Integration of on-board monitoring data into infrastructure management for effective decision-making in railway maintenance

Abstract

Railway infrastructure is a crucial asset for the mobility of people and goods. The increased traffic frequency imposes higher loads and speeds, leading to accelerated infrastructure degradation. Asset managers require timely information regarding the current (diagnosis) and future (prognosis) condition of their assets to make informed decisions on maintenance and renewal actions. In recent years, in-service vehicles equipped with on-board monitoring (OBM) measuring devices, such as accelerometers, have been introduced on railroad networks, traversing the network almost daily. This article explores the application of state-of-the-art OBM-based track quality indicators for railway infrastructure condition assessment and prediction, primarily under the prism of track geometry quality. The results highlight the similarities and advantages of applying track quality indicators generated from OBM measurements (high frequency and relatively lower accuracy data) compared to those generated from higher precision, yet temporally sparser, data collected by traditional track recording vehicles (TRVs) for infrastructure management purposes. The findings demonstrate the performance of the two approaches, further revealing the value of OBM information for monitoring the track status degradation process. This work makes a case for the advantageous use of OBM data for railway infrastructure management, and attempts to aid understanding in the application of OBM techniques for engineers and operators.

Keywords

On-board monitoring / Structural health monitoring / Railway systems and dynamics / Predictive maintenance

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Funding

Eidgen?ssische Technische Hochschule Zürich http://dx.doi.org/10.13039/501100003006