scholarly journals Oil-immersed Power Transformer Internal Fault Diagnosis Research Based on Probabilistic Neural Network

2016 ◽  
Vol 83 ◽  
pp. 1327-1331 ◽  
Author(s):  
Shenghao Yu ◽  
Dongming Zhao ◽  
Wei Chen ◽  
Hui Hou
Author(s):  
G.S. Naganathan ◽  
M. Senthilkumar ◽  
S. Aiswariya ◽  
S. Muthulakshmi ◽  
G. Santhiya Riyasen ◽  
...  

2010 ◽  
Vol 30 (3) ◽  
pp. 783-785 ◽  
Author(s):  
Zhong-yang XIONG ◽  
Qing-bo YANG ◽  
Yu-fang ZHANG

2013 ◽  
Vol 756-759 ◽  
pp. 3804-3808
Author(s):  
Zhi Mei Duan ◽  
Jia Tang Cheng

In order to improve the accuracy of fault diagnosis of power transformer, in this paper, a method is proposed that optimize the weight of BP neural network by adaptive mutation particle swarm optimization (AMPSO). According to the characteristic of transformer fault, the optimized neural network is used to diagnose fault of the power transformer. Individual particles action is amended by this algorithm and local minima problems of the standard PSO and BP network are overcooked. The experimental results show that, the method can classify transformer faults, and effectively improve the fault recognition rate.


Author(s):  
Sheng Zhu ◽  
Min Keng Tan ◽  
Renee Ka Yin Chin ◽  
Bih Lii Chua ◽  
Xiaoxi Hao ◽  
...  

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