An Acoustic Emission Event Filtering Method for Low-Speed Bearing Outer Race Defect Localization

Abstract

Rolling element bearing can be diagnosed by find the location of the fault with acoustic emission (AE) technology, this method is independent to the rotating speed. However, bearing AE signals collected under low-speed conditions are susceptible to interference from other components, which will affect the accuracy of localization. This paper proposes an AE event filtering method for low-speed bearing defect localization. Firstly, an improved denoising method based on discrete wavelet transform (DWT) is applied to the interfered AE signal, to suppress the interference component effectively. Secondly, an AE events filtering method is developed based on continuous wavelet transform and Neyman-Pearson criterion (CWT-NP), which includes searching for peaks in the continuous burst time of AE events through CWT, and calculating the peak group ratio (PGR). According to the PGR value of the AE event, the threshold is set by the NP criterion to filter the noise AE event. Lastly, the proposed method achieves satisfactory results in the outer race defect localization of low-speed bearing by constant and variable speed localization experiments. The results of the experiments demonstrate that the proposed approach is capable of filtering noise events, and find the exact location of the source of bearing damage.