IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS
Aiming at the shortcomings of multipoint optimal minimum entropy deconvolution adjusted（ MOMEDA） method,which cannot automatically identify the fault impulse period and shorten the length of deconvolved signal when enhancing bearing fault features,an improved MOMEDA（ IMOMEDA） method is proposed.The...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2021-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.01.001 |
| _version_ | 1797767691126177792 |
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| author | CHEN BingYan SONG DongLi ZHANG WeiHua CHENG Yao |
| author_facet | CHEN BingYan SONG DongLi ZHANG WeiHua CHENG Yao |
| author_sort | CHEN BingYan |
| collection | DOAJ |
| description | Aiming at the shortcomings of multipoint optimal minimum entropy deconvolution adjusted（ MOMEDA） method,which cannot automatically identify the fault impulse period and shorten the length of deconvolved signal when enhancing bearing fault features,an improved MOMEDA（ IMOMEDA） method is proposed.The autocorrelation spectrum of square envelope of the vibration signal is used to adaptively identify the fault period,and the estimated impulse period is used to deconvolve the vibration signal to enhance the periodic impulse features.Then the signal waveform extension method is used to extend the deconvolved signal to make its length consistent with the original signal.Finally,the obtained filtered signal is deconvolved for a certain number of times to effectively enhance the periodic features of the original signal.The analysis results of simulated bearing fault signal and railway bearing experiment signals and the comparisons with Kurtogram method show that the improved MOMEDA method can automatically identify the fault impulse period and effectively enhance the fault characteristics of rolling bearing. |
| first_indexed | 2024-03-12T20:42:31Z |
| format | Article |
| id | doaj.art-c47ac6d176024ea8b2c895a3e8a64f93 |
| institution | Directory Open Access Journal |
| issn | 1001-9669 |
| language | zho |
| last_indexed | 2024-03-12T20:42:31Z |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj.art-c47ac6d176024ea8b2c895a3e8a64f932023-08-01T07:52:34ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692021-01-01431830609741IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGSCHEN BingYanSONG DongLiZHANG WeiHuaCHENG YaoAiming at the shortcomings of multipoint optimal minimum entropy deconvolution adjusted（ MOMEDA） method,which cannot automatically identify the fault impulse period and shorten the length of deconvolved signal when enhancing bearing fault features,an improved MOMEDA（ IMOMEDA） method is proposed.The autocorrelation spectrum of square envelope of the vibration signal is used to adaptively identify the fault period,and the estimated impulse period is used to deconvolve the vibration signal to enhance the periodic impulse features.Then the signal waveform extension method is used to extend the deconvolved signal to make its length consistent with the original signal.Finally,the obtained filtered signal is deconvolved for a certain number of times to effectively enhance the periodic features of the original signal.The analysis results of simulated bearing fault signal and railway bearing experiment signals and the comparisons with Kurtogram method show that the improved MOMEDA method can automatically identify the fault impulse period and effectively enhance the fault characteristics of rolling bearing.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.01.001Feature enhancement;Fault diagnosis;Railway bearings;Multipoint optimal minimum entropy deconvolution adjusted;Autocorrelation function |
| spellingShingle | CHEN BingYan SONG DongLi ZHANG WeiHua CHENG Yao IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS Jixie qiangdu Feature enhancement;Fault diagnosis;Railway bearings;Multipoint optimal minimum entropy deconvolution adjusted;Autocorrelation function |
| title | IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS |
| title_full | IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS |
| title_fullStr | IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS |
| title_full_unstemmed | IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS |
| title_short | IMPROVED MOMEDA METHOD AND ITS APPLICATION TO FAULT FEATURE ENHANCEMENT OF ROLLING ELEMENT BEARINGS |
| title_sort | improved momeda method and its application to fault feature enhancement of rolling element bearings |
| topic | Feature enhancement;Fault diagnosis;Railway bearings;Multipoint optimal minimum entropy deconvolution adjusted;Autocorrelation function |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2021.01.001 |
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