Critical Components Selection for a Prognostics and Health Management System Design: an Application to an Overhead Contact System
In recent years, improving quality of rail services by increasing availability, saving energy, and cutting the costs of infrastructure and rolling stock maintenance has become a central concern in the railway industry. Furthermore, considerable research efforts have been devoted to develop
monitoring and health management solutions for the rail transportation systems. Streaming data from trains, infrastructure and signaling systems became a key subject for an implementation of a predictive maintenance. Prognostics and Health Management (PHM) is an approach that aims to support a predictive maintenance program. Basically, the first step to develop a PHM system is to identify critical components. This paper emphasizes on the critical components selection step. It presents a methodology to identify the critical components for the design of a PHM solution. The proposed methodology is based on objectives definition for PHM and it is applied to an Overhead Contact System (OCS).
How to Cite
Dependable and Secure Computing, 1(1), 11–33.
Bucca, G., & Collina, A. (2015). Electromechanical interaction between carbon-based pantograph strip and copper contact wire: A heuristic wear model. Tribology International, 92, 47–56. http://doi.org/10.1016/j.triboint.2015.05.019
ISO/IEC (2003). Dependability management – Part 3-1: – Application Guide – Analysis techniques for dependability – Guide on methodology (ISO/IEC
Jardine, A. K. S., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance.
Mechanical Systems and Signal Processing, 20(7), 1483–1510. http://doi.org/10.1016/j.ymssp.2005.09.012
Lu, X., Shan, S., Tang, G., & Wen, Z. (2016). Survey on the Railway Telematic System for Rolling Stocks. In Y. Qin, L. Jia, J. Feng, M. An, & L. Diao (Eds.),
Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation (Vol. 378, pp. 645–656). Berlin,
Heidelberg: Springer Berlin Heidelberg. Retrieved from http://link.springer.com/10.1007/978-3-662-49370-0_67
Massat, J. (2007). Modélisation du comportement dynamique du couple pantographe-caténaire. Application à La Détection de Défauts Dans La
Caténaire [Simulation of Pantograph-Catenary Dynamic interaction–Application to Catenary Defect Detection]. Ecole Centrale de Lyon [doctoral Thesis].
Mathew, S., Das, D., Rossenberger, R., & Pecht, M. (2008). Failure mechanisms based prognostics. In Prognostics and Health Management, 2008. PHM 2008. International Conference on (pp. 1–6). IEEE.
Mosallam, A., Medjaher, K., & Zerhouni, N. (2015). Component based data-driven prognostics for complex systems: Methodology and applications. In Reliability Systems Engineering (ICRSE), 2015 First International Conference on (pp. 1–7). IEEE. Retrieved from http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7366504
SNCF Open Data. (n.d.). Retrieved August 26, 2016, from https://data.sncf.com/
Tixier, J., Dusserre, G., Salvi, O., & Gaston, D. (2002). Review of 62 risk analysis methodologies of industrial plants. Journal of Loss Prevention in the process industries, 15(4), 291-303.
Uckun, S., Goebel, K., & Lucas, P. J. (2008). Standardizing research methods for prognostics. In Prognostics and Health Management, 2008. PHM 2008. International Conference on (pp. 1–10). IEEE.
UIC, UIC 791-1: Maintenance guidelines for overhead contact lines, 1st edition of 2006. ISBN 2-7461-1093-8
Wang, L., & Nee, A. Y. C. (Eds.). (2009). Collaborative Design and Planning for Digital Manufacturing. London: Springer London. Retrieved from http://link.springer.com/10.1007/978-1-84882-287-0
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.