Feature Extraction of Rolling Bearing Based on LMD Energy Feature

Abstract:

For the situation that it is difficult to diagnose rolling bearings fault effectively for small samples, so it proposes a feature extraction method of rolling bearing based on local mean decomposition (LMD) energy feature. Due to the frequency domain distribution of vibration signals will change when different faults occur in rolling bearings, so it can use LMD energy feature method to extract the fault features of rolling bearings. The instances analysis and extracted results show that the LMD energy feature can extract the vibration signal fault feature of rolling bearings effectively.

• Periodical: Applied Mechanics and Materials (Volume 868)
• Pages: 363-368
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.868.363
• Online since: July 2017
• Authors: Bang Sheng Xing*, Le Xu
• Keywords: Energy Feature, Feature Extraction, Local Mean Decomposition, Rolling Bearings

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