calculation, thereby better meeting the high requirements of power systems for power quality monitoring and analysis. It provides power engineers and system maintenance personnel with precise harmonic signal information, helping them make more accurate decisions and ensure stable operation of the power system and optimized power quality.

[0044] In an optional embodiment, spectral line fitting is performed on the first signal spectrum to generate a fitting function, including: determining a first peak frequency point in the first signal spectrum, wherein the first peak frequency point is used to indicate the frequency point with the largest amplitude in the first signal spectrum; based on the initial amplitude, initial frequency and initial phase, polynomial fitting is performed on the spectral lines on the left and right sides of the first peak frequency point to generate a fitting function.

[0045] Optionally, in the preliminary spectrum analysis results, that is, in the first signal spectrum, it is necessary to first determine the peak frequency point, that is, the frequency point with the largest amplitude. This peak frequency point can indicate the preliminary frequency position of a harmonic component in the signal, and is the basis for subsequent parameter correction. The detection of the peak frequency point can be achieved by finding the maximum amplitude in the spectrum, and the frequency corresponding to this maximum amplitude is the preliminary estimated harmonic frequency. After determining the first peak frequency point, based on the initial amplitude, initial frequency and initial phase, the spectrum lines on both sides of this peak frequency point are polynomially fitted to generate a fitting function. Polynomial fitting is a mathematical method that can more accurately describe the spectral characteristics of the signal, especially the spectral shape near the peak frequency point, by constructing a polynomial model. Through the fitting process, a function can be generated that can describe not only the peak frequency point, but also the spectral behavior of its adjacent frequency points, thereby providing a more precise harmonic frequency estimate.

[0046] Optionally, the polynomial fitting can be based on the least squares method or other optimization algorithms, by adjusting the coefficients of the polynomial so that the fitting function can best match the spectral data on both sides of the first peak frequency point. This process comprehensively considers the curve shape of the spectrum near the peak point, and captures subtle changes in the spectrum through a mathematical model, thereby obtaining a fitting function that can more accurately reflect the true frequency characteristics of the signal. The generated fitting function is used in subsequent frequency and phase correction steps. By analyzing the fitting function, a more accurate target frequency and target phase can be obtained to overcome the limitations of the discrete Fourier transform in processing non-fence frequency signals. This correction is particularly important for processing ultra-high harmonic signals, because the frequencies of these signals often deviate from the commonly used fence frequencies, resulting in errors in the initial parameter estimates.

[0047] In this embodiment, by accurately determining the first peak frequency point and performing polynomial fitting on the spectrum lines adjacent to the frequency point based on the initial harmonic parameters, a fitting function can be generated. This function can more accurately reflect the true frequency characteristics of the signal, provide an important model basis for subsequent frequency, phase and amplitude corrections, and ensure accurate measurement and analysis of complex high-frequency signals in the power supply system.

[0048] Optionally, assume that the frequency points on the left and right sides of the peak frequency f0 are numbered k1 and k2, and the amplitudes of these two spectral lines are y1=|X W (k1Δf)| and y2=|X W (k2Δf)|. Now we can get the fitting function:

[0049]

[0050] Among them, β represents the function value corresponding to the fitting function, α is an auxiliary parameter, α=k0-k1-0.5, and its value range is α∈(-0.5,0.5).

[0051] In an optional embodiment, based on the fitting function, the initial amplitude and the initial phase are corrected to obtain the target frequency and the target phase, including: determining the inverse function of the fitting function; and correcting the initial amplitude and the initial phase based on the inverse function to obtain the target frequency and the target phase.

