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Volume 21
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10.3390/s21020473
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Article

Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation

by
Haifeng Guo
1,2,3,4,5,
Aidong Xu
1,2,3,
Kai Wang
1,2,3,*,
Yue Sun
1,2,3,4,
Xiaojia Han
1,2,3,4,
Seung Ho Hong
6 and
Mengmeng Yu
6
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
Submission received: 27 October 2020 / Revised: 5 January 2021 / Accepted: 7 January 2021 / Published: 11 January 2021
(This article belongs to the Special Issue Sensors for Fault Diagnosis and Prognostics)
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Abstract

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.
Keywords: insulation degradation; insulation failure; inter-turn short; resonant frequency; PF; prognostics 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 Style

Guo, Haifeng, Aidong Xu, Kai Wang, Yue Sun, Xiaojia Han, Seung Ho 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

APA Style

Guo, H., Xu, A., Wang, K., Sun, Y., Han, X., Hong, S. H., & Yu, M. (2021). Particle Filtering Based Remaining Useful Life Prediction for Electromagnetic Coil Insulation. Sensors, 21(2), 473. https://doi.org/10.3390/s21020473

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