Abstract
Focusing on the fault diagnosis precision of subway auxiliary inverter, the diagnosis method based on genetic algorithm (GA) and least squares support vector machine (LSSVM) is proposed in this paper. First, the optimal parameters of LSSVM are obtained by GA with global search capability and the diagnosis model of the optimized LSSVM is established, then the empirical mode decomposition (EMD) is introduced to decompose the fault signal into several intrinsic mode functions (IMF), and finally we will extract the approximate entropy of each IMF as the fault feature which will be applied to test the performance of the diagnosis model. Simulation results have proved that the proposed diagnosis method is feasible to recognize each fault and has achieved higher precision.
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