Fault Detection of Power Electronic Circuit using Wavelet Analysis in Modelica

In more electric aircrafts (MEA) the electric power network is important for the reliability. To prevent severe faults it is the key issue to identify the faults in the early stage before a complete failure happens. In this paper an early stage fault detection method using wavelet multi-resolution analysis (MRA) for a regulated buck DC-DC converter is studied. Specifically, the electrolyte input capacitor is diagnosed. The study was carried out using simulation with Modelica / Dymola. The fault features that were extracted from different levels of wavelet decomposition provided clear information for both fast and slow occurring faults. This method showed significant advantages compared with filter techniques. It is concluded that wavelet transform is a suitable tool for early stage fault detection of the power electronics in MEA. In addition, the simulation language Modelica provides a convenient possibility for the quick design of fault detection strategy.

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