| Title |
Classification of High-Impedance Faults based on the Chaotic Attractor Patterns |
| Authors |
신승연(Shin, Seung-Yeon) ; 공성곤(Kong, Seong-Gon) |
| Keywords |
카오스 어트랙터 ; 패턴분류 ; 고저항 지락사고 ; RBFN 신경회로망 HIF |
| Abstract |
This paper presents a method of recognizing high impedance fault(HIF) of electrical power systems and classifying fault patterns based on chaos attractors. Two dimensional chaos attractors are reconstructed from neutral point current waveforms. Reliable features for HIF pattern classification are obtained from the chaos attractors. Radial basis function network, trained with two types of HIF data generated by the electromagnetic transient program and measured form actual faults. The RBFN successfully classifies normal and the three types of fault patterns according to the features generated from the chaos attractors. |