Research on noise reduction of local discharge signal based on adaptive ensemble empirical mode decomposition algorithm
SUN Cong1,2, JU Pengfei1,3, LI Dahua1,2, LI Dong1,2
1. School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin 300384; 2. Tianjin Advanced Mechatronic System Design and Intelligent Control Laboratory, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384; 3. National Experimental Teaching Demonstration Center of Mechanical and Electrical Engineering, Tianjin University of Technology, Tianjin 300384
Abstract：High voltage switchgear is widely used in power system, so it is very important to ensure its safe and stable operation. Aiming at the problems of narrow-band interference and other noise interference in the analysis of partial discharge of high-voltage switchgear, a new noise reduction algorithm called adaptive ensemble empirical mode decomposition (AEEMD) is proposed in this paper. The core idea of the proposed algorithm is to decompose only the first-order mode after adding white noise to the original signal, and then add noise to the remaining signal for cyclic processing. The denoising process is simplified and modal aliasing is reduced. Experimental results show that the signal waveform obtained by this method is basically consistent with the measured original signal waveform, and it is superior to the other two algorithms.
孙聪, 鞠鹏飞, 李大华, 李栋. 基于自适应集合经验模态分解算法的局部放电信号降噪研究[J]. 电气技术, 2022, 23(2): 67-72.
SUN Cong, JU Pengfei, LI Dahua, LI Dong. Research on noise reduction of local discharge signal based on adaptive ensemble empirical mode decomposition algorithm. Electrical Engineering, 2022, 23(2): 67-72.
2022, Vol. 23 
