Electric network harmonic frequency spectrum interpolation correction analytical method

Abstract

The invention belongs to the technical field of digital signal processing, in particular relates to a harmonic spectrum interpolation correction analysis method of a power network. The method provides the method for using the interpolation correction method to eliminate the phase change to further correct the spectrum through the analysis of the reasons of the spectrum leakage. The method utilizes the windowed interpolation spectrum analysis method to estimate the changing phase and utilizes the estimated result to construct a corresponding anti-phase function, the constructed anti-phase function is multiplied by a discrete sequence which is generated by Fourier inverse transformation in a time domain, and the multiplied discrete new sequence is carried out the Fourier transformation again, thereby achieving the spectrum correction effect. The analysis, the simulation and the experiment results can show that the method effectively improves the precision of the harmonic spectrum analysis of the power network during the non-synchronous sampling simultaneously when verifying the effectiveness of the method of the invention.

Description

technical field [0001] The invention belongs to the technical field of digital signal processing, and in particular relates to an interpolation correction analysis method for a non-synchronously sampled power grid harmonic spectrum. Background technique [0002] In today's many scientific disciplines, it is a commonly used basic method to analyze the sampled power grid signal from the frequency spectrum of power grid harmonics. Usually, this process is completed by discrete Fourier transform DFT, and the fast algorithm FFT of DFT improves the efficiency of this process. However, the sampling frequency and the length (or time) of the truncated data need to be carefully selected. If there is a slight deviation, the well-known spectrum aliasing and spectrum leakage will occur. [1] . We know that the spectral aliasing problem can be solved by increasing the sampling frequency and anti-aliasing filter. However, the data to be processed always has a finite length of discrete se...

AI Technical Summary

Problems solved by technology

To understand the signal period, it is necessary to measure, and measurement errors are inevitable. In this sense, synchronous sampling is impossible in practice.

[0005] 2. The deviation of the hardware synchronization link, which is mainly caused by the uncertainty of the zero-crossing point in the zero-crossing comparator in the synchronization link

The window interpolation method improves the accuracy of the signal spectrum to a certain extent, but there is still spectrum leakage

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