Turnouts are critical components of railway infrastructure, ensuring operational flexibility but also representing a significant share of track maintenance costs. The frog, as the most vulnerable part of a turnout, is subject to severe wear and degradation, requiring frequent inspection and maintenance.
Moving turnouts towards data-based, predictive maintenance is the goal of this Area of Research. Collaborating with several stakeholders, we explore different possibilities to gather enough and useful data in order to design algorithms for assessing condition and strength of turnouts making predictive maintenance possible for turnout components and systems.
