Title :
A Method of Diagnosing Power Transformer´s Fault Based on Fuzzy c and Immune Genetic Algorithm
Author :
Zhang Bide ; Li Yanrui ; Lin Zhaohui ; Fang Chunen
Author_Institution :
Sch. of Electr. Eng. & Inf., Xihua Univ., Chengdu
Abstract :
The local best solution is often gotten by fuzzy c. But the whole best solution can be gotten by immune genetic algorithm (IGA) effectively. In this paper, a new method that integrates fuzzy c with IGA is put forward for fault diagnosis of power transformer. The method converts the problem about minimum for fuzzy c to the problem about maximum for IGA. From the practice, the new method can diagnose the power transformerpsilas faults effectively. It has higher reliability and practicability.
Keywords :
fault diagnosis; fuzzy set theory; genetic algorithms; power transformers; fault diagnosis; fuzzy c algorithm; immune genetic algorithm; power transformer; Automation; Clustering methods; Dissolved gas analysis; Fault diagnosis; Genetic algorithms; IEC; Power engineering computing; Power system analysis computing; Power system faults; Power transformers; fault diagnosis; fuzzy c; immune genetic algorithm; power transformer;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
DOI :
10.1109/ICICTA.2008.235
