DC-DC Converter Faults Identification Based on Electromagnetic Emission

When the faults of electronic components in DC-DC Converter exist, they will harm the converter and produce unpredictable electromagnetic emission. To locate those faults, a new method is proposed to identify the structural faults of electronic components in DC-DC converter based on their electromagnetic emission in this paper. In this method, an equivalent circuit model with considering the parasitic parameters of the converter is firstly constructed. Therefore, this model is more accurate than the traditional ones, which does not consider the effects of parasitic parameters on electromagnetic emission. Then, to extract the faulty features, the voltages at three special nodes in the circuit model were analyzed, diagnosing more types of singular faults and their combined faults of components. Last, the BP neural network was used to train the fault model and then used to identify the faulty electronic components in DC-DC converter. The results show that more types of fault can be effectively identified and the accuracy is higher than 98% in this method.