An integrated method of ANFIS and Dempster-Shafer theory for fault diagnosis of power transformer

• Published in: IEEE transactions on dielectrics and electrical insulation Vol. 25; no. 1; pp. 360 - 371
• Main Authors: Kari, Tusongjiang, Gao, Wensheng, Zhao, Dongbo, Zhang, Ziwei, Mo, Wenxiong, Wang, Yong, Luan, Le
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: adaptive nuero fuzzy inference system; Adaptive systems; Artificial neural networks; Consistency; Dempster Shafer theory; Diagnostic systems; dissolved gas analysis; Fault detection; Fault diagnosis; Fuzzy logic; Fuzzy systems; Gas analysis; Noise measurement; Partial discharges; Power transformers; Reliability theory; transformer fault diagnosis; Transformers

Dissolved gas analysis (DGA) approach is extensively applied to detect incipient faults of power transformers. This paper presents a novel DGA method for power transformer incipient fault diagnosis based on integrated adaptive neuro fuzzy inference system (ANFIS) and Dempster-Shafer Theory (DST). Fo...