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Laura T. Rodríguez-Bayona

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Open access Sep 2026

Multi-sensor system for efficient in-service vehicle-based track monitoring and fault localization: a case study

As the requirements for railway operators to offer a safe and economically efficient transportation service have become extremely difficult to met due to the size and complexity of the rail network, vehicle-based track monitoring and fault detection have gained relevance as a way to abate maintenance-related costs via condition-based and predictive approaches. In this work, a cost-effective, permit-free vehicle-based track monitoring system implemented on a regular in-service vehicle is presented. The designed system makes use of inertial sensors mounted on the vehicle’s bogie and car body, as well as positioning technology based on global navigation satellite system (GNSS) to collect monitoring data for detection and spatial localization of track defects. The capabilities of the developed system are exemplified by means of a case study related to a track section with a temporary speed restriction (TSR)—a scenario where traditional acceleration-based detection often fails due to reduced vehicle speed. Here, it is demonstrated that the proposed approach, combining statistical and time-frequency analysis (e.g., wavelets), can effectively lead to the detection and localization of anomalies on the track using onboard inertial measurements, even under reduced vehicle speed.

Héctor A. Fernández-Bobadilla, R. Frolow, Laura T. Rodríguez-Bayona et al. · 0 citations

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