FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR
Reciprocating compressor vibration signal is typical nonlinear and non-stationary,and the vibration information interference coupling, owing to this problem,a fault diagnosis method of reciprocating compressor on the resonance-based sparse signal decomposition with optimal Q-factor was proposed.The...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.009 |
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| _version_ | 1850093521827004416 |
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| author | WANG JinDong BU QingChao ZHAO HaiYang ZHANG HongBin |
| author_facet | WANG JinDong BU QingChao ZHAO HaiYang ZHANG HongBin |
| author_sort | WANG JinDong |
| collection | DOAJ |
| description | Reciprocating compressor vibration signal is typical nonlinear and non-stationary,and the vibration information interference coupling, owing to this problem,a fault diagnosis method of reciprocating compressor on the resonance-based sparse signal decomposition with optimal Q-factor was proposed.The method use resonance sparse decomposition to find the low resonance component which its kurtosis is maximum, optimize Q-factor with genetic algorithm and particle swarm optimization to get the optimal Q-factor;then use resonance sparse decomposition to decompose reciprocating compressor vibration signal by the optimal Q-factor;the result shows that this method can diagnose the oversized bearing clearance fault effectively. |
| format | Article |
| id | doaj-art-95c3813ec443405b9afedd0a3f60ae7f |
| institution | DOAJ |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-95c3813ec443405b9afedd0a3f60ae7f2025-08-20T02:41:54ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014155756130604897FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTORWANG JinDongBU QingChaoZHAO HaiYangZHANG HongBinReciprocating compressor vibration signal is typical nonlinear and non-stationary,and the vibration information interference coupling, owing to this problem,a fault diagnosis method of reciprocating compressor on the resonance-based sparse signal decomposition with optimal Q-factor was proposed.The method use resonance sparse decomposition to find the low resonance component which its kurtosis is maximum, optimize Q-factor with genetic algorithm and particle swarm optimization to get the optimal Q-factor;then use resonance sparse decomposition to decompose reciprocating compressor vibration signal by the optimal Q-factor;the result shows that this method can diagnose the oversized bearing clearance fault effectively.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.009 |
| spellingShingle | WANG JinDong BU QingChao ZHAO HaiYang ZHANG HongBin FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR Jixie qiangdu |
| title | FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR |
| title_full | FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR |
| title_fullStr | FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR |
| title_full_unstemmed | FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR |
| title_short | FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR |
| title_sort | fault diagnosis of reciprocating compressor on the resonance based sparse signal decomposition with optimal q factor |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.03.009 |
| work_keys_str_mv | AT wangjindong faultdiagnosisofreciprocatingcompressorontheresonancebasedsparsesignaldecompositionwithoptimalqfactor AT buqingchao faultdiagnosisofreciprocatingcompressorontheresonancebasedsparsesignaldecompositionwithoptimalqfactor AT zhaohaiyang faultdiagnosisofreciprocatingcompressorontheresonancebasedsparsesignaldecompositionwithoptimalqfactor AT zhanghongbin faultdiagnosisofreciprocatingcompressorontheresonancebasedsparsesignaldecompositionwithoptimalqfactor |