PSI - Issue 4

Uwe Oßberger et al. / Procedia Structural Integrity 4 (2017) 106–114

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Author name / Structural Integrity Procedia 00 (2017) 000 – 000

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The comparison with similar geometry measurements of Hadfield steel crossings and other material concepts recently published by Ossberger et al. (2015) revealed that Hadfield crossing noses show a clearly distinguishable plastic deformation in the run in phase followed by a stable performance that is attributed to the fact that the crossing geometry has adapted to the average profile of the passing wheels. The plastic adaption of the Hadfield steel leads to a reduction of the local contact pressure and thus the local material load. For the experimental tool steel crossing nose in Fig. 1, the geometry change quantification in Fig. 6 showed no distinguishable plastic deformation based on the fact that no “blue regions” are visible and therefore all geometry changes can be attributed to abrasive wear. Furthermore, Ossberger et al. (2015) demonstrated that after normalization to the average load (MGT per year) in the same surveillance time, the Hadfield steel noses showed higher abrasive wear than the tool steel crossing nose. For the new tool steel crossing nose the lack of observable plastic deformation combined with the low abrasive wear lead to the conclusion on the one hand the tool steel crossing nose is more sensitive to the initial transition geometry than the Hadfield steel nose (thus heavily worn wheels will have a worse effect on the tool steel nose) but on the other hand the tool steel nose with a good initial geometry shows a superior wear performance. A fixed point crossing equipped with an experimental tool steel crossing nose has been instrumented with strain gauges and installed in a track with mixed traffic. Strain gauge signals were recorded in regular intervals to establish a database to develop signal based condition monitoring. A signal processing chain has been developed by Kollment et al. (2016) that enables to use the signals generated by a frequently passing vehicle with constant arrangement und only small variations in the velocity (e.g. a specific locomotive) to monitor changes in the combined system of the crossing nose geometry/wear state and the state of the underlying bedding. A signal processing work flow for signal based condition monitoring of the wear state of the crossing nose is proposed. For this workflow, the use of a single strain gauge signal on the crossing nose was sufficient. To distinguish between the geometry changes and the bedding and to correlate the observed signal change with the crossing nose geometry change, a quantitative measurement of the geometry changes of the crossing nose with service time has been set up. The geometry monitoring system is based on laser profilometry performed on predefined positions of the crossing in regular time intervals. It is therefore not intended as a replacement for the customary visual inspection procedure but rather to quantify the changes of the crossing geometry observed at these inspections and to serve as input to prognosis models. Until now, only light changes in the transition geometry where observed. Therefore it can be assumed that the effects of changes of the transition geometry are low compared to other effects on the changes of the consensus curve (Fig 4c). A combination of the ongoing collection of geometry measurements and strain measurements with existing finite element models and signal processing algorithms shall lead to a model based condition monitoring setup that enables a higher flexibility in the planning of repair maintenance and visual inspection intervals especially (but not exclusively) for fixed railway crossings. The authors want to thank the companies voestalpine VAE GmbH, ÖBB Infrastruktur AG, voestalpine Schienen GmbH and Böhler Edelstahl GmbH & Co.KG for their support. Furthermore, financial support by the Austrian Federal Government (in particular from Bundesministerium für Verkehr, Innovation und Technologie and Bundesministerium für Wissenschaft, Forschung und Wirtschaft) represented by Österreichische Forschungsförderungsgesellschaft mbH and the Styrian and the Tyrolean Provincial Government, represented by Steirische Wirtschaftsförderungsgesellschaft mbH and Standortagentur Tirol, within the framework of the COMET Funding Programme is gratefully acknowledged. Burstow, M. C., 2006, A model to predict and understand rolling contact fatigue in wheels and rails. Proceedings of the 7th World Congress on Railway Research (WCRR 2006), Montreal, Canada. Eck, S., Ossberger, U., Marsoner, S., Ebner, R., 2014. Comparison of the fatigue and impact fracture behaviour of 5 different steel grades used in the frog of a turnout. Int. J. Rail and Rapid Transit 228 (6), 603-610. http://dx.doi.org/10.1177/0954409713511078 Isermann, R. 2005. Model-based fault-detection and diagnosis – status and applications. Annual Reviews in Control 29, 71 – 85. http://dx.doi.org/10.1016/j.arcontrol.2004.12.002 Jardine, A.K.S., Lin, D., Banjevic, D., 2006. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing 20, 1483 – 1510. http://dx.doi.org/10.1016/j.ymssp.2005.09.012 Kollment, W., O’Leary, P., Harker, M., Oßberger, U., Eck, S., 2016 Towards Condition Monitoring of R ailway Points: Instrumentation, Measurement and Signal Processing, Proceedings of IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Taipei, Taiwan, 612-617. http://dx.doi.org/10.1109/I2MTC.2016.7520434 4. Summary and Outlook Acknowledgements References