Title :
The real-time fault diagnosis for transformers based on multi-scale STF
Author :
Lv, Feng ; Wang, Xiu-qing ; Jiao, Ren-Pu
Author_Institution :
Dept. of Electr., Hebei Normal Univ., China
Abstract :
Based on the theory of strong tracking filters, an online fault diagnosis method for transformer is given by combining state estimation and parameter identification. Computer simulations show that this method can effectively determine what kind of fault happens and which parameter is related to the fault. In addition, the parameter identification remains accurate when the fault happens.
Keywords :
fault diagnosis; parameter estimation; sensor fusion; state estimation; transformers; information fusion; online fault diagnosis method; parameter identification; real-time fault diagnosis; state estimation; strong tracking filters; transformer; Circuit faults; Computer simulation; Condition monitoring; Fault diagnosis; Fault location; Filtering theory; Filters; Insulation life; Parameter estimation; Power transformer insulation;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1264497
