The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network
Due to the new power electronic products improving and many qualities are growing，making the online fault diagnosis of power electronic circuit becomes more important. In this paper，simulation model is established by using MATLAB to obtain output voltage. Then we use the Fourier analysis method to e...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2018-04-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1503 |
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| _version_ | 1849227101030318080 |
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| author | JIANG Yan-shu WU Di WANG Wei-liang |
| author_facet | JIANG Yan-shu WU Di WANG Wei-liang |
| author_sort | JIANG Yan-shu |
| collection | DOAJ |
| description | Due to the new power electronic products improving and many qualities are growing，making the online fault diagnosis of power electronic circuit becomes more important. In this paper，simulation model is established by using MATLAB to obtain output voltage. Then we use the Fourier analysis method to extract the DC component，the amplitude，the second harmonic and harmonic amplitude three times. After these values are normalized，we set them into the BP network to receive six numbers in order to determine fault location and fault point. Taking three phase bridge rectifier circuit as an example with this method，the test error value is less than 10 －4. The experiment result shows that this method has merit of higher diagnostic rate，higher reliability and widely application. |
| format | Article |
| id | doaj-art-a6a9511e2b374f7cbffbaf4646919d4a |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2018-04-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-a6a9511e2b374f7cbffbaf4646919d4a2025-08-24T01:32:56ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832018-04-012302353910.15938/j.jhust.2018.02.007The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural NetworkJIANG Yan-shu0WU Di1WANG Wei-liang2School of Automation，Harbin University of Science and Technology，Harbin 150080，ChinaSchool of Automation，Harbin University of Science and Technology，Harbin 150080，ChinaSchool of Automation，Harbin University of Science and Technology，Harbin 150080，ChinaDue to the new power electronic products improving and many qualities are growing，making the online fault diagnosis of power electronic circuit becomes more important. In this paper，simulation model is established by using MATLAB to obtain output voltage. Then we use the Fourier analysis method to extract the DC component，the amplitude，the second harmonic and harmonic amplitude three times. After these values are normalized，we set them into the BP network to receive six numbers in order to determine fault location and fault point. Taking three phase bridge rectifier circuit as an example with this method，the test error value is less than 10 －4. The experiment result shows that this method has merit of higher diagnostic rate，higher reliability and widely application.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1503power electronic circuitfault diagnosisthe neural network |
| spellingShingle | JIANG Yan-shu WU Di WANG Wei-liang The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network Journal of Harbin University of Science and Technology power electronic circuit fault diagnosis the neural network |
| title | The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network |
| title_full | The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network |
| title_fullStr | The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network |
| title_full_unstemmed | The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network |
| title_short | The Ｒectifiercircuit Fault Diagnosis Based on the BP Neural Network |
| title_sort | rectifiercircuit fault diagnosis based on the bp neural network |
| topic | power electronic circuit fault diagnosis the neural network |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1503 |
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