A relevance vector machine-based approach for remaining useful life prediction of power MOSFETs

Accurate prediction of the RUL (remaining useful life) of a degradation component is crucial to the PHM for an electronic system. Power MOSFETs are widely used as essential components of electronic and electrical subsystems and its degradation has got more and more attention. This paper introduces a prognostic method which based on relevance vector machine and a degradation model to predict the RUL of power MOSFET. The proposed method uses relevance vector machine to find the relevance vectors. And then use relevance vectors to find the representative vectors. The degradation model is obtained by fitting the representative vectors. Then the RUL of power MOSFETs can be estimated by extrapolating the degradation model to a failure threshold. In the prediction process, we will update the degradation model when the difference of the predictive value and measured value exceeds the predefined value. The results show that the proposed method can provide better RUL estimation accuracy for power MOSFETs.