Electric Shock Fault Diagnosis of Low-Voltage Residual Current-Operated Protective Device

In order to diagnose the electric shock fault types of new-generation adaptive residual current operated protective devices (RCDs), a combination method based on local mean decomposition (LMD) amount of energy and support vector machine (SVM) is proposed in this study. First, LMD is applied to decompose the original electric shock signals into a finite number of product functions (PFs); then the former PFs containing the main features are selected to calculate the total energy. Second, SVM is used to solve the multi-class classification problem. The amount of energy of the PF component is considered as the input vector of the SVM, and particle swarm optimization (PSO) is used to optimize the model parameters. Experimental results show that the proposed method is effective in diagnosing animal or plant electric shock fault type, which provides a reliable theoretical basis for developing a new generation of adaptive RCDs. (C) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.