Prediction of wheel-rail contact forces using simple onboard monitoring system and machine learning

Walther, Simon; Müller, Simon; Fuerst, Axel; Renggli, Rolf; Unlü, Fatih (2022). Prediction of wheel-rail contact forces using simple onboard monitoring system and machine learning Journal of Rail and Rapid Transit, 237(5), pp. 553-562. Institution of Mechanical Engineers 10.1177/09544097221122006

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For safe railway operation, periodic measuring of vehicle dynamics (wheel-rail-contact forces) is important, especially for tilting trains since they run faster through curves than normal traffic. So far, these forces are determined in test runs once a year using instrumented wheelsets. To get information more regularly and more economically, a simple onboard monitoring system for daily use on a commercial train has been developed. This system is predicting the forces relevant to assess running safety of tilting trains, so it is optimised for curves with lateral forces close to the critical values. Vertical forces are predicted by metering the primary spring deflection, which is already a proven method. The ambitious part research is focussing on is the prediction of the lateral forces on the whole wheelset and on the guiding wheel. This is obtained by transferring lateral accelerations using machine learning to manage even non-linear effects of the train’s undercarriage. Finally, the used Random Forest regressor thereby shows a good accuracy of the predicted forces compared to the original forces of the instrumented wheelset with correlations of around 95% for the relevant tilting train track sections.

Item Type:	Journal Article (Original Article)
Division/Institute:	School of Engineering and Computer Science > Intelligente industrielle Systeme (I3S) School of Engineering and Computer Science > Intelligente industrielle Systeme (I3S) > I3S / Prozessoptimierung in der Fertigung School of Engineering and Computer Science
Name:	Walther, Simon0000-0001-9839-2054; Müller, Simon0000-0001-7518-9715; Fuerst, Axel; Renggli, Rolf and Unlü, Fatih
Subjects:	T Technology > T Technology (General) T Technology > TF Railroad engineering and operation T Technology > TJ Mechanical engineering and machinery
ISSN:	2041-3017
Publisher:	Institution of Mechanical Engineers
Language:	English
Submitter:	Simon Walther
Date Deposited:	14 Sep 2022 10:45
Last Modified:	16 Apr 2023 01:36
Publisher DOI:	10.1177/09544097221122006
Related URLs:	https://journals.sagepub.com/doi/10.1177...
Uncontrolled Keywords:	Vehicle track interaction Wheel/rail interaction Wheel-rail contact Track irregularity Lateral dynamics Wheel rail contact Forces Random forest Tilting train Onboard monitoring
ARBOR DOI:	10.24451/arbor.17701
URI:	https://arbor.bfh.ch/id/eprint/17701