Title :
Investigation on fuzzy degree criterion of the fault diagnosis in electrical power equipment
Author :
Zhou, Long ; Tong, Xiao-jun ; Chen, Mian-yun
Author_Institution :
Wuhan Polytech. Univ., Wuhan
Abstract :
The choice of feature parameter is very important to the fault diagnosis of electrical power equipment. In this paper, the conception of fuzzy degree of two error diagnoses in fault diagnosis and the fuzzy criterion for fault feature parameter evaluation are provided based on fuzzy set theory. Finally, the effectiveness of this criterion is provided by an example. The examples show that the method can obtain better diagnosis results.
Keywords :
fault diagnosis; fuzzy set theory; power apparatus; electrical power equipment; fault diagnosis; fault feature parameter evaluation; fuzzy degree criterion; fuzzy set theory; Cybernetics; Entropy; Fault diagnosis; Fuzzy logic; Fuzzy neural networks; Fuzzy set theory; Information theory; Machine learning; Neural networks; Electrical power equipment; Fault diagnosis; Fuzzy degree criterion;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620606
