Design of Cyber-Physical Systems Architecture for Prognostics and Health Management of High-speed Railway Transportation Systems
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Abstract
The high-speed railway (HSR) transportation system in China has been growing rapidly during the past decade. In 2016, the total length of HSR in China has reached to 22,000 kilometers, and there are over 2,000 pairs of high speed trains operating daily. With the advancement of design and manufacturing technologies, the reliability and construction costs have been improved significantly. However, there is still great need for reduction of their operation and maintenance costs. With such incentive, a pilot project has been launched to develop a prognostics and health management system for rolling stock to transform the maintenance paradigm from preventive to predictive maintenance. Considering the high task variety and big data environment in HSR real-time monitoring system, a cyberphysical system (CPS) architecture is proposed as the framework for its PHM system. This paper reviews the needs of predictive maintenance for the HSR system, and then present a concept design of the CPS-enabled smart operation and maintenance system.
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Cyber-Physical Systems, High-speed Railway, prognostics and health management (PHM)
B. Feigenbaum (2013). High-Speed Rail in Europe and Asia: Lessons for the United States.
J. Lee, H. D. Ardakani, S. Yang, and B. Bagheri (2015). Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia CIRP, vol. 38, pp. 3–7.
J. Lee, H. Kao, and S. Yang (2014). Service innovation and smart analytics for Industry 4. 0 and big data environment. Procedia CIRP, vol. 16, pp. 3–8.
A. T. S. Worth and B. Escartin-Claveria (2014). Alstom's approach to railway condition monitoring. 6th IET Conference on Railway Condition Monitoring Birmingham, 2014. pp. 1-6. doi: 10.1049/cp.2014.0991.
Lu X., Shan S., Tang G., Wen Z. (2016) Survey on the Railway Telematic System for Rolling Stocks. In: Qin
Y., Jia L., Feng J., An M., Diao L. Proceedings of the 2015 International Conference on Electrical and Information Technologies for Rail Transportation. Lecture Notes in Electrical Engineering, vol 378. Springer, Berlin, Heidelberg
E. Incorporated (2013). Foundations for Innovation in Cyber- Physical Systems.
H. Kao, W. Jin, D. Siegel, and J. Lee (2015). A Cyber Physical Interface for Automation Systems— Methodology and Examples. Machines, vol. 3, pp. 93–106.
J. L. Behrad Bagheri, Shanhu Yang, Hung-An Kao (2015). Cyber-physical Systems Architecture for Self- Aware Machines in Industry 4.0 Environment Cyber-Physical Environment. International Federation of Automatic Control, 2015, no. January, pp. 1622–1627.
E. R. Lapira (2012). Fault Detection in a Network of Similar Machines using Clustering Approach.
T. Wang, J. Yu, D. Siegel, and J. Lee (2008). A Similarity- Based Prognostics Approach for Remaining Useful Life Estimation of Engineered Systems. 2008 International Conference on Prognostics and Health Management, pp. 4–9.
J. Liu, D. Djurdjanovic, J. Ni, N. Casoetto, and J. Lee (2007). Similarity based method for manufacturing process performance prediction and diagnosis. Computers in Industry, vol. 58, pp. 558–566.