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Cost-benefit model for rail inspection decision using limited and incomplete data

conference contribution
posted on 06.12.2017, 00:00 by Gopinath ChattopadhyayGopinath Chattopadhyay, V Reddy
Detection of cracks in the rail is extremely important to rail infrastructure owners. The Hatfield (UK) accident in 2000, lead to the cost of £ 734 million for repairs and compensation payments. The main cause was undetected crack due to Rolling Contact Fatigue (RCF). For most of the railway operators data related to axle load, frequency of loading, speed, curve radius, contact stress, accumulated tonnage, rail-wheel material, hardness, preventive grinding, lubrication, inspection reports, rail history (source and year of installation) and derailment data along with costs are collected, compiled and kept in different databases at various departments. A recent study by authors found failure and cost data stored in different databases are limited and incomplete. Data are duplicated in some areas and vital information is missing in many other places. These are major barriers for modelling and decision making for rail-wheel inspection and maintenance.This paper focuses on study of current practices related to rail inspection and proposes a practical solution to reduce data related problems and developing a cost-benefit model for rail inspection decisions.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Parent Title

Condition monitoring and diagnostic engineering management (COMADEM 2007) : proceedings of the 20th international congress, 13-15 June 2007, Coimbra, Portugal.

Start Date

01/01/2007

ISBN-13

9789898109026

Location

Faro, Portugal

Publisher

Instituto de Telecommunicacoes

Place of Publication

Coimbra, Portugal

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Centre for Railway Engineering; Faculty of Sciences, Engineering and Health; School of Engineering Systems;

Era Eligible

Yes

Name of Conference

International Congress on Condition Monitoring and Diagnostic Engineering Management