Condition Monitoring of DC-Link Capacitors Using Time-Frequency Analysis and Machine Learning Classification of Conducted EMI

Condition monitoring techniques for power electronics components are important for reducing maintenance costs and increasing reliability in systems such as aircraft. This article presents a noninvasive condition monitoring system that utilizes time-frequency analysis of conducted electromagnetic interference (EMI) to classify the health of the dc-link capacitor within a three-phase inverter. The approach proposes a combined EMI filter and measurement board which is placed on the dc bus of the inverter. This board filters conducted EMI effectively and enables the inverter to comply with MIL-STD-461 G. It also enables EMI measurements to be collected for condition monitoring applications. The EMI content obtained from this board is analyzed from 15-43 MHz during switching events using a continuous wavelet transform. These characteristic switching images are used to train support vector machine models that are able to classify dc-link health into one of five health stages with accuracy up to 100%.