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Power switching device is the core component of inverter, but it is prone to open circuit fault, so it is necessary to study the fault diagnosis method.Aiming to the open-circuit fault of power electronic devices in Neutral-point Clamped(NPC) three-level inverter,a diagnosis approach based on Ensemble Empirical Mode Decomposition(EEMD) with fuzzy entropy and Kernel Extreme Learning Machine(KELM) with Particle Swarm Optimization(PSO).Firstly,the bridge three-phase voltage of power switch devices are sampled as the characteristic signals to classify different fault types.Afterwards,the feature parameters of the fault diagnosis is extracted by EEMD with fuzzy entropy.Finally,taking the feature parameters in various fault situations as training samples and testing samples,the PSO-KELM algorithm is utilized to identify different kinds of faults and output the consequences of fault diagnosis.Through MATLAB simulation experiments,the capability of the proposed method is more than 98%.Through comparing with other method,the effectiveness and superiority of the proposed method is proved.