Noise suppression in PD signal based on Prony time series energy spectrum

IET Science, Measurement & Technology

Yuhang He¹  Dakun Zhang¹  Chunxiao Yu²  Qin Shu³  Chang Wang³ 

[1] Chengdu Ruichi Technology Co., Ltd. Chengdu China;Southwest Institute of Technical Physics Chengdu China;The College of Electrical Engineering Sichuan University ChengDu China;

关键词: Probability theory, stochastic processes, and statistics;    Numerical approximation and analysis;    Electrical instruments and techniques;    Interpolation and function approximation (numerical analysis);    Dielectric breakdown and discharges;    Charge measurement;   

DOI  :  10.1049/smt2.12076

来源: DOAJ

【 摘 要 】

Abstract On‐line partial discharge (PD) monitoring is related to the safe and stable operation of power grid. However, the measured signal is inevitably affected by noise. Among a variety of noises, white noise is the most difficult to suppress and ubiquitous. It mainly determines the Cramer–Rao lower bound that cannot be crossed by all methods. This article proposes the Prony time‐series energy spectrum method to suppress white noise in a low signal‐to‐noise ratio environment. This method is divided into two parts: First, Prony time series energy spectrum is used to detect whether there is PD signals in the measured signal. Then, based on the least square method, the PD signal is estimated with the Prony model. In data analysis, this method can suppress ‐10dB white noise, while other methods have performed poorly or even failed under the same conditions. In general, this method has excellent anti‐noise performance compared to several other algorithms.

【 授权许可】

Unknown