Early Fault Diagnosis of the Rolling Bearing using Wavelet Transformation
Wang Lili  Wang Chao  Cai Zhengmin
(Xi'an Jiaotong University, 710049)

Abstract:  An efficient method is proposed for diagnosis of the rolling bearing's early fault. The fault signal is abstracted and amplified from the vibration signal of the rolling bearing with high background noise using narrow band filtration, envelope analysis and wavelet transformation. Several 307 rolling bearings are considered as examples to illustrate the validity. This method is very suitable for the online inspection and diagnosis of the rolling bearing.
Keywords: rolling bearing, fault diagnosis, wavelet transformation.