Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16
In this paper, an inter-turn short-circuit fault of a permanent magnet synchronous motor in an electromechanical actuator is analyzed, and a fault diagnosis method based on transfer learning with a VGG16 convolution network is proposed. First, a 2D finite element model of an inter-turn short circuit...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/8/1232 |
| _version_ | 1797434858394353664 |
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| author | Haibin Huangfu Yong Zhou Jianxin Zhang Shangjun Ma Qian Fang Ye Wang |
| author_facet | Haibin Huangfu Yong Zhou Jianxin Zhang Shangjun Ma Qian Fang Ye Wang |
| author_sort | Haibin Huangfu |
| collection | DOAJ |
| description | In this paper, an inter-turn short-circuit fault of a permanent magnet synchronous motor in an electromechanical actuator is analyzed, and a fault diagnosis method based on transfer learning with a VGG16 convolution network is proposed. First, a 2D finite element model of an inter-turn short circuit fault of a permanent magnet synchronous motor was established in ANSOFT Maxwell, and then a simulation experiment analysis was completed. A three-phase current was chosen as a fault characteristic signal. Second, a fault diagnosis method with a VGG16 deep convolutional neural network and based on transfer learning was designed, and the fine tuning of the hyperparameters of the fault diagnosis model was completed by using grid search and cross verification methods. Finally, based on the transfer learning VGG16 model established in this paper, the inter-turn short circuit fault of a permanent magnetic synchronous machine (PMSM) was diagnosed and verified. The experimental results showed that the proposed convolutional network model based on transfer learning can identify faults effectively and accurately, and has a good engineering guidance significance. |
| first_indexed | 2024-03-09T10:38:57Z |
| format | Article |
| id | doaj.art-bca0e2b9aa6f465eb734a77aa85a8bf7 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T10:38:57Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-bca0e2b9aa6f465eb734a77aa85a8bf72023-12-01T20:47:07ZengMDPI AGElectronics2079-92922022-04-01118123210.3390/electronics11081232Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16Haibin Huangfu0Yong Zhou1Jianxin Zhang2Shangjun Ma3Qian Fang4Ye Wang5School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaJiangshan Heavy Industries Research Institute Co., Ltd., Xiangyang 441057, ChinaXi’an Ding Bai Precision Technology Co., Ltd., Xi’an 710000, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaIn this paper, an inter-turn short-circuit fault of a permanent magnet synchronous motor in an electromechanical actuator is analyzed, and a fault diagnosis method based on transfer learning with a VGG16 convolution network is proposed. First, a 2D finite element model of an inter-turn short circuit fault of a permanent magnet synchronous motor was established in ANSOFT Maxwell, and then a simulation experiment analysis was completed. A three-phase current was chosen as a fault characteristic signal. Second, a fault diagnosis method with a VGG16 deep convolutional neural network and based on transfer learning was designed, and the fine tuning of the hyperparameters of the fault diagnosis model was completed by using grid search and cross verification methods. Finally, based on the transfer learning VGG16 model established in this paper, the inter-turn short circuit fault of a permanent magnetic synchronous machine (PMSM) was diagnosed and verified. The experimental results showed that the proposed convolutional network model based on transfer learning can identify faults effectively and accurately, and has a good engineering guidance significance.https://www.mdpi.com/2079-9292/11/8/1232EMAPMSMtransfer learningdeep convolutional neural networkfault diagnosis |
| spellingShingle | Haibin Huangfu Yong Zhou Jianxin Zhang Shangjun Ma Qian Fang Ye Wang Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 Electronics EMA PMSM transfer learning deep convolutional neural network fault diagnosis |
| title | Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 |
| title_full | Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 |
| title_fullStr | Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 |
| title_full_unstemmed | Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 |
| title_short | Research on Inter-Turn Short Circuit Fault Diagnosis of Electromechanical Actuator Based on Transfer Learning and VGG16 |
| title_sort | research on inter turn short circuit fault diagnosis of electromechanical actuator based on transfer learning and vgg16 |
| topic | EMA PMSM transfer learning deep convolutional neural network fault diagnosis |
| url | https://www.mdpi.com/2079-9292/11/8/1232 |
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