Title :
Fault Diagnosis of Power Transformer Based on Heuristic Reduction Algorithm
Author :
Li Zhong ; Yuan Jinsha ; Su Peng
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Baoding
Abstract :
Reduction of knowledge is an important topic on studies of rough set. In this paper, we present a heuristic reduction algorithm based on the dependency of a knowledge decision system for power transformer fault diagnosis. A group of minimal decision rules are produced from the consistency of the system attributes. A lot of real fault samples were analyzed by this algorithm. The experimental results show that the proposed algorithm is effective and efficient.
Keywords :
fault diagnosis; knowledge based systems; power engineering computing; power transformers; rough set theory; fault diagnosis; heuristic reduction algorithm; knowledge decision system; minimal decision rules; power transformer; rough set; Algorithm design and analysis; Artificial intelligence; Artificial neural networks; Fault diagnosis; Heuristic algorithms; Intelligent networks; Knowledge engineering; Power engineering and energy; Power transformers; Set theory;
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
DOI :
10.1109/APPEEC.2009.4918375
