Journal of the Washington Academy of Sciences, Spring 2012

Anomaly Detection for Insulated Gate Bipolar Transistor (IGBT) under Power Cycling using Principal Component Analysis and K-Nearest Neighbour Algorithm

Edwin Sutrisno, Qingguo Fan, Diganta Das and Michael Pecht
University of Maryland, College Park, MD 20742, USA


Insulated Gate Bipolar Transistor (IGBT) is a power electronic transistor used in medium to high power applications such as hybrid cars, railway traction motors, switch mode power supplies, and wind turbines. As more IGBTs find their application into larger and complex systems, the ability to detect and predict failures in IGBTs can provide a key advantage in driving down cost of maintenance and improving system availability and safety. This paper briefly discusses the common failure modes found in IGBTs under power cycling along with the experimental set up. Several electrical parameters are extracted and analysed for fault using principal component analysis (PCA) and k-nearest neighbour (KNN) classification. The proposed algorithm is successfully shown to detect faults just before the IGBTs enter a final degradation stage toward failure.

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