[0052] Optionally, after performing a polynomial fit on the peak frequency points in the first signal spectrum to generate a fitting function, the next step is to determine the inverse function of the fitting function. The inverse function is determined based on the mathematical properties and parameters of the fitting function, and its purpose is to correct the frequency and phase of the harmonic signal through inverse calculation. In the case of polynomial fitting, the inverse function can be obtained through polynomial solutions or numerical methods, providing a mathematical model for subsequent parameter correction. Frequency correction is based on the inverse function of the fitting function. In the discrete Fourier transform, due to the fence effect and spectral leakage, the initially calculated harmonic frequency may deviate from the true frequency of the signal. By inputting the preliminary frequency into the inverse function, a corrected frequency value can be obtained that is closer to the actual frequency of the signal. The purpose of frequency correction is to eliminate the inherent frequency estimation error of the DFT and improve the accuracy of harmonic frequency measurement. This is particularly important for the accurate measurement of ultra-high harmonic signals. Phase correction also relies on the inverse function of the fitting function. Phase information can reflect the phase difference between signal components and is crucial for understanding the signal composition and whether there is phase distortion in the power supply system. By using the inverse function, a more accurate target phase can be calculated based on the corrected frequency and preliminary phase information. The purpose of phase correction is to eliminate the phase error caused by inaccurate preliminary frequency estimation and ensure accurate measurement of the signal phase characteristics. The frequency and phase correction process is based on an in-depth analysis of the fitting function. By calculating the inverse function, a more accurate target frequency and target phase can be obtained. This correction process can compensate for the frequency and phase estimation deviations caused by the DFT fence effect and spectrum leakage, ensuring the accuracy of harmonic parameter measurement. For power quality monitoring in power supply systems, this correction step can help more accurately identify and analyze ultra-high harmonic signals, improving the operating efficiency and power quality of the power system.

[0053] Optionally, when the total number of sampling points is large, the above fitting function is recorded as β = t(α), and its inverse function α = t -1 By performing polynomial approximation on (β), we can obtain the fitting polynomial h(α) of α, thereby obtaining the corrected frequency and phase of the signal component:

[0054] f0=(k1+α+0.5)Δf

[0055]

[0056] Among them, f0 represents the corrected frequency (i.e., target frequency), represents the corrected phase (i.e., target phase), function arg[·] represents the angle, k s is the frequency point number, s=1,2.

[0057] In an optional embodiment, the initial amplitude is corrected based on the second signal spectrum to obtain a target amplitude, including: determining a second peak frequency point in the second signal spectrum, wherein the second peak frequency point is used to indicate a frequency point with the largest amplitude in the second signal spectrum; performing a weighted average on the amplitudes of the spectrum lines on the left and right sides of the second peak frequency point to obtain a weighted average result; and based on the weighted average result, correcting the initial amplitude to obtain a target amplitude.

[0058] Optionally, after performing a preliminary Fourier transform and parameter correction on the first signal spectrum, a new spectral representation, namely the second signal spectrum, is generated. This spectrum contains the corrected harmonic frequency and phase information. After frequency and phase correction, the second signal spectrum more accurately reflects the true frequency components of the harmonic signal. By identifying the frequency point with the largest amplitude in the second signal spectrum, namely the second peak frequency point, the frequency position of a particular harmonic can be located, which provides the basis for correcting the amplitude. To correct for amplitude errors caused by preliminary parameter estimates and inherent limitations of the DFT, a weighted average is performed on the amplitudes of the spectral lines to the left and right of the second peak frequency point. This method considers the energy distribution of the signal spectrum near the peak frequency point, and the weighted average can better reflect the actual strength of the harmonic signal. The weights can be selected based on the distance from the peak frequency point, with spectral lines closer to the peak frequency point receiving larger weights, thereby ensuring that the corrected amplitude is closer to the true amplitude of the signal. Based on the results of the weighted average, the initial amplitude obtained from the preliminary calculation is corrected to obtain the target amplitude. This correction process takes into account the distribution characteristics of the signal's spectral energy. Through weighted averaging, it more accurately reflects the actual strength of the harmonic signal, eliminating potential errors in the initial amplitude estimation. The target amplitude is closer to the true nature of the signal, facilitating accurate monitoring and analysis of power quality in power supply systems.

[0059] The above correction steps can improve the accuracy of harmonic signal amplitude measurement in power supply systems. It should be noted that in power systems, accurately measuring the amplitude of harmonics is crucial for evaluating power quality, monitoring equipment operating status, and ensuring system compliance. The amplitude measurement of very high-order harmonic signals is particularly challenging because their high frequency and potentially small amplitude make them susceptible to the inherent limitations of DFT. Therefore, by correcting the amplitude using weighted average, the measurement accuracy of high-frequency harmonic signals in power supply systems can be significantly improved, helping to promptly identify and resolve power quality issues, ensuring stable operation of the power system and optimizing power quality.

[0060] Optionally, a weighted average is performed on the amplitudes of the spectrum lines k1 and k2 on the left and right sides of the second peak frequency point to obtain a corrected amplitude of the signal component:

[0061] A=N -1 (y1+y2)h(α)

[0062] Wherein, A represents the corrected amplitude (ie, the target amplitude).

