Title : 
Study on Power Transformer Fault Diagnosis Based on Niche Genetic Algorithm
         
        
            Author : 
Zhao, Jiyin ; Zheng, Ruirui ; Dong, Haihong
         
        
            Author_Institution : 
Coll. of Electromech. & Inf. Eng., Dalian Nat. Univ., Dalian, China
         
        
        
        
        
        
        
            Abstract : 
Power transformer fault diagnosis is the key technology of electric power system. Niche genetic algorithm (NGA) was introduced to optimize adaptive-learning-rate-momentum back propagation (BP) network. NGA-BP model was established and applied to power transformer fault diagnosis. Compared with BP network, NGA-BP network has a better performance on convergent speed and stability. The experimental results demonstrate that fault diagnosis precision of NGA-BP network is 90%, which is higher than BP network.
         
        
            Keywords : 
backpropagation; fault diagnosis; genetic algorithms; power systems; power transformers; adaptive learning rate momentum; back propagation network; electric power system; fault diagnosis; niche genetic algorithm; power transformer; Artificial neural networks; Dissolved gas analysis; Educational institutions; Fault diagnosis; Gases; Genetic algorithms; Genetic engineering; Oil insulation; Power transformer insulation; Power transformers; BP neural network; dissolved gas analysis; genetic algorithn; niche; power transformer diagnosis;
         
        
        
        
            Conference_Titel : 
Natural Computation, 2009. ICNC '09. Fifth International Conference on
         
        
            Conference_Location : 
Tianjin
         
        
            Print_ISBN : 
978-0-7695-3736-8
         
        
        
            DOI : 
10.1109/ICNC.2009.141