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Rail-infrastructure Monitoring through the Dynamic Response of a Passing Train



We present a system for monitoring rail infrastructure from the dynamic response of a train in revenue-service. Presently, rail inspection is performed either visually or with dedicated track vehicles. We propose monitoring the tracks from operational trains, using accelerometers inside the cabin of the train. This would offer an economical approach, as accelerometers are a low-cost technology, tracks would not have to be taken out of service for inspection, and no dedicated inspection vehicles or crews would be required. However, using operational trains presents three challenges: the speed of the train varies from run to run, the position of the train is not known with high accuracy, and the vibration signal recorded in the train’s cabin is filtered by the train and its suspension. We propose extracting features from the signal which are robust to these conditions and show that our proposed features allow for detecting changes in the infrastructure from the train’s dynamic response. We demonstrate our ability to detect subtle track changes both through simulation and using data we collected from Pittsburgh’s Light Rail system. This type of sensing, signal processing, and data analysis could facilitate safer trains and more cost-efficient maintenance in the future.

doi: 10.12783/SHM2015/182

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