Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm
In order to optimize traditional fault diagnosis models for practical applications, a fault diagnosis model based on support vector machines optimized with the adaptive quantum differential evolution of (AQDE-SVM) is proposed in this study. First, the traditional differential evolution is rewritten...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/8126464 |
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| _version_ | 1832565825347780608 |
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| author | Yuanyuan Li Qichun Sun Hua Xu Xiaogang Li Zhijun Fang Wei Yao |
| author_facet | Yuanyuan Li Qichun Sun Hua Xu Xiaogang Li Zhijun Fang Wei Yao |
| author_sort | Yuanyuan Li |
| collection | DOAJ |
| description | In order to optimize traditional fault diagnosis models for practical applications, a fault diagnosis model based on support vector machines optimized with the adaptive quantum differential evolution of (AQDE-SVM) is proposed in this study. First, the traditional differential evolution is rewritten based on real number encoded into a qubit encoding. Second, this study proposes an adaptive quantum rotation gate and uses this gate to update the probability amplitude of the qubits. Finally, compared with quantum genetic algorithm support vector machines (QGA-SVM) and differential evolution-support vector machines (DE-SVM), etc., the results show that the algorithm proposed in this study has a higher diagnosis accuracy and shorter running time, providing great practical engineering value in the application of rolling bearing fault diagnosis. |
| format | Article |
| id | doaj-art-f0e5518e1ba94dd5b173fe0c9a241b4b |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-f0e5518e1ba94dd5b173fe0c9a241b4b2025-02-03T01:06:36ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/8126464Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE AlgorithmYuanyuan Li0Qichun Sun1Hua Xu2Xiaogang Li3Zhijun Fang4Wei Yao5Shanghai University of Engineering ScienceShanghai University of Engineering ScienceKunfeng Quantum Technology Co. Ltd.Kunfeng Quantum Technology Co. Ltd.Shanghai University of Engineering ScienceShanghai University of Engineering ScienceIn order to optimize traditional fault diagnosis models for practical applications, a fault diagnosis model based on support vector machines optimized with the adaptive quantum differential evolution of (AQDE-SVM) is proposed in this study. First, the traditional differential evolution is rewritten based on real number encoded into a qubit encoding. Second, this study proposes an adaptive quantum rotation gate and uses this gate to update the probability amplitude of the qubits. Finally, compared with quantum genetic algorithm support vector machines (QGA-SVM) and differential evolution-support vector machines (DE-SVM), etc., the results show that the algorithm proposed in this study has a higher diagnosis accuracy and shorter running time, providing great practical engineering value in the application of rolling bearing fault diagnosis.http://dx.doi.org/10.1155/2022/8126464 |
| spellingShingle | Yuanyuan Li Qichun Sun Hua Xu Xiaogang Li Zhijun Fang Wei Yao Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm Shock and Vibration |
| title | Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm |
| title_full | Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm |
| title_fullStr | Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm |
| title_full_unstemmed | Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm |
| title_short | Rolling Bearing Fault Diagnosis Based on SVM Optimized with Adaptive Quantum DE Algorithm |
| title_sort | rolling bearing fault diagnosis based on svm optimized with adaptive quantum de algorithm |
| url | http://dx.doi.org/10.1155/2022/8126464 |
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