Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation
Electromagnetic coils are one of the key components of many systems. Their insulation failure can have severe effects on the systems in which coils are used. This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils. First, insulation...
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MDPI AG
2021-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/2/473 |
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doaj-ea1a327d8ce342a6996acc034fd9051c2021-01-12T00:04:05ZengMDPI AGSensors1424-82202021-01-012147347310.3390/s21020473Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil InsulationHaifeng Guo0Aidong Xu1Kai Wang2Yue Sun3Xiaojia Han4Seung Ho Hong5Mengmeng Yu6Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, ChinaKey Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, ChinaKey Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, ChinaKey Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, ChinaKey Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, ChinaDepartment of Electronic Engineering, Hanyang University, Ansan 15588, KoreaDepartment of Electronic Engineering, Hanyang University, Ansan 15588, KoreaElectromagnetic coils are one of the key components of many systems. Their insulation failure can have severe effects on the systems in which coils are used. This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils. First, insulation degradation characteristics are extracted from coil high-frequency electrical parameters. Second, health indicator is defined based on insulation degradation characteristics to indicate the health degree of coil insulation. Finally, an insulation degradation model is constructed, and coil insulation RUL prediction is performed by particle filtering. Thermal accelerated degradation experiments are performed to validate the RUL prediction performance. The proposed method presents opportunities for predictive maintenance of systems that incorporate coils.https://www.mdpi.com/1424-8220/21/2/473insulation degradationinsulation failureinter-turn shortresonant frequencyPFprognostics |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Haifeng Guo Aidong Xu Kai Wang Yue Sun Xiaojia Han Seung Ho Hong Mengmeng Yu |
| spellingShingle |
Haifeng Guo Aidong Xu Kai Wang Yue Sun Xiaojia Han Seung Ho Hong Mengmeng Yu Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation Sensors insulation degradation insulation failure inter-turn short resonant frequency PF prognostics |
| author_facet |
Haifeng Guo Aidong Xu Kai Wang Yue Sun Xiaojia Han Seung Ho Hong Mengmeng Yu |
| author_sort |
Haifeng Guo |
| title |
Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation |
| title_short |
Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation |
| title_full |
Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation |
| title_fullStr |
Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation |
| title_full_unstemmed |
Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation |
| title_sort |
particle filtering based remaining useful life prediction for electromagnetic coil insulation |
| publisher |
MDPI AG |
| series |
Sensors |
| issn |
1424-8220 |
| publishDate |
2021-01-01 |
| description |
Electromagnetic coils are one of the key components of many systems. Their insulation failure can have severe effects on the systems in which coils are used. This paper focuses on insulation degradation monitoring and remaining useful life (RUL) prediction of electromagnetic coils. First, insulation degradation characteristics are extracted from coil high-frequency electrical parameters. Second, health indicator is defined based on insulation degradation characteristics to indicate the health degree of coil insulation. Finally, an insulation degradation model is constructed, and coil insulation RUL prediction is performed by particle filtering. Thermal accelerated degradation experiments are performed to validate the RUL prediction performance. The proposed method presents opportunities for predictive maintenance of systems that incorporate coils. |
| topic |
insulation degradation insulation failure inter-turn short resonant frequency PF prognostics |
| url |
https://www.mdpi.com/1424-8220/21/2/473 |
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