RUL Estimation for Package Failure of Power Electronic Devices Using Integral Mean of Precursor Signal

Abstract

Package failure like bond-wire lift-off is one common cause of failure for discrete power electronic devices such as Schottky diodes. To estimate their Remaining Useful Lifetime (RUL), forward voltage drop is often used as the precursor signal. Prior researches use the direct forward voltage feature and its derived features to construct neural networks for RUL prediction. These features can reflect the instant health condition of the device in the current time or time window, but miss to represent the accumulated effect of gradually decreasing health conditions. In the paper, we formulate the integral mean feature of forward voltage drop and propose to use it to conduct RUL estimation. By the integral mean feature, we are able to capture the device's health condition in an accumulated fashion. Our experiments show that our approach is superior in generalization performance when compared to the forward voltage feature and its statistical features based neural networks for RUL estimation.