Identification of Optimal Demodulation Frequency Band and Its Application in Fault Diagnosis of Rolling Element Bearings
In order to effectively extract fault impulses of rolling element bearings in the presence of low signal to noise ratio and intense non-Gaussian noise, a new method for identifying optimal demodulation frequency band was presented and applied to fault diagnosis of rolling element bearings. The propo...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Electric Drive for Locomotives
2019-09-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128x.2019.05.120 |
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| Summary: | In order to effectively extract fault impulses of rolling element bearings in the presence of low signal to noise ratio and intense non-Gaussian noise, a new method for identifying optimal demodulation frequency band was presented and applied to fault diagnosis of rolling element bearings. The proposed method adopted the sparsity of frequency band signal to quantify fault impulses,and decomposed frequency band signal with maximal sparsity was selected as the optimal demodulation signal. Eventually, the bearing fault types can be identified from envelope spectrum of the optimal demodulation signal. To validate the effectiveness of the proposed method in bearing fault diagnosis, simulated signals and experimental signals of bearing localized faults were tested respectively and the performance of fast kurtogram was compared. The results indicated that the proposed method could more accurately recognize resonant frequency band than fast kurtogram and effectively extract bearing fault characteristics with the interference of low signal to noise ratio and intense non-Gaussian noise. |
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| ISSN: | 1000-128X |