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Drive-By Methodologies for Smart Condition Monitoring of Railway Infrastructure

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Abstract

Advances in sensor technologies, data management and identification/detection algorithms have led to significant advances in condition monitoring of transportation infrastructure in the last four decades. Sensor-based condition monitoring identifies damage sensitive features from measurements. While the vast majority of condition monitoring research relies on dedicated and stationary sensor positioning, there is an emerging paradigm with so called drive-by condition monitoring that detects infrastructure damage from sensors embedded in moving vehicles. With the advent of mobile and smart technologies, drive-by condition monitoring has gained pace and is now among the most promising condition monitoring concepts. Unlike traditional dedicated approaches, drive-by condition monitoring can scan multiple bridges due to vehicle mobility and can provide spatially high-resolution readings from infrastructures, e.g., kilometres-long railway tracks. However, there are numerous challenges that limit the applicability of drive-by, such as the short duration of sample segments and the masking of infrastructure-induced vibrations by much larger vehicle-induced measurements. This chapter presents a brief state-of-the-art of drive-by condition monitoring with a focus on railway infrastructure, sheds light on the current trends, and proposes future directions that are likely to shape the next decade’s drive-by condition monitoring research from the authors’ perspectives.

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Authors and Affiliations

  1. School of Civil Engineering, University College Dublin, Belfield, Dublin, 04V1W8, Ireland

    Ekin Ozer & Eugene OBrien

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  1. Ekin Ozer
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  2. Eugene OBrien
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Correspondence to Ekin Ozer .

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Editors and Affiliations

  1. CONSTRUCT, School of Engineering, Polytechnic of Porto, Porto, Portugal

    Diogo Ribeiro

  2. CONSTRUCT, Department of Civil Engineering, Faculty of Engineering, FEUP, University of Porto, Porto, Portugal

    Pedro Aires Montenegro

  3. Division of Structural Engineering and Bridges, Department of Civil and Architectural Engineering, KTH Royal Institute of Technology, Stockholm, Sweden

    Andreas Andersson

  4. Department Mechanical Engineering and Construction, Universitat Jaume I, Castellón, Spain

    Maria D. Martínez-Rodrigo

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Ozer, E., OBrien, E. (2024). Drive-By Methodologies for Smart Condition Monitoring of Railway Infrastructure. In: Ribeiro, D., Montenegro, P.A., Andersson, A., Martínez-Rodrigo, M.D. (eds) Digital Railway Infrastructure. Digital Innovations in Architecture, Engineering and Construction. Springer, Cham. https://doi.org/10.1007/978-3-031-49589-2_7

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  • DOI: https://doi.org/10.1007/978-3-031-49589-2_7

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