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ISSN 2753-3239
CCC: 1
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE
Edited by: J. Pombo
Paper 27.8

Fault detection of railway vehicle suspension through on-board condition monitoring

I.S. Apezetxea1,2, B. Rodriguez-Arana1,2 and I. Puy1,2

1Ceit-BRTA, Donostia-San Sebastián, Spain
2Universidad de Navarra, Tecnun, Donostia-San Sebastián, Spain

Full Bibliographic Reference for this paper
I.S. Apezetxea, B. Rodriguez-Arana, I. Puy, "Fault detection of railway vehicle suspension through on-board condition monitoring", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 27.8, 2022, doi:10.4203/ccc.1.27.8
Keywords: helical spring, rail vehicle suspension, fault detection, condition monitoring, freight locomotive, dynamic stiffness method.

Abstract
Laboratory tests in order to acquire data of the selected wagon components failure (i.e. suspension helical springs) to be monitored have been carried out. In particular, the present work considers possibilities for the condition monitoring of helical springs based on measuring axle box accelerations. Undamaged and damaged springs are studied of a Y25 bogie, which have been exposed to a theoretical and experimental analysis. For analytical study, the dynamic stiffness method is going to be applied, which through its derivation, the dynamic behaviour of the helical spring is described. The experimental tests are conducted on an INSTRON MHF25 testing machine. Two types of dynamic tests have been performed: force-displacement relationship and FRF of the accelerometers. A good agreement between experimental and theoretical results has been observed. A positive aspect is that the results obtained with accelerometers are more satisfactory than those obtained through the representation of the evolution of dynamic stiffness. However, after analysing the FRF distribution of the damaged springs, a great dispersion has been observed between them. There is no clear trend in frequency response depending on the damage type of the spring. Despite this, satisfactory results have been obtained in order to identify damaged springs in service based on condition monitoring data defective. Through this analysis, significant correlation between helical spring indicator and defect type has been found, indicating promising chances of detecting a defect before there is a risk of high failure high, therefore ensuring the safe running of the vehicle.

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