Support Vector Machine for soft fault location in electrical circuits

Article type: Research Article

Authors: Sałat, Robert | Osowski, Stanisław

Affiliations: Warsaw University of Life Sciences, ul. Nowoursynowska 166, Poland | Warsaw University of Technology and Military University of Technology, Warsaw, ul. Koszykowa, Poland

Note: [] Corresponding author. Stanisław Osowski, Warsaw University of Technology and Military University of Technology, 00-661 Warsaw, Koszykowa 75, Poland. Tel.: +4822 234 7235; Fax: +4822 234 5642; E-mail: [email protected]

Abstract: The paper is concerned with the application of Support Vector Machine (SVM) to the fault location in the analog electrical circuits. The recognition of fault is based on the measurements of the accessible terminal voltage and current of the network at the set of frequencies. The SVM network is applied as the recognizing system and as the classifier. The important feature of the proposed solution is its high accuracy and great speed of operation. Once the network has been trained, the recognition of fault is achieved immediately, irrespective of the size of the circuit. Thus the solution is suited for real time applications for fault location in electrical circuits. The numerical results of recognition of faulty elements in two different structures of electrical filters are presented and discussed in the paper.

Keywords: Parametric fault recognition in analog circuits, neural network, Support Vector Machine

DOI: 10.3233/IFS-2010-0471

Journal: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 1, pp. 21-31, 2011