DocumentCode :
190245
Title :
Classification of pollution severity on insulator model using Recurrence Quantification Analysis
Author :
Chaou, K.A. ; Mekhaldi, A. ; Teguar, M.
Author_Institution :
Laboratoire de Recherche en Electrotechnique, Ecole Nationale Polytechnique of Algiers, Algeria, 10 Avenue Hassen Badi, B.P 182, El-Harrach, 16200 Algiers, Algeria
fYear :
2014
fDate :
14-17 April 2014
Firstpage :
1
Lastpage :
5
Abstract :
In this work, a novel approach is established in order to investigate and monitor the performance of high voltage insulators. Since leakage current (LC) waveforms are intimately linked to pollution severity, it is primordial to study and investigate leakage current characteristics during the entire contamination process. In this paper, performance of a plane model insulator is studied through a number of laboratory tests under various levels of pollution contamination. LC waveforms are investigated through a nonlinear method called “Recurrence Quantification Analysis” (RQA). This method revealed successfully the non-linear characteristics of LC for identifying the dynamic behaviors on the insulator surface. Moreover, RQA indicators are found to be directly linked to the contamination severity. Thus, mean values of these indicators are computed and used as an input to three different classification algorithms (k-nearest neighbors, Naïve Bayes, Support Vector Machines) in order to classify contamination severity.
Keywords :
Insulator model; Recurrence Quantification Analysis; classification algorithms; feature extraction; leakage current;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
T&D Conference and Exposition, 2014 IEEE PES
Conference_Location :
Chicago, IL, USA
Type :
conf
DOI :
10.1109/TDC.2014.6863188
Filename :
6863188
Link To Document :
بازگشت