Rolling Bearing Feature Extraction Based on Wavelet Filtering with Optimal Combination Bands

Abstract:

In order to select the band-pass filter parameters reasonably, a new method of rolling bearing feature extraction based on wavelet filtering with optimal combination bands is proposed. Filter banks with different number of filter/octave are constructed by Morlet wavelet, which are used to filter the signal. The filters with the optimal frequency-band are selected according to the kurtosis of the filtered signal. Then, the optimal band filters in each filter bank are combined to filter the signals and the feature extraction is available. Through simulation and experimental verification, results show that the proposed method is more effective than the common one.

• Periodical: Applied Mechanics and Materials (Volumes 599-601)
• Pages: 434-440
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.599-601.434
• Online since: August 2014
• Authors: Shuai Zhang*, Yong Xiang Zhang, Jie Ping Zhu
• Keywords: Best Band, Fault Feature, Filter Banks, Octaves, Rolling Bearing, Wavelet

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