Observed failures at railway turnouts: Failure analysis, possible causes and links to current and future research

Abstract Railway turnouts are a necessary part of railway infrastructure, used throughout the network to direct trains to the desired path, thus ensuring the smooth running of every train. Their reliability and availability is therefore an essential element for the efficiency of the entire network. However, the combination of movable parts, some of which with reducing cross sections and structural integrity, discontinuities in the rail geometry and variability in the system support stiffness leads to high failure rates compared with plain line track and to very high maintenance and renewal costs. In this paper, the database of failures occurred in the GB network between 2011 and 2017 has been statistically investigated with the support of free-text analysis techniques to interrogate the comments provided by the on-track maintenance staff. The key failures and possible causes have been identified for both the switch and crossing panels as well as areas for future research to support the development of the next generation of switches and crossings.

[1]  V. Markine,et al.  Numerical procedure for fatigue life prediction for railway turnout crossings using explicit finite element approach , 2016 .

[2]  Shin-ichi Toyabe,et al.  Detecting inpatient falls by using natural language processing of electronic medical records , 2012, BMC Health Services Research.

[3]  Samuel D. Bemment,et al.  Rethinking rail track switches for fault tolerance and enhanced performance , 2017 .

[4]  Björn A. Pålsson,et al.  Design optimisation of switch rails in railway turnouts , 2013 .

[5]  Jens C. O. Nielsen,et al.  Dynamic vehicle–track interaction in switches and crossings and the influence of rail pad stiffness – field measurements and validation of a simulation model , 2015 .

[6]  Lama Saeeda,et al.  Iterative Approach for Information Extraction and Ontology Learning from Textual Aviation Safety Reports , 2017, ESWC.

[7]  J Tunna,et al.  A Review of wheel wear and rolling contact fatigue , 2007 .

[8]  Mark Lehto,et al.  Near-miss narratives from the fire service: a Bayesian analysis. , 2014, Accident; analysis and prevention.

[9]  Miguel Figueres-Esteban,et al.  From free-text to structured safety management: Introduction of a semi-automated classification method of railway hazard reports to elements on a bow-tie diagram , 2018, Safety Science.

[10]  Jonas W. Ringsberg,et al.  Life prediction of rolling contact fatigue crack initiation , 2001 .

[11]  Jens C. O. Nielsen,et al.  Track gauge optimisation of railway switches using a genetic algorithm , 2012 .

[12]  John P. Dear,et al.  Monitoring of strain of in-service railway switch rails through field experimentation , 2016 .

[13]  J. Williams,et al.  Repeated Loading, Residual Stresses, Shakedown, and Tribology , 1999 .

[14]  Andrew Cornish,et al.  Life-time monitoring of in service switches and crossings through field experimentation , 2014 .

[15]  I. Y. Shevtsov,et al.  Optimisation of the elastic track properties of turnout crossings , 2016 .

[16]  Yann Bezin,et al.  Optimisation of support stiffness at railway crossings , 2018 .

[17]  Jens C. O. Nielsen,et al.  Geometry and stiffness optimization for switches and crossings, and simulation of material degradation , 2010 .

[18]  Klaus U. Schulz,et al.  Fast string correction with Levenshtein automata , 2002, International Journal on Document Analysis and Recognition.

[19]  William Powrie,et al.  Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit: Guest Editorial , 2011 .

[20]  Björn Pålsson,et al.  Optimisation of railway crossing geometry considering a representative set of wheel profiles , 2015 .

[21]  Justin Grimmer,et al.  Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts , 2013, Political Analysis.

[22]  Valeri Markine,et al.  Numerical analysis of the dynamic interaction between wheel set and turnout crossing using the explicit finite element method , 2016 .

[23]  Uwe Zerbst,et al.  Introduction to the damage tolerance behaviour of railway rails – a review , 2009 .

[24]  Jens C. O. Nielsen,et al.  Simulation of wheel-rail contact and damage in switches & crossings , 2009 .

[25]  R. Procter,et al.  Reading the riots on Twitter: methodological innovation for the analysis of big data , 2013 .

[26]  Son Doan,et al.  Application of information technology: MedEx: a medication information extraction system for clinical narratives , 2010, J. Am. Medical Informatics Assoc..

[27]  Herbert S. Chase,et al.  Early recognition of multiple sclerosis using natural language processing of the electronic health record , 2017, BMC Medical Informatics and Decision Making.

[28]  Jens C. O. Nielsen,et al.  Simulation of dynamic interaction between train and railway turnout , 2006 .

[29]  Yi Zhu,et al.  Tribology of the wheel–rail contact – aspects of wear, particle emission and adhesion , 2013 .

[30]  Chandra R. Bhat,et al.  Unobserved heterogeneity and the statistical analysis of highway accident data , 2016 .

[31]  Miguel Figueres-Esteban,et al.  Learning from text-based close call data , 2016 .

[32]  Seyedahmad Jalili Hassankiadeh.  Failure analysis of railway switches and crossings for the purpose of preventive maintenance. , 2011 .