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Bogie hunting instability is one of the common faults in railway vehicles. It not only affects ride comfort but also threatens operational safety. Due to the lower operating speed of metro vehicles, their bogie hunting stability is often overlooked. However, as wheel tread wear increases, metro vehicles with high conicity wheel–rail contact can also experience bogie hunting instability. In order to enhance the operational safety of metro vehicles, this paper conducts field tests and simulation calculations to study the bogie hunting instability behavior of metro vehicles and proposes corresponding solutions from the perspective of wheel–rail contact relationships. Acceleration and displacement sensors are installed on metro vehicles to collect data, which are processed in real time in 2 s intervals. The lateral acceleration of the frame is analyzed to determine if bogie hunting instability has occurred. Based on calculated safety indicators, it is determined whether deceleration is necessary to ensure the safety of vehicle operation. For metro vehicles in the later stages of wheel wear (after 300,000 km), the stability of their bogies should be monitored in real time. To improve the stability of metro vehicle bogies while ensuring the longevity of wheelsets, metro vehicle wheel treads should be reprofiled regularly, with a recommended reprofiling interval of 350,000 km. [ABSTRACT FROM AUTHOR]

Focusing on the problem of strip shape quality control in the finishing process of hot rolling, a shape model based on metal flow and stress release with the application of varying contact rolling parameters is introduced. Combined with digital twin technology, the digital twin framework of the shape model is proposed, which realizes the deep integration between physical time–space and virtual time–space. With the utilization of the historical data, the parameters are optimized iteratively to complete the digital twin of the shape model. According to the schedule, the raw material information is taken as the input to obtain the simulation of the strip shape, which shows a variety of export shape conditions. The prediction absolute error of the crown and flatness are less than 5 μm and 5 I-unit, respectively. The results prove that the proposed shape simulation model with strong prediction performance can be effectively applied to hot rolling production. In addition, the proposed model provides operators with a reference for the parameter settings for actual production and promotes the intelligent application of a shape control strategy. [ABSTRACT FROM AUTHOR]