While structural health monitoring has largely focused on detecting material degradation and stiffness loss, dynamic instability remains an overlooked failure mode. This study addresses railway vehicle hunting motion, a self-excited oscillation that evolves into sustained instability under adverse conditions. A novel health evaluation indicator, termed Hunting Coefficient ( H C ), is proposed, derived from measurable wheelset displacement amplitude and hunting oscillation frequency. Unlike conventional threshold-based methods on wheelset displacement or bogie acceleration, H C enables hierarchical classification of health states (healthy, degraded, failure) and enables early warning of incipient instability. Validation was conducted through full-scale roller rig experiments, which offers a controlled and repeatable platform for reproducing hunting behavior under varying speeds and excitation conditions. The results demonstrate that H C reliably tracks the progression of hunting instability and outperforms conventional displacement- or acceleration-based metrics in sensitivity, robustness, and real-time applicability. These findings offer a practical basis for in-service monitoring of railway vehicles, supporting condition-based maintenance strategies and enhancing the operational safety of railway systems.
Wang et al. (Wed,) studied this question.