A simple state-based prognostic model for railway turnout systems

Date published

2010-05-31T00:00:00Z

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IEEE Institute of Electrical and Electronics

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Article

ISSN

0278-0046

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Citation

Omer F. Eker, Fatih Camci, Adem Guclu, Halis Yilboga, Mehmet Sevkli, Saim Baskan, A simple state-based prognostic model for railway turnout systems, IEEE Transactions on Industrial Electronics, Volume 58, Issue 5, 2011, Pages 1718 - 1726.

Abstract

The importance of railway transportation has been increasing in the world. Considering the current and future estimates of high cargo and passenger transportation volume in railways, prevention or reduction of delays due to any failure is becoming ever more crucial. Railway turnout systems are one of the most critical pieces of equipment in railway infrastructure. When incipient failures occur, they mostly progress slowly from the fault free to the failure state. Although studies focusing on the identification of possible failures in railway turnout systems exist in the literature, neither the detection nor forecasting of failure progression has been reported. This paper presents a simple state-based prognostic method that aims to detect and forecast failure progression in electro-mechanical systems. The method is compared with Hidden Markov Model based methods on real data collected from a railway turnout system. Obtaining statistically sufficient failure progression samples is difficult considering that the natural progression of failures in electro-mechanical systems may take years. In addition, validating the classification model is difficult when the degradation is not observable. Data collection and model validation strategies for failure progression are also presented.

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Github

Keywords

Fault Diagnosis, Diagnostic expert system, Failure Analysis, Rail transportation maintenance, Forecasting, Prognostics, Remaining useful life estimation, Railway Turnouts, Time Series

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© 2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”

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