Partial Discharge Denoising Method Based on Improved Wavelet Threshold Optimized by Double Chain Quantum Genetic Algorithm

摘要

Aiming at the problem of PD signal noise suppression, a new PD denoising method based on the improved wavelet threshold optimized by double chain quantum genetic algorithm is proposed. Based on the traditional wavelet thresholding method, a new thresholding function with adjusting factors $lpha$ and $eta$ is constructed, and the adjusting factors $lpha$ and $eta$ are optimized by double chain quantum genetic algorithm, so that the adjusting factors under different decomposition scales can be determined quickly and accurately, and the adaptive thresholding can be realized. Through the denoising of PD simulation signals and on-site detection signal, and compared with the soft threshold and hard threshold denoising algorithm, the results show that the algorithm has the best evaluation index of denoising effect, and can effectively denoise the white noise and narrow-band interference of PD signals. The denoising results have high accuracy and better retain the original characteristics of PD signals, which has practical application value.