Identification method of cyclic top defects in track geometry measurements in its early stage

Track irregularities in the long wavelengths are often overlooked in the development of new track identification and detection techniques, yet they can have serious implications for the safety of freight wagons and the comfort of passengers. This study is aimed to extend the current published literature, by proposing a methodology for the identification and classification of evolving cyclic top (CT) irregularities in the mid and long wavelength range between 25 and 70 m. The methodology required a dataset of historical vertical track geometry measurements to identify and classify CT irregularities, by analysing the growing wavelength contents. The classification of detected CT into early and advanced stage of evolution allows maintenance interventions to be timely planned, improving transportation efficiency. This study contributes to enhancing monitoring methodologies for track geometry and highlights the importance of considering mid and long wavelength irregularities.