An application of the Unknown Input Observer algorithm for the identification of vertical railway track irregularity

In this paper, a model-based solution for the identification of the railway track irregularity from simulation data is presented. The proposed methodology relies on the application of the Unknown Input Observer algorithm. A Simpack railway vehicle model is adopted to simulate the acceleration levels that vehicle-mounted sensors (for instance on the bogies and carbody) would measure during operation. A vehicle running at constant speed on a straight track is considered, considering different type of track irregularity (longitudinal level, cross-level) to test the algorithm capability to identify the input irregularity. In the analysed cases, satisfactory results are achieved both in terms of signal histories and corresponding frequency content, proving the methodology suitable for the identification of the track irregularity for monitoring purposes, adopting an instrumented vehicle.