The Study of Rotor Fault Feature Recognition Based on EEMD-ICA Denoising Method
Shuyi Liu, Mei Tian, Zhuojuan Yang, Wenliang Liu · IOP Conference Series Materials Science and Engineering · 2018
Aiming at the problem of large noise interference and difficulty in extracting faults during rotor fault diagnosis, a signal de-noising method based on EEMD-ICA was proposed. This method can effectively suppress the modal aliasing phenomenon and accurately separate the noise components contained in signals. Experimental results show that the denoising effect of proposed method was obvious and the rotor fault features can be effectively identified.