PHM for railway system — A case study on the health assessment of the point machines

Point machines are used for operating railway turn outs and are considered as critical track elements in railway assets. Failures in the point machine's mechanism cause delays, increase railway operating costs and, more importantly, may cause train accidents. Hence, the condition monitoring and health management of point machines has become a main area of interest. This research focuses on establishing a strategy and technical architecture for prognostics and health management (PHM) of the electromechanical point machines. This study has been conducted on the ALSTOM P80 electromechanical point machine data acquired from eight machines in various locations throughout Italy. Time-stamped data was acquired for point machines current and voltage signals. Various feature extraction techniques have been applied to the data. Then, Principal Component Analysis (PCA) was applied to the features to assess the health of the machines. There is currently a lack of information about the present and past conditions of the machines and the exact timing of each participating movement of the mechanism. Despite this, the results obtained show degradation of the machines and demonstrate the applicability of the aforementioned PHM technique for fault diagnostics and prognostics of point machines.