Study on the Preprocessing Method of Rolling Bearing Signal based on LFK and Entropy Difference Spectrum Criterion
Aiming at the problem that the fault feature of rolling bearing can be easily overwhelmed by random noise,a novel denoising method on the basis of local characteristic- scale decomposition and Fast Kurtogram（ LFK） is presented. Firstly,the signal is decomposed by local characteristic- scale decompos...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2016-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.12.007 |
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| Summary: | Aiming at the problem that the fault feature of rolling bearing can be easily overwhelmed by random noise,a novel denoising method on the basis of local characteristic- scale decomposition and Fast Kurtogram（ LFK） is presented. Firstly,the signal is decomposed by local characteristic- scale decomposition（ LCD） and entropy difference spectrum is proposed to choose and reconstruct the component signals. However,the residual noise may still exist in the reconstructed signal. So in order to remove noise interference to some degree,the Fast Kurtogram is applied to enhance the filtering and denoising effect further. Meanwhile,and the bearing fault feature information is well preserved. At last,the validity of the method is tested and verified by the simulation signal and the inner ring fault signal of rolling bearing. |
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| ISSN: | 1004-2539 |