An Improved Multi-Scale Morphological Undecimated Wavelet Method and its Application in Rolling Bearing Fault Feature Extraction

Abstract:

For the purpose of extract the fault feature hidden by strong noise background in rolling bearing fault signal, a morphological undecimated wavelet method was proposed. A undecimated wavelet decomposition operator called gradient filter was presented based on an open-closed and closed-open mixed filter. The morphological gradient filter was used to extract the impulse feature of signal. The type and the length of structure elements used in these filters were alterable adapt to the signal. The method was applied to analyze the simulated data and measured vibration signals from the bearing with fault. The results confirm that the proposed method is feasible in impulse feature extraction of signal, and it is more effective than other traditional morphological undecimated wavelet methods.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 1009-1013
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.1009
• Online since: August 2013
• Authors: Qiang Hua Chen, Hong Ru Li, Bao Hua Xu
• Keywords: Feature Extraction, Morphological Undecimated Wavelet, Multi-Element, Multi-Scale, Rolling Bearing

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