Mine cable partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold - Jiyuan CAO; Yanwen WANG; Peng CHEN; Xuan ZHOU; Weixiong ZHU; Yihe ZHANG; Le WANG (Meitan xuebao)
The insulation state of the mine cable plays an important role in the stable operation of the mine power supply system. Partial discharge on-line monitoring is an important means of cable insulation state monitoring. Aiming at the problems that the mine cable partial discharge signal is easily submerged in the field white noise and periodic narrowband interference, and the adaptability of the noise reduction method is generally not strong, a partial discharge denoising method based on multivariate variational mode decomposition and improved wavelet threshold is proposed. Firstly, the minimum average envelope entropy is used as the fitness function, and the sparrow search algorithm is used to realize the automatic optimization of the decomposition mode number and penalty factor of multivariate variational mode decomposition. Secondly, the kurtosis value of each intrinsic mode function is calculated, and the partial discharge dominant component and the noise dominant component are distinguished. Using the characteristics of Wiener filtering that can adaptively adjust the filtering effect through local variance, the partial discharge characteristic signal in the partial discharge dominant component is accurately extracted. The partial discharge characteristic signal is classified as gross error by 3σ criteria, and the Gaussian white noise and narrow-band interference signal in the noise dominant component are inversely suppressed. The partial discharge dominant component and the noise dominant component are reconstructed to obtain the partial discharge reconstruction signal. Finally, the exponential decay wavelet threshold function is constructed, which can quickly approximate the hard threshold function on the basis of overcoming the discontinuity of the hard threshold function and the constant deviation of the soft threshold function. The new improved wavelet threshold algorithm is used to denoise the partial discharge reconstruction signal, and the partial discharge denoising signal is obtained. The proposed method is compared with several common methods. The results show that the proposed method has a good noise reduction effect on the simulated partial discharge signal and the measured partial discharge signal, and the operation efficiency of the algorithm is good.