Wheel data

With the rapid development of high-speed trains (HSTs), safety and reliability in HSTs operation have attracted plenty of attention. The wheel, as one of the most crucial components, requires absolutely high reliability. The non-roundness wear is a typical failure mode of the HST wheel, which can have a detrimental influence on track and train components, leading to increased risks of rail breaks, sleeper cracking, high-cycle fatigue of wheels and axles, and bearing damage. It inevitably jeopardizes the safety and reliability of railway operations. Therefore, considerable research efforts recently have been devoted to investigating the intelligent fault diagnosis techniques for HST wheels based on the wheel profile data, i.e. the radial runout curve with respect to the wheel perimeter. We provide wheel profile data for this purpose, and this data is in support of our paper "Adaptive Graph-based Support Vector Data Description for Weakly-Supervised Anomaly Detection".