DocumentCode
2736844
Title
Application of adaptive neuro fuzzy inference system to the partial discharge pattern recognition
Author
Guo, Canxin ; Zhang, Li ; Qian, Yong ; Huang, Chengjun ; Wang, Hui ; Yao, Linpeng ; Jiang, Xiuchen
Author_Institution
Dept. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
Volume
2
fYear
2009
fDate
20-22 Nov. 2009
Firstpage
729
Lastpage
732
Abstract
The application of adaptive neuro fuzzy inference system (ANFIS) to the partial discharge (PD) pattern recognition is presented in this paper. Four types of defect models are made according to the main reason of insulation failures in real power system. Experiments are carried out to acquire the sample data, from which eight statistical features are extracted to construct the ANFIS. Different characteristics of the proposed defect models are compared based on the extracted features. Then the ANFIS is trained by characteristic features. Testing samples are utilized to validate the performance of the recognition system. The result shows that ANFIS reaches a successful recognition rate in the application of PD pattern classification.
Keywords
adaptive systems; discharges (electric); fuzzy reasoning; pattern recognition; power system faults; statistical analysis; adaptive neuro fuzzy inference system; defect models; insulation failures; partial discharge pattern recognition; power system; statistical features; Circuit testing; Data mining; Feature extraction; Fuzzy logic; Fuzzy systems; Partial discharges; Pattern recognition; Power system modeling; System testing; Voltage; ANFIS; PD; features extraciton; pattern recognition; power apparatus;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-4754-1
Electronic_ISBN
978-1-4244-4738-1
Type
conf
DOI
10.1109/ICICISYS.2009.5358281
Filename
5358281
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