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S. Barmada, M. Tucci, F. Romano, "Arc Detection and Classification in Pantograph Catenary Systems by the use of Clustering Techniques", in J. Pombo, (Editor), "Proceedings of the Second International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 149, 2014. doi:10.4203/ccp.104.149

Keywords: railway systems, pantograph-catenary system, predictive maintenance, time series clustering, electric arc, signal processing.

Summary

In this paper the authors employ advanced signal processing techniques, namely clustering algorithms, to the analysis of currents and voltages collected by high speed trains in order to detect the presence and the quantity of electric arcs in the pantograph-catenary current collection system. The analysis is performed on a set of data recorded during different test runs; the data includes voltage, current and a phototube signal detecting the presence of electric arcs. The proposed analysis groups the data in different clusters, which are then related to the real presence of arcs by the use of the phototube data. The results show the physical meaning of the clusters and the potential of the technique for its use in a preventive maintenance technique.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 104 PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 149 Arc Detection and Classification in Pantograph Catenary Systems by the use of Clustering Techniques S. Barmada¹, M. Tucci¹ and F. Romano² ¹DESTEC, University of Pisa, Italy ²Trenitalia s.p.a., Italy doi:10.4203/ccp.104.149 purchase the full-text of this paper Full Bibliographic Reference for this paper S. Barmada, M. Tucci, F. Romano, "Arc Detection and Classification in Pantograph Catenary Systems by the use of Clustering Techniques", in J. Pombo, (Editor), "Proceedings of the Second International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 149, 2014. doi:10.4203/ccp.104.149 Keywords: railway systems, pantograph-catenary system, predictive maintenance, time series clustering, electric arc, signal processing. Summary In this paper the authors employ advanced signal processing techniques, namely clustering algorithms, to the analysis of currents and voltages collected by high speed trains in order to detect the presence and the quantity of electric arcs in the pantograph-catenary current collection system. The analysis is performed on a set of data recorded during different test runs; the data includes voltage, current and a phototube signal detecting the presence of electric arcs. The proposed analysis groups the data in different clusters, which are then related to the real presence of arcs by the use of the phototube data. The results show the physical meaning of the clusters and the potential of the technique for its use in a preventive maintenance technique. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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