DocumentCode :
3359448
Title :
Similarity Analysis in Condition Evolution Rule of Transformer in Family Based on Clustering
Author :
Jin-Sha Yuan ; Xin-Ye Li
Author_Institution :
Dept. of Electron. & Commun. Eng., North China Electr. Power Univ. Baoding, Baoding
fYear :
2009
fDate :
27-31 March 2009
Firstpage :
1
Lastpage :
4
Abstract :
In integrated condition assessment, family quality is an factor affecting a transformer´s condition. If some devices in family have had default record, then the other transformer in family would have same default in future. And now, the affecting degree by family default factor is subjectively decided by expert´s experience. This paper collected power transformer experimental data in same factory and with same type, analyzed condition evolution similarity of power transformer in family based on clustering technology to mine the potential evolution rule. To make the clustering result more accurate, this paper improved the similarity criterion in clustering algorithm, proposed line slope distance of condition evolution as line shape similarity criterion, used both data distance criterion and line slope distance criterion to cluster transformer experiment data with same factory and same type in reality. It then analyzed the condition evolution of a power transformer according to the family condition evolution rule. The result is the same with the reality.
Keywords :
condition monitoring; power transformers; clustering technology; data distance criterion; family default factor; integrated condition assessment; line shape similarity criterion; line slope distance criterion; power transformer; transformer condition evolution rule; Clustering algorithms; Power engineering and energy; Power system analysis computing; Power system stability; Power system transients; Power transformers; Production facilities; Shape; Stability analysis; Unsupervised learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-2486-3
Electronic_ISBN :
978-1-4244-2487-0
Type :
conf
DOI :
10.1109/APPEEC.2009.4918747
Filename :
4918747
Link To Document :
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