Title :
Fault Diagnosis Model of Transformer Based on Immune Algorithm
Author :
Yu, Jie ; Zhou, Hao
Author_Institution :
Coll. of Electr. Eng., Zhejiang Univ., Hangzhou
Abstract :
Condition diagnose mode is one of the key steps in carrying out electric equipments condition maintenance. Based on the concept and theory of immunity in bioscience and simulation of the eliminating function of immune antibody system to antigen, this paper analyses the relationship between matrix singular value decomposition with the formal model of antigen-antibody combination. Then authors put forward the fault diagnosis of electric equipments using minimum energy antigen-antibody combination. Typical fault diagnosis of dissolved gas in the oil of transformers has proved the effectiveness and feasibility of this method, the method has a promising applicable future in fault diagnosis application
Keywords :
fault diagnosis; power transformers; singular value decomposition; transformer oil; bioscience; condition diagnose mode; condition maintenance; dissolved gas; electric equipments; fault diagnosis model; immune algorithm; immune antibody system; matrix singular value decomposition; minimum energy antigen-antibody combination; transformer oil; Electrical safety; Fault diagnosis; Immune system; Matrix decomposition; Monitoring; Oil insulation; Power system faults; Power system stability; Safety devices; Singular value decomposition; DGA; antibody; antigen; electric equipment; fault diagnoses; immune algorithm; matrix decomposition; power system; transformer; transformer oil;
Conference_Titel :
Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES
Conference_Location :
Dalian
Print_ISBN :
0-7803-9114-4
DOI :
10.1109/TDC.2005.1547056
