基于最大似然估计的变电站特高频局部放电定向方法

A Substation UHF Partial Discharge Directional of Arrival Estimation Method Based on Maximum Likelihood Estimation

局部放电是电力设备绝缘劣化的早期征兆,其准确检测对电力设备安全稳定运行有重要意义。现有研究侧重于对局部放电脉冲波形进行分析与处理,来解决变电站现场局部放电信号信噪比低、易受干扰的问题,从而提高定向准确度。该文将局部放电定向问题转换为统计分析问题,利用概率统计中的最大似然估计法实现了低信噪比环境下的特高频局部放电准确定向。仿真分析计算及变电站电气试验结果证明,该方法能提高局部放电定向精度,特别是在干扰较多、信噪比较低的变电站环境下(信噪比约5dB),定向精度高于传统多信号分类(MUSIC)算法约20%。该文为利用概率统计方法解决局部放电定向问题提供了新思路。

Partial discharge (PD) is one of the causes of insulation degradation in electrical equipment.Accurate detection of partial discharge is of great significance to the safety and stability of electrical equipment.The existing research focuses on the analysis and processing of the partial discharge pulse waveform,trying to solve the problem of low signal to noise ratio (SNR) and susceptibility to interference,thereby improving the directional of arrival (DOA) estimation accuracy.In this paper,the problem of PD detection is transferred into a statistical analysis problem.The maximum likelihood estimation method is utilized to solve the problem of ultra-high frequency PD DOA estimation.Simulation analysis and field electrical experiment results showed that the method can improve the accuracy of DOA estimation,especially in substation environment where SNR=5dB.The estimation accuracy of the proposed method increased 20% compared to the traditional MUSIC algorithm.This paper provides a new perspective for solving the PD detection problem by using probability statistics method.