基于遗传算法优化 VMD 和小波阈值的电力电缆局部放电信号降噪方法

A Denoising Method for Mining Cable PD Signal Based on Genetic Algorithm Optimization of VMD and Wavelet Threshold.

机构信息

School of Mechanical, Electronic & Information Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China.

CHN Energy Technology & Economics Research Institute Co., Ltd., Beijing 100083, China.

出版信息

Sensors (Basel). 2022 Dec 1;22(23):9386. doi: 10.3390/s22239386.

DOI:10.3390/s22239386

PMID:36502087

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9736700/

Abstract

When the pulse current method is used for partial discharge (PD) monitoring of mining cables, the detected PD signals are seriously disturbed by the field noise, which are easily submerged in the noise and cannot be extracted. In order to realize the effective separation of the PD signal and the interference signal of the mining cable and improve the signal-to-noise ratio of the PD signal, a denoising method for the PD signal of the mining cable based on genetic algorithm optimization of variational mode decomposition (VMD) and wavelet threshold is proposed in this paper. Firstly, the genetic algorithm is used to optimize the VMD, and the optimal value of the number of modal components and the quadratic penalty factor is determined; secondly, the PD signal is decomposed by the VMD algorithm to obtain intrinsic mode functions (IMF). Then, wavelet threshold denoising is applied to each IMF, and the denoised IMFs are reconstructed. Finally, the feasibility of the denoising method proposed in this paper is verified by simulation and experiment.

摘要

当采用脉冲电流法对矿用电缆进行局部放电（PD）监测时，检测到的 PD 信号会受到现场噪声的严重干扰，容易淹没在噪声中，无法提取。为了实现矿用电缆 PD 信号的有效分离和干扰信号，提高 PD 信号的信噪比，提出了一种基于遗传算法优化变分模态分解（VMD）和小波阈值的矿用电缆 PD 信号去噪方法。首先，利用遗传算法对 VMD 进行优化，确定模态分量数和二次惩罚因子的最优值；其次，采用 VMD 算法对 PD 信号进行分解，得到固有模态函数（IMF）。然后，对每个 IMF 进行小波阈值去噪，并对去噪后的 IMF 进行重构。最后，通过仿真和实验验证了本文提出的去噪方法的可行性。