Planet bearing fault diagnosis using multipoint Optimal Minimum Entropy Deconvolution Adjusted

The vibration signals of planet bearings exhibit periodic impulsive features and are modulated by various effects, including: 1) time-varying vibration transfer path; 2) load zone passing; 3) time-varying angles between gear pair mesh lines of action and impact force vector; and 4) bearing fault. At the same time, slippages of rolling elements in bearings can lead to randomized periods of impulses and blurs in the Fourier spectrum of planet bearing vibration signals. As a result, common methods have limitations in analyzing planet bearing signals. In this paper, we establish a model of planet bearing vibration signal considering slippages in rolling elements, then derive its Fourier spectrum to illustrate the impact of slippages on Fourier spectrum. In order to extract the features of impulses caused by faults, we apply a deconvolution algorithm called Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA), which is good at deconvoluting signals with periodic impulses. For adaption to planet bearing vibration, we redesign the target vector of MOMEDA to simulate the actual stochastic impulses caused by slippages. To quantify the severity of slippages and describe the randomness of impulses, we propose the slippage parameter and utilize negentropy to determinate it. Lastly, the proposed method is validated using both numerical simulation and experimental data. We detect faults in outer race, rolling element and inner race of planet bearings, respectively. Compared with traditional Fourier and envelope spectra as well as kurtogram filtering method, MOMEDA shows specific applicability for fault diagnosis of planet bearings. (C) 2019 Elsevier Ltd. All rights reserved.