DWPT-Based Sub-Band Analysis for FaultDetection of Rolling Element Bearings

摘要

To early detect symptoms of defective rolling element bearings, this paper introduces discrete wavelet packet transform （DWPT）-based sub-band analysis. The objective of this analysis is to explore the impacts of multiple sub-band signals by 4-level DWPTusing proper Daubechies mother wavelet on a 2.5-second acoustic emission signal. In particular, the DWPT-based sub-bandanalysis determines the most informative sub-band signal involving intrinsic information about bearing defects among theaforementioned multiple sub-band signals based on the ratio of spectral magnitudes at harmonics of the bearing＇s characteristicfrequency to those around the harmonics. This paper also verifies the efficacy of the DWPT-based sub-band analysis for seededbearing defects （i.e., a crack on the inner race, the outer race, or a roller）.