Optimising the wheel/rail interface on a modern urban rail system

Evans, J. R.; Lee, T. K.Y.; Hon, Chen

doi:10.1080/00423110701882355

Cited by 20 publications

(14 citation statements)

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“…Vertical wheel load is related to axle load, but will be dynamically amplified roughly in proportion to speed, with frequencies in the tens of hertz range. 2 Much of the work on monitoring the dynamics of wheel-rail contact has been applied noise reduction, and this work has revealed some very complex interactions between wheel and track roughness, rail and wheel stiffness, and track foundations, the overall effect being that noise is generated by rail and wheel vibrations in the frequency range from about 50 Hz to 2 kHz, although curve squeal is much less well-understood because the forcing [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] {SAGE}PIF/PIF 458497.3d (PIF) [PREPRINTER stage] function is believed to be frictional instability rather than roughness-induced vertical displacements. 3 Given this complex loading situation, traditional mean gross tonnage (MGT)-based rail life prediction methods are not reliable since dynamic loading produces non-uniform and dynamic stress distributions from traction, braking and steering forces, often giving rise to multipoint contact pressure distributions rather than the Hertzian distribution traditionally assumed.…”

Section: Introductionmentioning

confidence: 99%

“…4 Both wear and RCF models include contact forces (see, for example, Tunna et al 5 ) and such models are now used in the management of rail assets using parameters estimated from wheel and track geometry, axle loads and speed. 6,7 The object of the current work is to assess whether the intensity of railwheel contact can be monitored using acoustic emission (AE) in much the same way as fatigue forcing parameters are monitored in other civil engineering assets, such as wave loading in ships. 8 The American Railway Engineering and Maintenance-of-Way Association guidance on rolling friction in rails 9 suggests that the track resistance, F, (as a force) is given by:…”

Section: Introductionmentioning

confidence: 99%

“…Effect of axle load on mean energy per wheel rotation in tests with spacer installed 6. Proc IMechE Part F: J Rail and Rapid Transit 0(0)[1-15] {SAGE}PIF/PIF 458497.3d (PIF) [PREPRINTER stage] Effect of speed and load on AE records with spacer absent.…”

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confidence: 99%

“…Average kurtosis of cross-correlation function between track defects and AE above normal rolling background for all experiments with no spacer installed [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. {SAGE}PIF/PIF 458497.3d (PIF) [PREPRINTER stage]…”

mentioning

confidence: 99%

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A laboratory study of rail–wheel interaction monitoring using acoustic emission: Effect of rolling conditions with and without lateral rattling

Thakkar

Steel

Reuben

2012

Proceedings of the Institution of Mechanical Engineers, Part F:

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This paper presents part of an extended laboratory study on the potential to apply the acoustic emission (AE) technique for in-situ rail-wheel interaction monitoring using rail-mounted sensors. The essential monitoring principle is that the intensity of the rail-wheel contact will affect the intensity of the AE that is generated during rolling. The current paper is confined to situations of 'normal' rolling, investigating the effects of wheel load, speed and lateral rattling of the generated AE, although the wider study includes the effects of rail and wheel irregularities on the AE generated. Rail-wheel contact was simulated on a scaled test rig consisting of a single wheel rolled round a circular track using a motor mounted at the centre of the track attached to a driving arm. AE was recorded at a fixed point on the track while the wheel was rolled around the track at a range of speeds with varying axle load. Wheel slip was found to be insignificant and tests using a simulated source confirmed that the energy recorded with a source at a given position on the track was repeatable. In one set of experiments, measures were taken to eliminate lateral rattling of the wheel and eccentricity of the wheel arc relative to the track arc. In a second set of experiments, some lateral float of the wheel along the axle was allowed and a limited amount of eccentricity was built into the track. The energy per wheel rotation for normal rolling was found to increase in a linear fashion with increasing axle load and centrifugal force, as would be expected due to the increasing rolling resistance with axle load and increasing lateral force with angular speed. The frictional instability associated with the lateral rattling was clearly detectible at low axle loads and lower speeds, and both natural and eccentricity (flange rubbing) rail abnormalities were detectible in the AE record. It is concluded that, with appropriate calibration, contact stresses between wheel and rail on straight or curved track can be monitored using track-mounted sensors so that cumulative contact stress can potentially be monitored.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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A laboratory study of rail–wheel interaction monitoring using acoustic emission: Effect of rolling conditions with and without lateral rattling

Thakkar

Steel

Reuben

2012

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…This was particularly evident on high rails of tighter curve radii and prediction of low rail damage. In order to increase the model's efficiency, it was suggested that different creep force angles may generate different types of damage and the subsequent studies showed the relationship between the resultant creep force angle and damage risk (Evans et al 2008;Bevan, 2011). For this reason, the 'raw Tγ' and the creep force angle should be taken into account to improve the model's predictions.…”

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confidence: 99%

Prediction of RCF Damage on Underground Metro Lines

Boyacioglu¹,

Bevan²,

Vickerstaff

2018

Icrt 2017

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London Underground (LUL) is one of the largest metro networks in the world and carried nearly 1.5 billion passengers in 2015. This increasing passenger demand leads to higher axle loads and shorter headways in the railway operations. However, this has a detrimental impact on the damage generated at the wheel-rail interface. In spite of the advances in rolling stock and track engineering, new developments in material manufacturing methods and rail inspection technology, cracking in rails still remains a major concern for infrastructure managers in terms of safety and maintenance costs. In this study, field data from two metro lines on the LUL network was analysed to identify the distribution and severity of the different damage types. Detailed vehicle dynamics route simulations were conducted for the lines and the calculated wheel-rail forces were investigated to assess the applicability current models for the prediction of rail damage on metro lines. These models include the Whole Life Rail Model (WLRM), previously developed for Great Britain (GB) main line tracks, and Shakedown theory. The influence of key factors such as curve radius, different friction conditions, track irregularities and wheel-rail profiles on the wheel-rail contact interface have been evaluated and compared with outputs from simulations on mainline routes. The study found that the contact patch energy (Tγ) and the interaction between wear and RCF in rails were highly influenced by the characteristics of metro tracks. It was also shown that both the Tγ and Shakedown methods can provide successful prediction of damage susceptibility of rails. However, in order to increase the accuracy of damage predictions and to ascertain the severity of different damage types, the duty conditions which are observed by the rail and the changes in contact conditions resulting from the successive vehicle passes should be considered in the modelling.

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Wheel profile design for target conicity and wide tread wear spreading

Polách¹

2011

Wear

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Optimising the wheel/rail interface on a modern urban rail system

Cited by 20 publications

References 1 publication

A laboratory study of rail–wheel interaction monitoring using acoustic emission: Effect of rolling conditions with and without lateral rattling

A laboratory study of rail–wheel interaction monitoring using acoustic emission: Effect of rolling conditions with and without lateral rattling

Prediction of RCF Damage on Underground Metro Lines

Wheel profile design for target conicity and wide tread wear spreading

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