Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation
1
Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China
2
Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3
Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
4
University of Chinese Academy of Sciences, Beijing 100049, China
5
Liaoning Institute of Science and Technology, Benxi 117004, China
6
Department of Electronic Engineering, Hanyang University, Ansan 15588, Korea
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(2), 473; https://doi.org/10.3390/s21020473
Received: 27 October 2020
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Revised: 5 January 2021
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Accepted: 7 January 2021
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Published: 11 January 2021
(This article belongs to the Special Issue Sensors for Fault Diagnosis and Prognostics)
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.
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Keywords:
insulation degradation; insulation failure; inter-turn short; resonant frequency; PF; prognostics
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MDPI and ACS Style
Guo, H.; Xu, A.; Wang, K.; Sun, Y.; Han, X.; Hong, S.H.; Yu, M. Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation. Sensors 2021, 21, 473. https://doi.org/10.3390/s21020473
AMA Style
Guo H, Xu A, Wang K, Sun Y, Han X, Hong SH, Yu M. Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation. Sensors. 2021; 21(2):473. https://doi.org/10.3390/s21020473
Chicago/Turabian StyleGuo, Haifeng, Aidong Xu, Kai Wang, Yue Sun, Xiaojia Han, Seung H. Hong, and Mengmeng Yu. 2021. "Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation" Sensors 21, no. 2: 473. https://doi.org/10.3390/s21020473
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