Abstract: By analyzing the typical characteristics of AE signals, and according to the extracting principle of AE signals initiated by mechanical faults or damages, the reassigned wavelet scalogram analysis method of AE signals is put forward for the first time. When wavelet scalogram and reassigned scalogram are applied for the feature extraction of AE signals at the same time, the latter can improve the aggregation of scalogram, reduce interference terms and attribute the feature information of AE signals more accurately. Through theoretical analysis and simulation, the wavelet basis function and parameters are selected, so the problem that the resolutions of time and frequency of wavelet reassigned scalogram connot simultaneously attain the best is solved. When applying wavelet reassigned scalogram is applied for fault diagnosis of rolling bearings based on AE technique, the diagnosis results are quite visualized, clear and accurate. Both simulations and experimental research prove that the wavelet reassigned scalogram effectively used for condition monitoring and fault diagnosis based on AE technique.

Key words: Acoustic emission, Bearing, Fault diagnosis, Feature extraction, Reassigned scalogram, Scalogram, Wavelets transform