Leaves on the Line: Low Adhesion Detection in Railways

Hubbard, P.; Amarantidis, G.A.; Ward, Christopher P.

doi:10.1016/j.ifacol.2016.10.647

Cited by 6 publications

(9 citation statements)

References 10 publications

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“…26 Further research will be undertaken to try to mitigate the impact of defensive driving when examining the data set, the use of the on-board GPS data will facilitate this. 27 Cleaning the line after each 5th loop prevents full formation of a strongly bonded 'black layer', however restoring the line to clean state was stipulated by the test site at the end of each test day. This is because the test site uses the track for other vehicles when the brake tests were not being conducted.…”

Section: Created Leaf-layers As Low Adhesion Simulantsmentioning

confidence: 99%

Field trials of a methodology for locomotive brake testing to assess friction enhancement in the wheel/rail interface using a representative leaf layer

Lanigan

Krier

Johnstone

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part F:

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There are two options for testing the performance of rail vehicles and the application of material to the wheel/rail interface to influence friction, and therefore braking performance, in a low adhesion environment: laboratory work which is not representative of conditions in the field, and expensive track tests using fully instrumented modern vehicles largely using low adhesion simulants that are not representative of those that occur in the real world and usually applied over great lengths of track. This paper presents a third option: low-cost track tests. We determined the minimum of equipment and resources needed to produce low adhesion using a method more representative on Autumn conditions on rail and monitor the performance of rail vehicles when braking on it. This was mainly targeted at use for testing products applied to the wheel/rail interface to enhance traction, hence the need for real low adhesion causes. We present the methodology that we have developed, and some initial results showing that using it we can generate a low adhesion scenario when braking from 10 mph. This can be used to develop mitigation solutions for low adhesion in a more cost effective manner.

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Section: Created Leaf-layers As Low Adhesion Simulantsmentioning

confidence: 99%

Field trials of a methodology for locomotive brake testing to assess friction enhancement in the wheel/rail interface using a representative leaf layer

Lanigan

Krier

Johnstone

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…This now provides an expression for F sus in terms of the variables expressed in (10). Using the parameter identification method in (12), and a time history of the required states from the simulation model, the resultant value of Θ F is shown in the application of equation 13: (17) As before, the right hand side of (17) can be generated directly from simulation data to provide a numerical solution for M sus . In this case, the suspension geometry does not allow for any combination of terms so the state variables required to be defined for M sus arê…”

Section: Parameter Identification For Suspension Descriptionmentioning

confidence: 99%

“…Again, the minimisation of error is performed using (12), and the resultant 260 value of Θ M is shown in the application of equation (13):…”

Section: Parameter Identification For Suspension Descriptionmentioning

confidence: 99%

“…Recently, the study has been extended to investigate the method of contact force estimation during curving [12]. This technique used a reduced-order, linear suspension model of a simplified vehicle, and non-linear contact mechanics to simulate the vehicle travelling through a curve, and a reduced-order suspension model to estimate contact force.…”

Section: Introductionmentioning

confidence: 99%

“…The method is applied to a high-fidelity, realistic, simulation of a rail vehicle to extend the study of [12]. A novel inclusion in this paper is the use of systems identification to approximate a linear, primary suspension model for use in a Kalman Filter.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contact force estimation in the wheel/rail interface for curving scenarios through regions of reduced adhesion

et al. 2018

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Regions of extreme low-adhesion between the wheel and rail can cause critical problems in traction and braking. This can manifest in operational issues such as signals being passed at danger, or pessimistic network wide responses to mitigate for localised issues. Poor traction conditions can be caused by oil contaminants, rain, ice, condensation of water droplets (micro-wetting) or leaves on the line, where compressed leaf contamination can cause a rapid decrease in adhesion. The complexity of the problem arises as a result of the inability to directly measure and monitor all the factors involved. There remains a lack of real-time information regarding the state and location of low-adhesion areas across rail networks. On-board low adhesion detection technology installed to in-service vehicles is a suggested method to capture up-to-date adhesion information network wide and minimise significant disruptions and cancellations in railway schedules. This paper extends a principle of a model-based estimation technique previously developed in straight track running for operating in a curving scenario. The vehicle model of focus here will be a high-fidelity, multi-body physics representation of a full-vehicle.

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Acceleration-based friction coefficient estimation of a rail vehicle using feedforward NN: validation with track measurements

Abduraxman,

Hubbard,

Harrison

et al. 2024

Vehicle System Dynamics

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Leaves on the Line: Low Adhesion Detection in Railways

Cited by 6 publications

References 10 publications

Field trials of a methodology for locomotive brake testing to assess friction enhancement in the wheel/rail interface using a representative leaf layer

Field trials of a methodology for locomotive brake testing to assess friction enhancement in the wheel/rail interface using a representative leaf layer

Contact force estimation in the wheel/rail interface for curving scenarios through regions of reduced adhesion

Acceleration-based friction coefficient estimation of a rail vehicle using feedforward NN: validation with track measurements

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