Multiscale slope feature extraction for rotating machinery fault diagnosis using wavelet analysis

作者：Li Peng; Kong Fanrang; He Qingbo^*; Liu Yongbin

来源：Measurement, 2013, 46(1): 497-505.

DOI：10.1016/j.measurement.2012.08.007

• Discrete wavelet transform
• Rotating machinery
• Multiscale slope feature
• Fault diagnosis

This paper proposes a multiscale slope feature extraction method using wavelet-based multiresolution analysis for rotating machinery fault diagnosis. The new method mainly includes three following steps: the discrete wavelet transform (DWT) is first performed on vibration signals gathered by accelerometer from rotating machinery to achieve a series of detailed signals at different scales; the variances of multiscale detailed signals are then calculated; finally, the wavelet-based multiscale slope features are estimated from the slope of logarithmic variances. The presented features reveal an inherent structure within the power spectra of vibration signals. The effectiveness of the proposed feature was verified by two experiments on bearing defect identification and gear wear diagnosis. Experimental results show that the wavelet-based multiscale slope features have the merits of high accuracy and stability in classifying different conditions of both bearings and gearbox, and thus are valuable for machinery fault diagnosis.

• 出版日期2013-1
• 单位中国科学技术大学