Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.3233/IFS-2010-0471 | Journal of Intelligent and Fuzzy Systems |
Keywords | Field | DocType |
fault location,SVM network,analog electrical circuit,electrical circuit,electrical filter,proposed solution,Support Vector Machine,accessible terminal voltage,different structure,faulty element,soft fault location | Stuck-at fault,Electrical network,Fault coverage,Support vector machine,Artificial intelligence,Artificial neural network,Classifier (linguistics),Fault model,Mathematics,Machine learning,Fault indicator | Journal |
Volume | Issue | ISSN |
22 | 1 | 1064-1246 |
Citations | PageRank | References |
8 | 0.96 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert Salat | 1 | 14 | 2.23 |
| Stanislaw Osowski | 2 | 231 | 37.05 |
| SałatRobert | 3 | 8 | 0.96 |
| OsowskiStanisław | 4 | 8 | 0.96 |