An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method
This study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. The method was used to conduct information fu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2019/3926963 |
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| _version_ | 1832563367700594688 |
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| author | Xiaoxun Zhu Jianhong Zhao Dongnan Hou Zhonghe Han |
| author_facet | Xiaoxun Zhu Jianhong Zhao Dongnan Hou Zhonghe Han |
| author_sort | Xiaoxun Zhu |
| collection | DOAJ |
| description | This study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. The method was used to conduct information fusion of real modal components of vibration signals and SDP image identification using CNN in order to achieve vibration fault diagnosis. Compared with other graphic processing methods, the proposed method more fully expressed the characteristics of different vibration signals and thus presented variations between different vibration states in a simpler and more intuitive way. The proposed method was experimentally investigated using simulation signals and rotor test-rig signals, and its validity and advancements were demonstrated using experimental analysis. By using CNN through deep learning to adaptively extract SDP characteristic information, vibration fault identification was ultimately realized. |
| format | Article |
| id | doaj-art-8482db85d60b478fad32f7aff34abae7 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-8482db85d60b478fad32f7aff34abae72025-02-03T01:20:24ZengWileyShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/39269633926963An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis MethodXiaoxun Zhu0Jianhong Zhao1Dongnan Hou2Zhonghe Han3School of Energy and Power Engineering, North China Electric Power University, Baoding 071003, Hebei, ChinaSchool of Energy and Power Engineering, North China Electric Power University, Baoding 071003, Hebei, ChinaSchool of Energy and Power Engineering, North China Electric Power University, Baoding 071003, Hebei, ChinaSchool of Energy and Power Engineering, North China Electric Power University, Baoding 071003, Hebei, ChinaThis study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. The method was used to conduct information fusion of real modal components of vibration signals and SDP image identification using CNN in order to achieve vibration fault diagnosis. Compared with other graphic processing methods, the proposed method more fully expressed the characteristics of different vibration signals and thus presented variations between different vibration states in a simpler and more intuitive way. The proposed method was experimentally investigated using simulation signals and rotor test-rig signals, and its validity and advancements were demonstrated using experimental analysis. By using CNN through deep learning to adaptively extract SDP characteristic information, vibration fault identification was ultimately realized.http://dx.doi.org/10.1155/2019/3926963 |
| spellingShingle | Xiaoxun Zhu Jianhong Zhao Dongnan Hou Zhonghe Han An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method Shock and Vibration |
| title | An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method |
| title_full | An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method |
| title_fullStr | An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method |
| title_full_unstemmed | An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method |
| title_short | An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method |
| title_sort | sdp characteristic information fusion based cnn vibration fault diagnosis method |
| url | http://dx.doi.org/10.1155/2019/3926963 |
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