DocumentCode :
631995
Title :
Research of pre-warning and diagnosis for transformer based on on-line monitoring devices
Author :
Rongping Guo ; Xiaohu Yan ; Qian Peng ; Yongxing Cao ; Hailong Zhang
Author_Institution :
Sichuan Electr. Power Res. Inst., Chengdu, China
fYear :
2013
fDate :
17-19 April 2013
Firstpage :
381
Lastpage :
385
Abstract :
The real-time pre-warning and fault diagnosis for transformer based on on-line monitoring devices is proposed in this paper. The values and growth rates of online monitoring variables, together with the information about ex-factory and hand-over tests and monitoring values and variables of similar equipment of the same substation, can be used to make accurate and in-time pre-warning for the transformer that may have default. The possible reason to the abnormal individual parameter was analyzed based on the fault diagnosis of the online monitoring variables. Comprehensive analysis was made on the oil chromatogram with improved three-ratio method, Duval´s triangle method and pictorial method. Then the reason to the transformer fault was diagnosed with the expert system integrated with multiple parameters to acquire detailed information, handling measure and relevant example of the fault. Finally, the feasibility and efficiency of the method proposed in this paper is demonstrated by the experiment.
Keywords :
chromatography; fault diagnosis; power transformer testing; substations; transformer oil; Duval´s triangle method; fault diagnosis; in-time pre-warning; oil chromatogram; on-line monitoring devices; online monitoring; pictorial method; real-time pre-warning; substation; three-ratio method; transformer fault; Maintenance engineering; Monitoring; Oil insulation; Partial discharges; Power transformer insulation; Transformer cores; fault diagnosis; on-line monitoring devices; real-time pre-warning; transformer;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON Spring Conference, 2013 IEEE
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4673-6347-1
Type :
conf
DOI :
10.1109/TENCONSpring.2013.6584476
Filename :
6584476
Link To Document :
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