[0063] Through the above steps S102 to S108, the purpose of implementing signal preprocessing combining windowing, truncation and Fourier transform, and the subsequent accurate correction of harmonic parameters can be achieved, thereby achieving the technical effect of improving the measurement accuracy and analysis accuracy of ultra-high harmonic signals, ensuring the reliable evaluation of power quality, and then solving the technical problem of difficult and accurate low-precision processing of ultra-high harmonic signals in the power supply system. Specifically, by obtaining the ultra-high harmonic signals in the power supply system and converting them into discrete sampling signals for mathematical modeling. Subsequently, the discrete sampling signals are windowed and truncated to reduce spectrum leakage and Gibbs effect, and a first signal spectrum is obtained. Then, the first signal spectrum is processed by Fourier transform to extract the initial amplitude, initial frequency and initial phase of the signal, that is, the initial harmonic parameters. Finally, these initial harmonic parameters are corrected to eliminate the errors caused by windowing and truncation, and more accurate target harmonic parameters are obtained, thereby improving the measurement accuracy of the harmonic signal and the accuracy of power quality analysis.

[0064] Based on the above embodiments and optional embodiments, the present invention proposes an optional implementation mode: Figure 2 FIG. 1 is a flow chart of an optional method for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention. Figure 2 As shown, the method includes:

[0065] S1. Original signal modeling: Modeling the discrete sampling form x(n) of the ultra-high-order harmonic signal.

[0066] S2. Sampling signal processing: Windowing and truncating the above sampling sequence {x(n)}, and performing Fourier transform to obtain the initial amplitude, initial frequency, and initial phase of the signal component for the first calculation.

[0067] S3. Spectrum line fitting: Find the peak frequency point in the above spectrum, fit the amplitudes corresponding to the frequency points on its left and right sides, and obtain the fitting function β=t(α), where α is an auxiliary parameter.

[0068] S4. Frequency and phase correction: By performing polynomial approximation on the inverse function of the above fitting function, the fitting polynomial h(α) of α can be obtained, thereby obtaining the corrected frequency (i.e., target frequency) and corrected phase (i.e., target phase) of the signal component.

[0069] S5. Amplitude correction: perform weighted averaging on the amplitudes of the spectrum lines on the left and right sides of the peak frequency point to obtain the corrected amplitude of the signal component (i.e., the target amplitude).

[0070] In this embodiment, a windowed interpolation algorithm is used to correct the amplitude, frequency, and phase of the initial rapid calculation results of the ultra-high harmonics. While maintaining a low calculation time, the estimation accuracy of the amplitude, frequency, and phase of the ultra-high harmonic signal components can be significantly improved.

[0071] To highlight the detection performance of the algorithm, this embodiment selects the IEC standard 61000-4-30 recommended algorithm (IEC), Wavelet Transform (WT), and Orthogonal Matching Pursuit with Compressed Sensing (OMPCS) as comparison algorithms and compares them with the method of this embodiment. Assuming the sampling rate is 409.6kHz and the sampling window length is set to 10 power frequency cycles. The algorithm performance is evaluated using frequency error, amplitude error, and phase error. The test signals selected in this embodiment are as follows:

[0072]

[0073] Among them, A m , f m and are the amplitude, frequency and phase of the signal components contained in the ultra-high harmonics. M is the total number of signal components, and m is the serial number of the signal component. s The fundamental frequency of the test signal is set to 50.1 Hz and the amplitude is 380 V.

[0074] Figure 3 This is an optional test result comparison diagram according to an embodiment of the present invention. It can be seen that whether it is phase error, amplitude error or frequency error, the method of this embodiment (in Figure 3 The value (marked by A) is smaller than that of the IEC algorithm, the WT method and the OMPCS method, which also shows that the method of this embodiment has higher estimation accuracy than other methods.

[0075] This embodiment also provides a device for processing ultra-high harmonic signals in a power supply system. The device is used to implement the above-mentioned embodiments and preferred implementations, and details already described will not be repeated. As used below, the terms "module" and "device" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0076] According to an embodiment of the present invention, there is also provided an embodiment of a device for implementing the above-mentioned method for processing ultra-high harmonic signals in a power supply system. Figure 4FIG. 1 is a structural diagram of a device for processing ultra-high harmonic signals in a power supply system according to an embodiment of the present invention. Figure 4 As shown, the ultra-high harmonic signal processing device in the power supply system includes: a signal acquisition module 400, a signal processing module 402, a spectrum conversion module 404, and a parameter correction module 406, wherein:

