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E. Fumeo¹, S. Terribile¹, D. Anguita¹, E. Massara² and N. Mazzino²

¹Department of Computer Science, Bioengineering, Robotics and Systems Engineering, Polytechnic School, University of Genoa, Italy
²Innovation Project, Ansaldo STS S.p.A., Genoa, Italy

doi:10.4203/ccp.110.309

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E. Fumeo, S. Terribile, D. Anguita, E. Massara, N. Mazzino, "A Data Fusion Approach based on Systems Integration for Axle Bearing Monitoring", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 309, 2016. doi:10.4203/ccp.110.309

Keywords: asset management, condition-based maintenance, data fusion, monitoring system, diagnostics system, system integrator, human machine interface.

Summary

In the context of condition-based maintenance (CBM) for railway transportation systems, the correlation of data coming from several heterogeneous sensors is gaining growing research interest: for this purpose, it is extremely important to study and deploy data fusion methodologies able to merge information coming both from wayside train monitoring and diagnostic systems and from on-board train monitoring systems. This paper describes an innovative data fusion approach based on a software systems integration for axle bearing CBM: a data fusion system composed of three modules, namely the data fusion application, the system integrator and a visualization system referred as the human machine interface have been developed. The results presented in this paper show the benefits in terms of maintenance costs reduction, risk management and safety, and the system proves to have a positive impact all over the railways systems.

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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: 110 PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE Edited by: J. Pombo Paper 309 A Data Fusion Approach based on Systems Integration for Axle Bearing Monitoring E. Fumeo¹, S. Terribile¹, D. Anguita¹, E. Massara² and N. Mazzino² ¹Department of Computer Science, Bioengineering, Robotics and Systems Engineering, Polytechnic School, University of Genoa, Italy ²Innovation Project, Ansaldo STS S.p.A., Genoa, Italy doi:10.4203/ccp.110.309 purchase the full-text of this paper Full Bibliographic Reference for this paper E. Fumeo, S. Terribile, D. Anguita, E. Massara, N. Mazzino, "A Data Fusion Approach based on Systems Integration for Axle Bearing Monitoring", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 309, 2016. doi:10.4203/ccp.110.309 Keywords: asset management, condition-based maintenance, data fusion, monitoring system, diagnostics system, system integrator, human machine interface. Summary In the context of condition-based maintenance (CBM) for railway transportation systems, the correlation of data coming from several heterogeneous sensors is gaining growing research interest: for this purpose, it is extremely important to study and deploy data fusion methodologies able to merge information coming both from wayside train monitoring and diagnostic systems and from on-board train monitoring systems. This paper describes an innovative data fusion approach based on a software systems integration for axle bearing CBM: a data fusion system composed of three modules, namely the data fusion application, the system integrator and a visualization system referred as the human machine interface have been developed. The results presented in this paper show the benefits in terms of maintenance costs reduction, risk management and safety, and the system proves to have a positive impact all over the railways systems. purchase the full-text of this paper (price £22) 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 £85 +P&P)
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