Jou-Yi Shih

A sleeper, or more generally a “bearer”, moves vertically under a passing train load. The extent of this motion depends on the static and dynamic load of the train, the train speed, and the support conditions at the bearer and its neighbours. Excessive motion, typically from voiding see-sawing, low support stiffness or possibly excessive stiffness, or even too little stiffness, are all of interest to maintainers. Typically, problems arise around transition zones, switches and crossings, but plain track with poor support can also be a problem. Within the last decade, low-cost micro-electro-mechanical system (MEMS) accelerometers have been used to capture the time history of vertical motion for use in condition monitoring. Existing condition monitoring systems often overlook or sometimes even ignore the possibility of problematic data, which seem to be common in monitored locations. It is essential to understand whether such “bad” data require further attention. Three problematic sites are presented, focussing on examples where the acceleration was higher than expected or the computed displacement was not as expected. Potential causes include wheel defects, hammering of the ballast by a hanging bearer, or high acceleration at some structural resonant frequency. The present paper aims to show the challenges of using MEMS accelerometers to collect data for condition monitoring and offers insights into the sort of problematic data that may be collected from real sites.

Railway switches and crossings constitute a small fraction of linear track length but consume a large proportion of the railway track system maintenance budget. While switch and crossing (S&C) faults rarely prevent trains from running, switches and crossings are the source of many faults and need continual attention. On the rare occasions when trains are prevented from running the cost of the disruption is very high. Condition monitoring of the point operating equipment that moves the switchblades has been in use for many years but condition monitoring of the state of the switch in terms of the support and mechanical damage as trains pass over has only recently started to become possible. To this end, it is important to understand the correlation between S&C faults and sensor data that can detect those faults. This paper assesses some of the data collected from multiple sensors variously positioned on and around a switch and crossing on the UK mainline for a few days of normal train operation. Accelerometers, geophones, and strain gauges were installed at the locations where they were anticipated to be most useful. Forces at the load transfer point on the crossing nose were estimated from two separate strain gauge bridges and possible use of acceleration on the crossing is discussed. Correlations between different data are analysed and assessed and correlation between peak estimated load transfer forces and accelerations is presented. Based on the analysis, conclusions are drawn about the different types of dynamic information around S&Cs that can be obtained from a variety of sensor types.

Railway track switches experience high failure rates, which can be reduced by monitoring their structural health. The results obtained from a validated Finite Element (FE) model for train–track switch interaction have been introduced to support sensor selection and placement. For the FE models with nominal and damaged rail profiles, virtual strain sensor measurements have been obtained after converting the true strains to engineering strains. Comparisons for the strains before and after the introduction of the fault have demonstrated greater amplitude for the strains after fault introduction. The highest difference in strain amplitude is in the vertical direction, followed by the longitudinal and lateral directions.

This paper compares different track model formulations for the simulation of dynamic vehicle–track interaction in switches and crossings (S&C, turnouts) in a multi-body simulation (MBS) environment. The investigations are an extension of the S&C simulation Benchmark with the addition of a finite element model of a 60E1-760-1:15 turnout. This model constitutes a common reference from which four different track formulations are derived: co-running, modal superposition, finite element incorporated into the MBS model and finite element coupled to MBS using a co-simulation approach. For the different track models, the difference in modelling technique, results, simulation time, and suitability for different simulation tasks is compared. A good agreement is found between the different track model formulations for wheel–rail contact forces and rail displacements. This study found a better agreement between co-running and structural track models compared to previous studies in the prediction of wheel–rail contact forces. This appears to be due to the increased complexity of co-running track model used in this study together with a tuning of the co-running track model to the reference model in a wider frequency range. For the reader interested to reproduce the results in this paper, the reference track model is available for download.

This paper proposes a three-layered co-running track model for predicting and analysing the dynamic behaviour of railway turnouts during the passage of trains. It is a multi-body dynamic model with space-dependent track parameters. The method is demonstrated by applying a UIC60-760-1:15 turnout (with curve radius 760 m and turnout angle 1:15). Equivalent track properties are introduced, based on the turnout track flexibility, and the rail receptance and impact force results are compared with the results from a finite element (FE) model. The validation results show a good agreement with those of the FE model, but with far less computational expense in terms of power and time. The new model is found to capture the dominant dynamic behaviour of the turnout across all frequencies up to 2000 Hz. The results have drawn that consideration of higher frequencies is important due to the nature of dynamic forces affecting the crossing region and high-speed cases.

Switch and crossing (S&C) faults are a major cause of track-related delays and account for a significant proportion of maintenance and renewal budgets for railway infrastructure managers around the world. Although various modelling approaches have been proposed in the literature for the simulation of vehicle–track dynamic interaction, wheel–rail contact and damage prediction, there is a lack of evaluation for combining these approaches to effectively predict the failure mechanism. An evaluation of S&C modelling approaches has therefore been performed in this article to justify their selection for the research interests of predicting the most dominant failure mechanisms of wear, rolling contact fatigue (RCF) and plastic deformation in S&C rails by recognising the factors that influence the accuracy and efficiency of the proposed modelling approaches. A detailed discussion of the important modelling aspects has been carried out by considering the effectiveness of each individual approach and the combination of different approaches, along with a suggestion of appropriate modelling approaches for predicting the dominant failure mechanisms.

A new track swtich and crossing (S&C), the back to back bistable (B2B) switch, is proposed that has shown potential to significantly reduce the wheel/rail contact forces through the switch due to its more continuous wheel/rail contact interface and more uniform track stiffness arising from the elimination of the crossing nose. This offers a major reduction on maintenance cost of future S&Cs. The paper explains the concept and identifies the design guidelines for a current layout and uses vehicle/turnout dynamic modelling to predict wheel rail forces through a switch to identify performance improvements relative to a conventional S&C. Both multi-body simulation (MBS) and Finite Element (FE) model have been developed to account for dynamic and thermal analysis. The new design has shown improvements in lateral and vertical wheel-rail contact forces and less relative rail displacements due to thermal effect compared to the conventional S&C.