NDLI: Temporal association rule mining for the preventive diagnosis of onboard subsystems within floating train data framework

Content Provider	IEEE Xplore Digital Library
Author	Sammouri, W. Come, E. Oukhellou, L. Aknin, P. Fonlladosa, C.-E. Prendergast, K.
Copyright Year	2012
Description	Author affiliation: Université Paris-Est, IFSTTAR, GRETTIA, F-93166 Noisy-le-Grand, France (Sammouri, W.; Come, E.; Oukhellou, L.; Aknin, P.) \|\| Alstom Transport, F-93482 St. Ouen, France (Fonlladosa, C.-E.; Prendergast, K.)
Abstract	The increasing interest in preventive maintenance strategies for railway transportation systems and the emergence of telecommunication technologies have both led to the development of floating train data (FTD) systems. Commercial trains are being equipped with both positioning and communications systems as well as onboard intelligent sensors monitoring various subsystems all over the train. The sizable collected amounts of real-time spatio-temporal data can be used to leverage the development of innovative diagnosis methodologies based on temporal and sequential data mining. This paper presents a temporal association rule mining approach named T-patterns, applied on highly challenging floating train data. The aim is to discover temporal associations between pairs of timestamped alarms, called events, that can predict the occurrence of severe failures within a complex bursty environment. Experiments carried out on Alstom's TrainTracer™ data show promising results.
Starting Page	1351
Ending Page	1356
File Size	472785
Page Count	6
File Format	PDF
ISBN	9781467330640
ISSN	21530009
e-ISBN	9781467330633
e-ISBN	9781467330626
DOI	10.1109/ITSC.2012.6338698
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Association rules Rail transportation Maintenance engineering Vectors Histograms Prediction algorithms
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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