A real-time posture monitoring method for rail vehicle bodies based on machine vision

Monitoring vehicle operation conditions has become significantly important in modern high-speed railway systems. However, the operational impact of monitoring the roll angle of vehicle bodies has principally been limited to tilting trains, while few studies have focused on monitoring the running posture of vehicle bodies during operation. We propose a real-time posture monitoring method to fulfil real-time monitoring requirements, by taking rail surfaces and centrelines as detection references. In realising the proposed method, we built a mathematical computational model based on space coordinate transformations to calculate attitude angles of vehicles in operation and vertical and lateral vibration displacements of single measuring points. Moreover, comparison and verification of reliability between system and field results were conducted. Results show that monitoring of the roll angles of car bodies obtained through the system exhibit variation trends similar to those converted from the dynamic deflection of bogie secondary air springs. The monitoring results of two identical conditions were basically the same, highlighting repeatability and good monitoring accuracy. Therefore, our monitoring results were reliable in reflecting posture changes in running railway vehicles.