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- W2943164619 abstract "Prognostics is a practice of predicting health condition and remaining useful lifetime (RUL) of a device or a system. The prognostics of power module enabling the assessment of health condition and time predicted when the module will fail given the current characteristics and loading condition. The presents practice of prognostics on power transistor can be classified into three groups: Model-Driven, Data-Driven and Hybrid method. This paper present an overview of the Model and Data-Driven Methods and their main problem is discussed. This paper also proposes a new prognostics methodology, which utilizes the characteristics of voids, and ON-State resistance, R ds, on as inputs for the proposed algorithm termed as RULPAV (Remaining Useful Life Prediction Algorithm based on Voids). The proposed methodology is expected to improve the RUL prediction as well as to minimize the reliance on junction temperature measurement." @default.
- W2943164619 created "2019-05-09" @default.
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- W2943164619 date "2018-11-01" @default.
- W2943164619 modified "2023-09-23" @default.
- W2943164619 title "An Overview of Data-Driven and Model-Driven Based Prognostics Techniques for Power Modules" @default.
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- W2943164619 doi "https://doi.org/10.1109/iceese.2018.8703563" @default.
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