Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis
According to the modulation characteristic of fault signals of rolling bearings and the disadvantages of depending on the experience to select resonance high frequency band,an improved empirical mode decomposition（EMD） and spectrum kurtosis method of rolling bearing fault diagnosis is put forward.Fi...
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| Format: | Article |
| Language: | zho |
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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.1004.2539.2016.04.027 |
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| author | Jing Shuangxi Yang Xin Leng Junfa Wang Zhiyang |
| author_facet | Jing Shuangxi Yang Xin Leng Junfa Wang Zhiyang |
| author_sort | Jing Shuangxi |
| collection | DOAJ |
| description | According to the modulation characteristic of fault signals of rolling bearings and the disadvantages of depending on the experience to select resonance high frequency band,an improved empirical mode decomposition（EMD） and spectrum kurtosis method of rolling bearing fault diagnosis is put forward.First of all,the bearing fault signal are decomposed into a number of intrinsic mode functions（IMF） through the EMD method.Then,the false IMF components is eliminated through mutual information,kurtosis and cross- correlation,the fault signal is reconstructed.Finally,the optimal band pass filter is designed by using the spectral kurtosis,then analysis of envelope demodulation spectrum of the filtered signal is carried out,the fault feature of rolling bearing is extracted.The analysis results of rolling bearing experimental signal show that,the improved EMD and spectral kurtosis method can effectively extract the fault features of rolling bearing,and has more advantages than the traditional envelope analysis method. |
| format | Article |
| id | doaj-art-76ba08a7981c4f1b91324fc63b586abb |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2016-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-76ba08a7981c4f1b91324fc63b586abb2025-01-10T14:18:09ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392016-01-014012512829923322Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum KurtosisJing ShuangxiYang XinLeng JunfaWang ZhiyangAccording to the modulation characteristic of fault signals of rolling bearings and the disadvantages of depending on the experience to select resonance high frequency band,an improved empirical mode decomposition（EMD） and spectrum kurtosis method of rolling bearing fault diagnosis is put forward.First of all,the bearing fault signal are decomposed into a number of intrinsic mode functions（IMF） through the EMD method.Then,the false IMF components is eliminated through mutual information,kurtosis and cross- correlation,the fault signal is reconstructed.Finally,the optimal band pass filter is designed by using the spectral kurtosis,then analysis of envelope demodulation spectrum of the filtered signal is carried out,the fault feature of rolling bearing is extracted.The analysis results of rolling bearing experimental signal show that,the improved EMD and spectral kurtosis method can effectively extract the fault features of rolling bearing,and has more advantages than the traditional envelope analysis method.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.04.027Empirical mode decompositionSpectrum kurtosisRolling bearingFault diagnosis |
| spellingShingle | Jing Shuangxi Yang Xin Leng Junfa Wang Zhiyang Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis Jixie chuandong Empirical mode decomposition Spectrum kurtosis Rolling bearing Fault diagnosis |
| title | Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis |
| title_full | Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis |
| title_fullStr | Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis |
| title_full_unstemmed | Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis |
| title_short | Fault Feature Extraction of Rolling Bearing based on Improved EMD and Spectrum Kurtosis |
| title_sort | fault feature extraction of rolling bearing based on improved emd and spectrum kurtosis |
| topic | Empirical mode decomposition Spectrum kurtosis Rolling bearing Fault diagnosis |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2016.04.027 |
| work_keys_str_mv | AT jingshuangxi faultfeatureextractionofrollingbearingbasedonimprovedemdandspectrumkurtosis AT yangxin faultfeatureextractionofrollingbearingbasedonimprovedemdandspectrumkurtosis AT lengjunfa faultfeatureextractionofrollingbearingbasedonimprovedemdandspectrumkurtosis AT wangzhiyang faultfeatureextractionofrollingbearingbasedonimprovedemdandspectrumkurtosis |