Track irregularities are one of the main excitations that cause undesired vehicle dynamic vibrations.

Developing a proper monitoring methodology is essential to guarantee safety and ride comfort. Typically, studies aimed at improving monitoring and maintenance plans focus on addressing vertical irregularities in the D1 wavelength range (3 – 25 m), crucial for passenger vehicle safety. However, periodic track irregularities at longer wavelengths, known as Cyclic Top (CT), can affect freight wagons and potentially lead to derailments, as documented in various derailment reports. In this project, track irregularity measurements are analysed to develop a methodology able to identify CT and detect it at an early stage.

The method involves calculating two features to detect defects and evaluate their magnitude, simplifying the process. It can be easily applied to different track lines by adjusting threshold limits according to specific criteria such as ‘early stage’ and ‘relevant amplitude,’ enhancing its flexibility. Utilizes optimized techniques like the Goertzel algorithm instead of the FFT, improving computational speed and efficiency in analysis.

Main Advantage of the developed Methodology

  • Easy Implementation
  • Adaptability
  • Computational Efficiency