Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation
Sparse representation has a wide range of applications in the field of image processing and audio processing. Applying the sparse representation theory to the field of vibration signal processing can efficiently represent the periodic components of the signal. Through the Adams system simulation and...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2020-10-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.10.006 |
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| author | Xiaoyun Gong Weiye Zhang Yongjie Jing Wenliao Du |
| author_facet | Xiaoyun Gong Weiye Zhang Yongjie Jing Wenliao Du |
| author_sort | Xiaoyun Gong |
| collection | DOAJ |
| description | Sparse representation has a wide range of applications in the field of image processing and audio processing. Applying the sparse representation theory to the field of vibration signal processing can efficiently represent the periodic components of the signal. Through the Adams system simulation and measured signal rotor coupling fault data sparse representation， the vibration characteristics of rotor unbalance bearing coupling fault and the law of interaction between faults are studied under the sparse representation. The results show that bearing faults are usually submerged under coupled faults， and it exhibits weak fault characteristics compared to unbalanced faults. Aiming at the problem that the bearing fault feature is difficult to extract in the rotor unbalance bearing coupling fault， using the sparse representation method based on Gabor atom to match the periodic vibration component in the rotor unbalance bearing coupled fault vibration signal， and the spectral kurtosis algorithm is used to find the frequency band where the impact signal is located for bearing fault feature extraction. The effectiveness of the proposed method is verified by analyzing multiple sets of measured signals. |
| format | Article |
| id | doaj-art-f00d58ff9a3e42ed8ec1cb903777fda8 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2020-10-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-f00d58ff9a3e42ed8ec1cb903777fda82025-01-10T14:55:21ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392020-10-0144384329791654Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse RepresentationXiaoyun GongWeiye ZhangYongjie JingWenliao DuSparse representation has a wide range of applications in the field of image processing and audio processing. Applying the sparse representation theory to the field of vibration signal processing can efficiently represent the periodic components of the signal. Through the Adams system simulation and measured signal rotor coupling fault data sparse representation， the vibration characteristics of rotor unbalance bearing coupling fault and the law of interaction between faults are studied under the sparse representation. The results show that bearing faults are usually submerged under coupled faults， and it exhibits weak fault characteristics compared to unbalanced faults. Aiming at the problem that the bearing fault feature is difficult to extract in the rotor unbalance bearing coupling fault， using the sparse representation method based on Gabor atom to match the periodic vibration component in the rotor unbalance bearing coupled fault vibration signal， and the spectral kurtosis algorithm is used to find the frequency band where the impact signal is located for bearing fault feature extraction. The effectiveness of the proposed method is verified by analyzing multiple sets of measured signals.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.10.006Sparse representationOMP algorithmFault diagnosisVibration signal processingCoupling fault |
| spellingShingle | Xiaoyun Gong Weiye Zhang Yongjie Jing Wenliao Du Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation Jixie chuandong Sparse representation OMP algorithm Fault diagnosis Vibration signal processing Coupling fault |
| title | Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation |
| title_full | Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation |
| title_fullStr | Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation |
| title_full_unstemmed | Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation |
| title_short | Vibration Characteristic Analysis and Feature Extraction of Bearing Coupling Fault based on Sparse Representation |
| title_sort | vibration characteristic analysis and feature extraction of bearing coupling fault based on sparse representation |
| topic | Sparse representation OMP algorithm Fault diagnosis Vibration signal processing Coupling fault |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.10.006 |
| work_keys_str_mv | AT xiaoyungong vibrationcharacteristicanalysisandfeatureextractionofbearingcouplingfaultbasedonsparserepresentation AT weiyezhang vibrationcharacteristicanalysisandfeatureextractionofbearingcouplingfaultbasedonsparserepresentation AT yongjiejing vibrationcharacteristicanalysisandfeatureextractionofbearingcouplingfaultbasedonsparserepresentation AT wenliaodu vibrationcharacteristicanalysisandfeatureextractionofbearingcouplingfaultbasedonsparserepresentation |