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

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 23; p. 9386
• Main Authors: Wang, Yanwen, Chen, Peng, Zhao, Yongmei, Sun, Yanying
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.12.2022; MDPI
• Subjects: Algorithms; Analysis; Cables; Computer Simulation; Evolution & development; genetic algorithm; Genetic algorithms; Genetic research; Heart Rate; Methods; Mines and mineral resources; mining cables; Morphology; Mutation; Optimization; PD denoising; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio; VMD; wavelet threshold; Wavelet transforms; United Kingdom; genetic algorithm; mining cables; wavelet threshold; PD denoising; VMD
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22239386

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 K and the quadratic penalty factor α is determined; secondly, the PD signal is decomposed by the VMD algorithm to obtain K 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.