Title :
Power Transformer Dga Integrated Diagnosis System Based on Oracle Database
Author :
Song Bin ; Chen Mingbang
Author_Institution :
Sch. of Electr. Eng., Wuhan Univ., Wuhan
Abstract :
In the paper, a transformer dissolved gas analysis in oil (DGA) fault integrated diagnosis system based on Oracle is developed, and its modules are introduced. Fault diagnosis of transformer is based on three-ratio-method, grey relational entropy, fuzzy clustering, Artificial Neural Network, featured by its analytic hierarchy process to integrated analysis, so as to perfect existing diagnosis methods. The system has realized each module function by layers, and it can diagnose fault in power transformer. The system also can provide figure display and friendly help module. The effectiveness of the system is verified by DGA data in Yunnan Power Grid and other DGA data.
Keywords :
database management systems; decision making; electric machine analysis computing; fault diagnosis; power transformers; DGA; Oracle database; Yunnan power grid; analytic hierarchy process; artificial neural network; dissolved gas analysis; fuzzy clustering; grey relational entropy; integrated diagnosis system; power transformer; three-ratio-method; Artificial neural networks; Dissolved gas analysis; Entropy; Fault diagnosis; Fuzzy neural networks; Oil insulation; Petroleum; Power transformers; Relational databases; Spatial databases;
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.2009.4918617
