Title :
Application of rough set and genetic algorithm to transformer fault diagnosis
Author :
Zhu, Ji ; Yu, Ying
Author_Institution :
Dept. of Autom., Shanghai Univ., Shanghai, China
Abstract :
A genetic algorithm combined with theories of rough set is proposed in the process of fault diagnosis of power transformer. Then by the process of value reducing, the fault diagnosis rules are extracted from the minimal decision table obtained from the algorithm. Besides, the feasibility of the generalized rules for power transformer fault diagnosis and the efficiency of the algorithm are illustrated with two specific examples.
Keywords :
fault diagnosis; genetic algorithms; power transformers; rough set theory; decision table; fault diagnosis process; genetic algorithm; power transformer; rough set theories; transformer fault diagnosis; Fault diagnosis; Gases; Genetic algorithms; Hydrocarbons; Information systems; Oil insulation; Power transformers;
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
DOI :
10.1109/IWACI.2011.6159963
