A TEO‐based modified Laplacian of Gaussian filter to detect faults in rolling element bearing for variable rotational speed machine

Abstract

Conventional signal processing techniques for fault detection are usually aimed at constant speed conditions. Nowadays, order tracking, especially tacho-less order tracking is regarded as a valuable tool for extracting fault features under variable rotational speed conditions. Therefore, a teager energy operator (TEO)-based modified Laplacian of Gaussian filter is proposed to enhance the fault detection behaviour of tacho-less order tracking. This method consists of four steps: First, multi-synchrosqueezing transform is employed to estimate and then extract the instantaneous rotation frequency of a shaft. Second, based on the extracted curve, the non-stationary domain signal is converted into a quasi-stationary domain by the re-sampling technique. Third, the obtained quasi-stationary domain signal is de-noise by the novel method. Finally, fault characteristic orders are extracted via envelope order spectrum analysis method and the performance is significantly improved. The results of numerical simulation and experimental investigations are performed to validate the superiority of the novel method for fault extraction under variable rotational speed conditions.