| Title |
A Study on the Extraction of Fundamental Frequency Components in the Transient Wave Signals Using Artificial neural networks |
| Keywords |
신경회로망 맵핑필터 ; 디지탈 거리계전 ; 일반화 델타규칙 Neural Networks Mapping Filter ; Digital Distance Relaying ; GDR |
| Abstract |
This paper presents a filtering method using neural networks to extract fundamental frequency components of the transient wave signals in power systems. Based on the ability of multilayer feedforward neural networks to approximate any continuous function, a neural networks mapping filter is proposed for the protective distance relaying systems to extract the effective components efficiently. A characteristic feature of this mapping filter is composed of the multilayer perceptron neural networks which are trained by using random signals and those are mapped to the DFT filtering computational structure by GDR(Generalized Delta Rule). The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks. |