Denoising Method of Hydro-turbine Vibration Signal Based on Joint WOA-VMD and Improved Wavelet Threshold

Abstract

Comparing to the untreated signal, the traditional wavelet thresholding functions decomposed and reconstructed signal has a constant error. Variational mode decomposition (VMD) sets different penalty factor α and mode decomposition layer K during signal processing will lead to the final noise reduction results. Therefore, this paper introduces the Whale Optimization Algorithm (WOA)-VMD and improved wavelet threshold denoising for oscillation signal disposal of hydraulic turbine. Firstly, WOA was used to optimize the VMD decomposition parameters α and K with the local minimum of envelope entropy as the objective function, and the optimal noise reduction effect was obtained. Secondly, the vibration signals with noise were deconstructed into K intrinsic mode functions (IMF) after VMD, and their thresholds were set. Furthermore, the IMF component below the threshold value is denoised again by improving the wavelet threshold value. Finally, the IMF reorganization after de-noising is used to obtain the final noise reduction signal. Through the verification analysis, the combination of WOA-VMD and improved wavelet threshold function denoising method could effectively filter the noise in the signal and significantly improve the noise reduction effect of the hydraulic turbine vibration signal.