[0077] The signal acquisition module 400 is used to acquire ultra-high harmonic signals in the power supply system and model the ultra-high harmonic signals as discrete sampling signals, wherein the ultra-high harmonic signals are harmonic signals with a frequency greater than a preset frequency threshold;

[0078] The signal processing module 402 is connected to the signal acquisition module 400 and is used to perform windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum;

[0079] A spectrum conversion module 404, connected to the signal processing module 402, is configured to perform Fourier transform processing on the spectrum of the first signal to obtain initial harmonic parameters of the ultra-high harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high harmonic signal;

[0080] The parameter correction module 406 is connected to the spectrum conversion module 404 and is used to correct the initial harmonic parameters of the ultra-high-order harmonic signal to obtain the target harmonic parameters of the ultra-high-order harmonic signal.

[0081] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0082] It should be noted that the signal acquisition module 400, signal processing module 402, spectrum conversion module 404, and parameter correction module 406 correspond to steps S102 to S108 in the embodiment. The examples and application scenarios implemented by these modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules, as part of the device, can be run on a computer terminal.

[0083] It should be noted that the optional or preferred implementation of this embodiment can be found in the relevant description in the embodiment, which will not be repeated here.

[0084] The ultra-high harmonic signal processing device in the above-mentioned power supply system may further include a processor and a memory. The above-mentioned signal acquisition module 400, signal processing module 402, spectrum conversion module 404, parameter correction module 406, etc. are all stored in the memory as program modules, and the processor executes the above-mentioned program modules stored in the memory to realize the corresponding functions.

[0085] The processor includes a core, which retrieves corresponding program modules from memory. There can be one or more cores. Memory may include non-permanent memory in a computer-readable medium, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory includes at least one memory chip.

[0086] According to an embodiment of the present application, an embodiment of a non-volatile storage medium is also provided. Optionally, in this embodiment, the non-volatile storage medium includes a stored program, wherein, when the program is executed, the device containing the non-volatile storage medium is controlled to execute any of the above-mentioned methods for processing ultra-high harmonic signals in a power supply system.

[0087] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group, and the non-volatile storage medium includes a stored program.

[0088] Optionally, when the program is running, the device where the non-volatile storage medium is located is controlled to perform the following functions: obtain an ultra-high-order harmonic signal in the power supply system, and model the ultra-high-order harmonic signal as a discrete sampling signal, wherein the ultra-high-order harmonic signal is a harmonic signal with a frequency greater than a preset frequency threshold; perform windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; perform Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include the initial amplitude, initial frequency and initial phase of the ultra-high-order harmonic signal; and correct the initial harmonic parameters of the ultra-high-order harmonic signal to obtain the target harmonic parameters of the ultra-high-order harmonic signal.

[0089] According to an embodiment of the present application, an embodiment of a processor is further provided. Optionally, in this embodiment, the processor is used to run a program, wherein when the program is run, any of the above-mentioned methods for processing ultra-high harmonic signals in a power supply system is executed.

[0090] According to an embodiment of the present application, an embodiment of a computer program product is also provided. When executed on a data processing device, it is suitable for executing a program that initializes any of the steps of the above-mentioned method for processing ultra-high harmonic signals in a power supply system.

[0091] Optionally, the above-mentioned computer program product, when executed on a data processing device, is suitable for executing an initialization program having the following method steps: obtaining an ultra-high-order harmonic signal in the power supply system, modeling the ultra-high-order harmonic signal as a discrete sampling signal, wherein the ultra-high-order harmonic signal is a harmonic signal with a frequency greater than a preset frequency threshold; performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include the initial amplitude, initial frequency and initial phase of the ultra-high-order harmonic signal; and correcting the initial harmonic parameters of the ultra-high-order harmonic signal to obtain target harmonic parameters of the ultra-high-order harmonic signal.

[0092] An embodiment of the present invention provides an electronic device, which includes a processor, a memory, and a program stored in the memory and capable of running on the processor. When the processor executes the program, the following steps are implemented: obtaining an ultra-high-order harmonic signal in a power supply system, modeling the ultra-high-order harmonic signal as a discrete sampling signal, wherein the ultra-high-order harmonic signal is a harmonic signal with a frequency greater than a preset frequency threshold; performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high-order harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high-order harmonic signal; and correcting the initial harmonic parameters of the ultra-high-order harmonic signal to obtain target harmonic parameters of the ultra-high-order harmonic signal.

[0093] The above sequence of the embodiments of the present invention is for description only and does not represent the superiority or inferiority of the embodiments.

