The long-term monitoring of car-body vibration displacement when a high-speed train passes through complex terrain sections in windy conditions has become an urgent engineering problem in China. However, few studies have focused on this topic, and an effective engineering long-term monitoring method is lacking in China. In this study, by combining the vibration characteristics and structural characteristics of railway vehicles, a real-time car-body displacement monitoring method to fulfill monitoring requirements was proposed, and a mathematical computational model based on space coordinate transformations to calculate the car-body displacements in operation was developed. Moreover, the comparison and the verification of the monitoring system accuracy were conducted using full-scale tests. The results showed that the displacement of the car-body relative to the bogie frame obtained through the system was consistent with the real vibration state of the car-body. Therefore, our monitoring system was reliable in reflecting the car-body vibration displacement changes in high-speed trains that were in motion.
An efficient anomaly detection for high-speed train braking system using broad learning system
