Abstract

Periodic narrowband signals and white noise are the main interferences in online detection and localization of cable partial discharge (PD), however, existing research has always focused on the white noise suppression only, which is not in line with the actual scene. A novel de-noising method for effectively extracting random PD pulse from complex and strong interferences is proposed in this paper and applied to PD localization. Firstly, an improved adaptive variational mode decomposition (AVMD) is used to decompose periodic narrowband interference, white noise, and PD signal into different intrinsic mode. According to the characteristic that the power of intrinsic mode component of periodic narrowband interference in the discrete Fourier transformation (DFT) power spectrum is much larger than that of PD and white noise, the periodic narrowband is removed out. In order to effectively filter out white noise, a scale adaptive wavelet packet decomposition method based on correlation coefficient is proposed, which decomposes the signal into high, middle, and low-frequency components. The components with low frequency, small amplitude are removed out as the white noise interference according to the threshold method, and the residual is the de-noising PD signal. Experimental results show that the proposed method can robustly suppress the interference of periodic narrowband signal and white noise, and effectively preserve the essential characteristics of the real PD signal. In the multi-sensor travelling wave based localization system of cable PD source using time-varying kurtosis, accurate estimation of first arrival time of PD pulse can be achieved by the de-noising results.

Highlights

  • Due to the advantage of high reliability, less space demand, and beautiful appearance, power cables have been widely used in power grid of city, railway, offshore wind system, etc. [1]

  • In order to effectively filter out white noise, a scale adaptive wavelet packet decomposition method based on correlation coefficient is proposed, which decomposes the signal into high, middle, and low-frequency components

  • The components with low frequency, are removed amplitude are removed out as the white noise interference according small to the amplitude threshold method, and out as the white noise interference according to the threshold method, and the residual is the de-noising the residual is the de-noising partial discharge (PD) signal

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Summary

Introduction

Due to the advantage of high reliability, less space demand, and beautiful appearance, power cables have been widely used in power grid of city, railway, offshore wind system, etc. [1]. Insulation faults directly affect the safe operation of the cable grid. Online partial discharge (PD) detection and localization is considered as the most effective means of detecting the insulation defects [2,3,4,5]. The electromagnetic coupling detection method, which uses a high-frequency current sensor (HFCT). To couple the electromagnetic signal generated by the PD pulse without any damage of the cable body [6,7,8], is currently the most commonly used cable PD detection method. The multi-sensor travelling wave method, which can effectively eliminate the influence of wave velocity uncertainty [9,10,11], is a novel travelling wave based localization method using the coupled PD current pulse. The environment in which the cable is laid is complicated, and the real PD signal detected by the

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