A Novel Approach to Fault Classification of Power Transmission Lines Using Singular Value Decomposition and Fuzzy Reasoning Spiking Neural P Systems

A novel approach for classifying different types of faults occurring in power transmission lines is proposed by considering wavelet transform, singular value decomposition and Fuzzy Reasoning Spiking Neural P Systems (FRSNPS). In this approach, singular value decomposition in wavelet domain is used to extract features of fault current components recorded from power transmission lines; FRSNPS is applied to build the fault type classification model. Several cases with different fault types in power transmission lines are considered in the simulation experiments to verify the effectiveness of the proposed approach. The robustness to noise and to parameters of power transmission lines is also discussed.