METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA
In order to solve the problem that the fault feature information of rolling bearing is difficult to be separated,a new method of fault feature extraction is presented,which is based on the complementary ensemble empirical mode decomposition（ CEEMD） and fast independent component analysis（ Fast ICA）....
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2018-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.05.002 |
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| _version_ | 1841535578297860096 |
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| author | HUANG GangJing FAN YuGang HUANG GuoYong |
| author_facet | HUANG GangJing FAN YuGang HUANG GuoYong |
| author_sort | HUANG GangJing |
| collection | DOAJ |
| description | In order to solve the problem that the fault feature information of rolling bearing is difficult to be separated,a new method of fault feature extraction is presented,which is based on the complementary ensemble empirical mode decomposition（ CEEMD） and fast independent component analysis（ Fast ICA）. First,analyze the CEEMD vibration signals,decompose them into intrinsic mode function（ IMF） components signal of different scales; then through the sensitivity evaluation algorithm,decompose and recombine the signals,and use Fast ICA to reduce their noise; in the end,conduct Hilbert envelope spectrum analysis to the signals separated by the Fast ICA,to obtain the fault feature information. This method is applied to the fault analysis of rolling bearing vibration signal,and was proved to be valid. |
| format | Article |
| id | doaj-art-cd1e4eed7fa546b0b507fc4ef7785b02 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2018-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-cd1e4eed7fa546b0b507fc4ef7785b022025-01-15T02:31:28ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692018-01-01401024102930603016METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICAHUANG GangJingFAN YuGangHUANG GuoYongIn order to solve the problem that the fault feature information of rolling bearing is difficult to be separated,a new method of fault feature extraction is presented,which is based on the complementary ensemble empirical mode decomposition（ CEEMD） and fast independent component analysis（ Fast ICA）. First,analyze the CEEMD vibration signals,decompose them into intrinsic mode function（ IMF） components signal of different scales; then through the sensitivity evaluation algorithm,decompose and recombine the signals,and use Fast ICA to reduce their noise; in the end,conduct Hilbert envelope spectrum analysis to the signals separated by the Fast ICA,to obtain the fault feature information. This method is applied to the fault analysis of rolling bearing vibration signal,and was proved to be valid.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.05.002CEEMDSensitive factorFast independent component analysisRolling bearingFault diagnosis |
| spellingShingle | HUANG GangJing FAN YuGang HUANG GuoYong METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA Jixie qiangdu CEEMD Sensitive factor Fast independent component analysis Rolling bearing Fault diagnosis |
| title | METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA |
| title_full | METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA |
| title_fullStr | METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA |
| title_full_unstemmed | METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA |
| title_short | METHOD OF FAULT FEATURE EXTRATION BASED ON CEEMD AND FASTICA |
| title_sort | method of fault feature extration based on ceemd and fastica |
| topic | CEEMD Sensitive factor Fast independent component analysis Rolling bearing Fault diagnosis |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2018.05.002 |
| work_keys_str_mv | AT huanggangjing methodoffaultfeatureextrationbasedonceemdandfastica AT fanyugang methodoffaultfeatureextrationbasedonceemdandfastica AT huangguoyong methodoffaultfeatureextrationbasedonceemdandfastica |