Keywords: railway infrastructure, condition-based maintenance, in-service vehicle, model-based solution, rail vehicle dynamic simulation, Unknown Input Observer algorithm.

This paper proposes a model-based approach for the estimation of railway track irregularities, based on the implementation of an Unknown Input Observer (UIO). A multibody railway vehicle model developed in Simpack is used to simulate acceleration signals measured by sensors installed on the bogies and carbody during regular operation. The analysis considers a vehicle travelling at different constant speeds, representative of typical metro line conditions, on both straight and curved tracks. The objective is to reconstruct key track irregularities, namely vertical alignment and cross level, using onboard measurements, and to assess the performance of the proposed identification algorithm. To this end, several evaluation metrics are introduced, showing a good agreement between actual and reconstructed track profiles. The results demonstrate that the proposed approach is effective for track irregularity identification and suitable for monitoring applications based on instrumented in-service vehicles.

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