Title :
Transformer Insulation Fault Diagnosis Method Based on Rough Set and Fuzzy Set and Evidence Theory
Author :
Su, Hongsheng ; Li, Qunzhan
Author_Institution :
Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu
Abstract :
To deal with incomplete and indeterminate information as well as fuzzy information in transformer fault diagnosis, the paper proposes a novel transformer insulation fault diagnosis method based on rough set and fuzzy set and evidence theory. The method firstly establishes rough model with two-universe of fault sets and symptom sets, and makes symptom sets fuzzy. Then based on the relationships between two universes, the largest fault set is sought based on the known fault symptom information. Finally, the best diagnosis result is achieved based on evidence reasoning. Actual example shows that the proposed method possesses good robustness, and is an effective transformer fault diagnosis method and processing technique for uncertain and incomplete information
Keywords :
case-based reasoning; fault diagnosis; fuzzy set theory; power engineering computing; power transformer insulation; rough set theory; evidence reasoning; evidence theory; fault sets; fault symptom information; fuzzy set theory; rough set theory; symptom sets; transformer insulation fault diagnosis; Automation; Dielectrics and electrical insulation; Fault diagnosis; Fuzzy set theory; Fuzzy sets; Intelligent control; Power transformer insulation; Robustness; evidence theory; fault diagnosis; fuzzy set; tough set; transformer;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714112