基于多重分形谱的转子系统故障诊断与参数优选
Because of the robustness of one dimensional time series reconstruction G-P algorithm to extract the fault omen is poor,especially influenced by a sensitive noise in the measured signal.A noise reduction method is proposed based on detrended fluctuat ion analysis（FDA） and kernel principal component...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2013-01-01
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| Series: | Jixie chuandong |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2013.09.014 |
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| Summary: | Because of the robustness of one dimensional time series reconstruction G-P algorithm to extract the fault omen is poor,especially influenced by a sensitive noise in the measured signal.A noise reduction method is proposed based on detrended fluctuat ion analysis（FDA） and kernel principal component analysis（KPCA）,the eigenvalue extraction algorithm based on Mult ifractal spectrum is presented.Through pseudo-phase portrait to determine the weighting factor threshold,optimize and choose parameter and compare with the defects of single G<sub>P</sub> algorithm,and combine with the 3 kinds of rotor system common faults,the stability and accuracy of eigenvalue extraction of this method is analyzed,the results prove that,the diagnosis result is good. |
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| ISSN: | 1004-2539 |