Abstract
Prognostics and health management has become an advanced engineering technology in avionics systems which can implement condition monitoring and reduce unnecessary downtime. A prognostic application to power MOSFETs is developed in this paper. Firstly, failure mechanism of the power MOSFETs under power cycling aging tests is analyzed. Then, the drain-source on-state resistance is considered as a leading precursor of failure as it exhibits a decaying trend. Finally, a degradation model is established to predict the remaining useful life based on Kalman filter and LS-SVM, respectively. Several results are analyzed to demonstrate the feasibility and effectiveness of these methods.
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Acknowledgement
This work is supported by Domestic Cooperation Project of Shanghai Science and Technology Innovation Action Plan in 2017 (No. 17595800900), supported by Guangxi Key Laboratory of Cryptography and Information Security (No. GCIS201719), and supported by Key Lab of Information Network Security of Ministry of Public Security (The Third Research Institute of Ministry of Public Security) under grant no. C18607.
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Wu, J., Xu, Z., Wei, X. (2020). Remaining Useful Life Prediction of Power MOSFETs Using Model-Based and Data-Driven Methods. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_56
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DOI: https://doi.org/10.1007/978-3-030-15235-2_56
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