A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation
Extraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has t...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/9079790 |
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| _version_ | 1832567576514789376 |
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| author | Xing Yuan Huijie Zhang Hui Liu |
| author_facet | Xing Yuan Huijie Zhang Hui Liu |
| author_sort | Xing Yuan |
| collection | DOAJ |
| description | Extraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has the advantages of matching with the specific oscillation behavior of signal components. In this article, an adaptive sparse representation (ASR) method is proposed, which integrates the sparse code shrinkage (SCS) and parameter optimization into TQWT. However, direct application of ASR is difficult to extract fault signatures at the early stage or low-speed operation due to weak fault symptoms and background noise. A novel fault diagnosis strategy based on continuous wavelet transform (CWT) and ASR is investigated. CWT owns significant advantages on multiscale subdivision and weak signal detection. The results of simulated and experimental vibration signal analyses verify the effectiveness of the proposed method in accurately extracting weak impulse features from the noise environment. |
| format | Article |
| id | doaj-art-348a5c2136824bae84cd58b35431084c |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-348a5c2136824bae84cd58b35431084c2025-02-03T01:01:10ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/9079790A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse RepresentationXing Yuan0Huijie Zhang1Hui Liu2State Key Laboratory for Manufacturing System EngineeringState Key Laboratory for Manufacturing System EngineeringState Key Laboratory for Manufacturing System EngineeringExtraction and enhancement of weak impulse signature is the key of rolling bearing fault prognostics in which case the features are often weak and covered by noise. Tunable Q-factor wavelet transform (TQWT), as an emerging wavelet construction theory developed in a frequency domain explicitly, has the advantages of matching with the specific oscillation behavior of signal components. In this article, an adaptive sparse representation (ASR) method is proposed, which integrates the sparse code shrinkage (SCS) and parameter optimization into TQWT. However, direct application of ASR is difficult to extract fault signatures at the early stage or low-speed operation due to weak fault symptoms and background noise. A novel fault diagnosis strategy based on continuous wavelet transform (CWT) and ASR is investigated. CWT owns significant advantages on multiscale subdivision and weak signal detection. The results of simulated and experimental vibration signal analyses verify the effectiveness of the proposed method in accurately extracting weak impulse features from the noise environment.http://dx.doi.org/10.1155/2022/9079790 |
| spellingShingle | Xing Yuan Huijie Zhang Hui Liu A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation Shock and Vibration |
| title | A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation |
| title_full | A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation |
| title_fullStr | A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation |
| title_full_unstemmed | A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation |
| title_short | A Novel Fault Diagnosis Approach for Rolling Bearing Based on CWT and Adaptive Sparse Representation |
| title_sort | novel fault diagnosis approach for rolling bearing based on cwt and adaptive sparse representation |
| url | http://dx.doi.org/10.1155/2022/9079790 |
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