A New Gear Fault Identification Method Based on EEMD Permutation Entropy and Grey Relation Degree

In this paper, a new fault identification method was proposed based on EEMD permutation entropy and grey relation degree. Firstly, the sampled data was denoised by morphological filter. Secondly, the denoised signal was decomposed into a finite number of stationary intrinsic mode functions (IMF). Thirdly, the permutation entropy were calculated to express some containing the most dominant fault information. Different fault type corresponds with different permutation entropy distribution. Finally, the grey relation degree between the symptom set and standard fault set was calculated as the identification evidence for fault diagnosis. The practical results show that this method is quite effective in gear fault identification. It's suitable for on-line monitoring and diagnosis of gear system.