DocumentCode :
3011009
Title :
A smart on-line over-voltage layered identification system
Author :
Du Lin ; Chen Huan ; Liu Jun
Author_Institution :
State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ., Chongqing, China
fYear :
2012
fDate :
23-27 Sept. 2012
Firstpage :
874
Lastpage :
877
Abstract :
This paper proposes an effective smart on-line over-voltage identification system based on a new layered recognition structure. The over-voltage is a main and great threat for the safety and stability of electric system. It´s very helpful to analyze and identify over-voltage for improving power system insulation coordination. Through analysis of filed over-voltage data recorded by over-voltage on-line monitoring system, an over-voltage layered identification structure is presented for eleven kinds of common over-voltage. The wavelet transform and singular value decomposition theory are used to extract features of over-voltage. In consideration of the requirements of over-voltage recognition, the least square support vector machine is employed as the classifier to build a layered identification model, and the grid search algorithm is adopted to optimize the parameters of support vector machine to improve classification rate. The filed data testing results show that this system is feasible and promising for engineering application.
Keywords :
feature extraction; insulators; least squares approximations; overvoltage protection; power system measurement; singular value decomposition; support vector machines; wavelet transforms; classification rate; electric system; feature extraction; grid search algorithm; layered recognition structure; least square support vector machine; over-voltage data; over-voltage on-line monitoring system; over-voltage recognition; power system insulation coordination; singular value decomposition theory; smart on-line over-voltage layered identification system; wavelet transform; Discrete wavelet transforms; Feature extraction; Lightning; Matrix decomposition; Time frequency analysis; least square support vector machine; over-voltage; pattern identification; singular value decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Condition Monitoring and Diagnosis (CMD), 2012 International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4673-1019-2
Type :
conf
DOI :
10.1109/CMD.2012.6416290
Filename :
6416290
Link To Document :
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