Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System
This paper established the fault diagnosis system of aluminum electrolysis, according to the characteristics of the faults in aluminum electrolysis. This system includes two subsystems; one is process fault subsystem and the other is fault subsystem. Process fault subsystem includes the subneural ne...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2014/975317 |
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| _version_ | 1832552023712595968 |
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| author | Jie-jia Li Xiao-yan Han Peng Zhou Xiao-yu Sun Na Chang |
| author_facet | Jie-jia Li Xiao-yan Han Peng Zhou Xiao-yu Sun Na Chang |
| author_sort | Jie-jia Li |
| collection | DOAJ |
| description | This paper established the fault diagnosis system of aluminum electrolysis, according to the characteristics of the faults in aluminum electrolysis. This system includes two subsystems; one is process fault subsystem and the other is fault subsystem. Process fault subsystem includes the subneural network layer and decision fusion layer. Decision fusion neural network verifies the diagnosis result of the subneural network by the information transferring over the network and gives the decision of fault synthetically. EMD algorithm is used for data preprocessing of current signal in stator of the fault subsystem. Wavelet decomposition is used to extract feature on current signal in the stator; then, the system inputs the feature to the rough neural network for fault diagnosis and fault classification. The rough neural network gives the results of fault diagnosis. The simulation results verify the feasibility of the method. |
| format | Article |
| id | doaj-art-83958e49b3c54bb6bfc9677a6d3eac8e |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-83958e49b3c54bb6bfc9677a6d3eac8e2025-02-03T05:59:46ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422014-01-01201410.1155/2014/975317975317Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control SystemJie-jia Li0Xiao-yan Han1Peng Zhou2Xiao-yu Sun3Na Chang4Information & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, ChinaInformation & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, ChinaInformation & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, ChinaInformation & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, ChinaInformation & Control Engineering Faculty, Shenyang Jianzhu University, Shenyang 110168, ChinaThis paper established the fault diagnosis system of aluminum electrolysis, according to the characteristics of the faults in aluminum electrolysis. This system includes two subsystems; one is process fault subsystem and the other is fault subsystem. Process fault subsystem includes the subneural network layer and decision fusion layer. Decision fusion neural network verifies the diagnosis result of the subneural network by the information transferring over the network and gives the decision of fault synthetically. EMD algorithm is used for data preprocessing of current signal in stator of the fault subsystem. Wavelet decomposition is used to extract feature on current signal in the stator; then, the system inputs the feature to the rough neural network for fault diagnosis and fault classification. The rough neural network gives the results of fault diagnosis. The simulation results verify the feasibility of the method.http://dx.doi.org/10.1155/2014/975317 |
| spellingShingle | Jie-jia Li Xiao-yan Han Peng Zhou Xiao-yu Sun Na Chang Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System Advances in Materials Science and Engineering |
| title | Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System |
| title_full | Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System |
| title_fullStr | Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System |
| title_full_unstemmed | Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System |
| title_short | Comprehensive Analysis of Fault Diagnosis Methods for Aluminum Electrolytic Control System |
| title_sort | comprehensive analysis of fault diagnosis methods for aluminum electrolytic control system |
| url | http://dx.doi.org/10.1155/2014/975317 |
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