[0094] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the above modules can be a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, modules or indirect coupling or communication connection of modules, which can be electrical or other forms.

[0096] The modules described above as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0097] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing module, or each module may exist physically separately, or two or more modules may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or software functional modules.

[0098] If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable non-volatile storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a non-volatile storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned non-volatile storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, and other media that can store program codes.

[0099] The above are only preferred embodiments of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for processing ultra-high harmonic signals in a power supply system, characterized in that: include: Acquire an ultra-high harmonic signal in the power supply system, and model the ultra-high harmonic signal as a discrete sampling signal, wherein the ultra-high harmonic signal is a harmonic signal having a frequency greater than a preset frequency threshold; Performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; Performing Fourier transform processing on the first signal spectrum to obtain initial harmonic parameters of the ultra-high harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high harmonic signal; The initial harmonic parameters of the ultra-high-order harmonic signal are corrected to obtain target harmonic parameters of the ultra-high-order harmonic signal.

2. The method according to claim 1, characterized in that The step of correcting the initial harmonic parameters of the ultra-high harmonic signal to obtain target harmonic parameters of the ultra-high harmonic signal includes: Performing spectral line fitting on the first signal spectrum to generate a fitting function; Based on the fitting function, the initial amplitude and the initial phase are corrected to obtain a target frequency and a target phase; obtaining a second signal spectrum based on the target frequency and the target phase; Based on the second signal spectrum, the initial amplitude is corrected to obtain a target amplitude, wherein the target harmonic parameters include the target frequency, the target amplitude, and the target phase.

3. The method according to claim 2, characterized in that The performing spectral line fitting on the first signal spectrum to generate a fitting function includes: Determining a first peak frequency point in the first signal spectrum, wherein the first peak frequency point is used to indicate a frequency point with a maximum amplitude in the first signal spectrum; Based on the initial amplitude, the initial frequency, and the initial phase, polynomial fitting is performed on the spectrum lines on the left and right sides of the first peak frequency point to generate the fitting function.

4. The method according to claim 2, characterized in that The step of correcting the initial amplitude and the initial phase based on the fitting function to obtain a target frequency and a target phase includes: determining an inverse function of the fitting function; The initial amplitude and the initial phase are corrected based on the inverse function to obtain the target frequency and the target phase.

5. The method according to claim 2, characterized in that The correcting the initial amplitude based on the second signal spectrum to obtain a target amplitude includes: Determine a second peak frequency point in the second signal spectrum, wherein the second peak frequency point is used to indicate a frequency point with a maximum amplitude in the second signal spectrum; Performing a weighted average on the amplitudes of the spectrum lines on the left and right sides of the second peak frequency point to obtain a weighted average result; Based on the weighted average result, the initial amplitude is corrected to obtain the target amplitude.

6. The method according to claim 1, characterized in that The performing windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum includes: Performing windowing processing on the discrete sampling signal using a Hamming window function to obtain a windowed signal; The windowed signal is truncated according to a preset signal length to obtain the first signal spectrum.

7. The method according to any one of claims 1 to 6, characterized in that Modeling the ultra-high harmonic signal as a discrete sampling signal includes: Preprocessing the ultra-high harmonic signal to obtain a preprocessed signal, wherein the preprocessing includes at least low-pass filtering and noise suppression; The pre-processed signal is converted into the discrete sampled signal comprising a plurality of signal components.

8. A device for processing ultra-high harmonic signals in a power supply system, characterized in that: include: A signal acquisition module is used to acquire an ultra-high harmonic signal in the power supply system and model the ultra-high harmonic signal as a discrete sampling signal, wherein the ultra-high harmonic signal is a harmonic signal with a frequency greater than a preset frequency threshold; a signal processing module, configured to perform windowing and truncation processing on the discrete sampling signal to obtain a first signal spectrum; a spectrum conversion module, configured to perform Fourier transform processing on the spectrum of the first signal to obtain initial harmonic parameters of the ultra-high harmonic signal, wherein the initial harmonic parameters include an initial amplitude, an initial frequency, and an initial phase of the ultra-high harmonic signal; The parameter correction module is used to correct the initial harmonic parameters of the ultra-high-order harmonic signal to obtain the target harmonic parameters of the ultra-high-order harmonic signal.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executed by the method for processing ultra-high harmonic signals in a power supply system according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The method comprises one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for processing ultra-high harmonic signals in a power supply system according to any one of claims 1 to 7.

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