Automating Signal Synchronization for Enhanced Track Monitoring in Turnouts

The focus of this research is the automation of the synchronization process for track-recording vehicle signals in turnouts. Accurate synchronization of measurement signals is essential for assessing specific track sections—especially complex areas such as turnouts—and for enabling reliable time series for condition monitoring. Currently, the synchronization process is only partially automated, resulting in high levels of manual effort. With over 4000 turnouts on Austria’s main railways, full automation is important for ensuring efficiency and consistency of the synchronization process. Based on an analysis of 109 turnouts in the OeBB railways, the process begins with rough synchronization using mileage and curvature signals to eliminate invalid measurement runs. Subsequently, longitudinal level signals are synchronized within maintenance time blocks. These blocks include measurement runs with consistent signal characteristics between two maintenance interventions. The latest valid run then serves as reference for each block. Methods such as cumulative sum, Euclidean distance and cross-correlation are then employed to achieve fine synchronization. The results demonstrate the feasibility and efficiency of automated synchronization compared to manual methods, enabling more accurate condition assessment. This allows infrastructure managers to track turnout-specific quality indicators, integrate them into asset management systems, and develop predictive maintenance strategies.