Fault Types-Classification and Section Discrimination Algorithm using Neuro-Fuzzy in Combined Transmission Lines

뉴로-퍼지를 이용한 혼합송전선로에서의 고장종류 및 고장구간 판별 알고리즘

It is important to classily fault types and discriminate fault section by any detecting technique for combined transmission lines. This paper proposes the technique to classify the fault types and fault section using neuro-fuzzy systems. Neuro-fuzzy systems are composed of two parts to perform different works. First, neuro-fuzzy system for fault type classification is performed with approximation coefficient of currents obtained by wavelet transform. Another neuro-fuzzy system discriminates the fault section between overhead and underground with detail coefficients of voltage and current. In this paper, neuro-fuzzy system shows the excellent results for classification of fault types and discrimination of fault section.