Reliability Analysis of Wheel Polygonization Using Hierarchical Gaussian Mixture Markov Chains

During the operation of high-speed trains, some vehicles will experience wheel polygonization (WP). Severe polygonal wear significantly increases the wheel-rail contact force, reduces the service life of wheelsets, and may cause other component failures. In this article, hierarchical Gaussian Markov chain models were established to estimate the failure time of WP, considering the effects of season, initial wheel radius, and wheel wear. Two-layer hierarchical Gaussian mixture models are employed to analyze the distribution patterns of the failure time of polygonal wheels for motors and trailers in different seasons. The results show that different seasons have a significant impact on the failure time of polygonal wheels, and motors are more prone to polygonal wear. In addition, wheel polygonization tends to occur in pairs. Moreover, when the wheel diameter variation is small, its influence on reliability is insignificant.