DocumentCode :
3573701
Title :
Fault Diagnosis of Power Transformer Insulation Based on Fuzzy Normal Partition and Logic Reasoning
Author :
Xie, Li ; Zhou, Long ; Tong, Xiao-jun ; Chen, Mian-yun
Author_Institution :
Wuhan Polytech Univ., Wuhan
Volume :
2
fYear :
2007
Firstpage :
1081
Lastpage :
1085
Abstract :
A new diagnosis method based on fuzzy normal partition and logic reasoning for insulation fault of power transformer is put forward in this paper. First, according to the normal distribution functions, fuzzy processing of the insulation diagnosis parameters and diagnosis conclusions is realized. Secondly, the insulation diagnosis knowledge is acquired and the reasoning rules are built. Finally, the reasoning results are gotten by applying fuzzy reasoning in fault diagnosis. The method may resolve the problem that the relations between actual test data and diagnosis conclusions are difficult to describe and improve the reasoning efficiency. Moreover, the method increases the accuracy of fault diagnosis and maneuverability by actual computation.
Keywords :
fault diagnosis; formal logic; fuzzy reasoning; normal distribution; power engineering computing; power system faults; power transformer insulation; fault diagnosis; fuzzy normal partition; fuzzy reasoning; insulation fault; logic reasoning; normal distribution functions; power transformer fault; power transformer insulation; reasoning rules; Dielectrics and electrical insulation; Fault diagnosis; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Gaussian distribution; Machine learning; Power system reliability; Power transformer insulation; Power transformers; Fault diagnosis; Fuzzy partition; Logic reasoning; Power transformer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370304
Filename :
4370304
Link To Document :
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