| Autor: |
Hongtao Su, Mengmeng Song, Zicheng Xiong |
| Předmět: |
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| Zdroj: |
Vibroengineering Procedia; Nov2020, Vol. 34, p14-19, 6p |
| Abstrakt: |
In this work, a novel bearing fault diagnosis method based on EEMD and adaptive redundant lifting scheme packet is proposed. Firstly, EEMD method is used to decompose rolling bearing signals of different fault types, and the correlation coefficient criterion method is carried out in order to screen effective IMF components and reconstruct them. Then, the adaptive redundant lifting scheme packet method is used to denoise the reconstructed signal, and the energy characteristics of different fault signals are extracted. Finally, the bearing fault diagnosis system is constructed by BP neural network diagnosis. The results show that the diagnostic method proposed in this paper has better diagnosis efficiency and precision than the traditional wavelet packet. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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