Title :
A hybrid intelligent system for fault detection in power systems
Author :
Mori, Hiroyuki ; Aoyama, Hikaru ; Yamanaka, Toshiyuki ; Urano, Shoichi
Author_Institution :
Dept. of Electr. & Electron. Eng., Meiji Univ., Kawasaki, Japan
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper proposes a method for fault detection with a preconditioned artificial neural network. The proposed method makes use of FFT and deterministic annealing (DA) clustering as a precondition technique. The proposed method is tested in a sample system
Keywords :
fast Fourier transforms; knowledge based systems; multilayer perceptrons; pattern clustering; power system analysis computing; power system faults; simulated annealing; DA clustering; FFT; deterministic annealing clustering; fault detection; hybrid intelligent system; power systems; preconditioned artificial neural network; Artificial neural networks; Circuit faults; Control systems; Electrical fault detection; Hybrid intelligent systems; Hybrid power systems; Power system control; Power system faults; Power system planning; Power system security;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007472
