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S.P. Lin¹, K. Kimoto², Y. Suda¹, A. Iwamoto³, T. Saito³, K. Yano³, M. Mizuno⁴, M. Tanimoto⁵ and K. Nagasawa⁵

¹Institute of Industrial Science, The University of Tokyo, Japan
²Department of Mechanical Engineering, The University of Tokyo, Japan
³Tokyo Metro, Japan
⁴Nippon Steel & Sumitomo Metal, Japan
⁵Nippon Steel & Sumikin Technology, Japan

doi:10.4203/ccp.110.248

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S.P. Lin, K. Kimoto, Y. Suda, A. Iwamoto, T. Saito, K. Yano, M. Mizuno, M. Tanimoto, K. Nagasawa, "A Study on the Application of Big Data Analytics in Railways Systems", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 248, 2016. doi:10.4203/ccp.110.248

Keywords: condition monitoring, wheel load, lateral force, safety, big data, machine learning, naive Bayes classifier.

Summary

Recently, big data analytics has been applied in various fields with the development of information technology and analysis tools. However, there are few examples of big data analytics in the field of railway mechanical systems, because vehicle performance is evaluated using motion analysis or experiments under specific conditions. By contrast, condition monitoring systems are introduced in the railway systems, and these monitoring systems enable big data to be accumulated during commercial operations. In this paper, the big data of running records in railway systems are analyzed by using a naive Bayes classifier, one of the methods of big data analytics, and the individualities of railway vehicles are identified.

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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 248 A Study on the Application of Big Data Analytics in Railways Systems S.P. Lin¹, K. Kimoto², Y. Suda¹, A. Iwamoto³, T. Saito³, K. Yano³, M. Mizuno⁴, M. Tanimoto⁵ and K. Nagasawa⁵ ¹Institute of Industrial Science, The University of Tokyo, Japan ²Department of Mechanical Engineering, The University of Tokyo, Japan ³Tokyo Metro, Japan ⁴Nippon Steel & Sumitomo Metal, Japan ⁵Nippon Steel & Sumikin Technology, Japan doi:10.4203/ccp.110.248 purchase the full-text of this paper Full Bibliographic Reference for this paper S.P. Lin, K. Kimoto, Y. Suda, A. Iwamoto, T. Saito, K. Yano, M. Mizuno, M. Tanimoto, K. Nagasawa, "A Study on the Application of Big Data Analytics in Railways Systems", in J. Pombo, (Editor), "Proceedings of the Third International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Stirlingshire, UK, Paper 248, 2016. doi:10.4203/ccp.110.248 Keywords: condition monitoring, wheel load, lateral force, safety, big data, machine learning, naive Bayes classifier. Summary Recently, big data analytics has been applied in various fields with the development of information technology and analysis tools. However, there are few examples of big data analytics in the field of railway mechanical systems, because vehicle performance is evaluated using motion analysis or experiments under specific conditions. By contrast, condition monitoring systems are introduced in the railway systems, and these monitoring systems enable big data to be accumulated during commercial operations. In this paper, the big data of running records in railway systems are analyzed by using a naive Bayes classifier, one of the methods of big data analytics, and the individualities of railway vehicles are identified. 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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