Virtual point tracking method for online detection of relative wheel-rail displacement of railway vehicles

Abstract

Relative wheel-rail displacement (RWRD) is an important physical quantity that responds to the hunting stability and running safety of railway vehicles but detecting this physical quantity is challenging during train operation due to the complex service environment and the nonlinearity of vehicle-rail system. To address this problem, this paper proposes a virtual point tracking (VPT) method to detect RWRD. First, a series of regions of interest (ROIs) in the preprocessed wheel-rail contact images are extracted using a simplified YOLO (SYOLO) model. Then, some key positions of the wheel and rail on the extracted ROIs are identified using an improved UNet (IUNet) model and characterized by virtual points. Finally, the global coordinates of the virtual points in the whole wheel-rail contact image are calculated to obtain the final RWRD. To demonstrate the feasibility of the VPT method, it is used to detect the RWRD of a vehicle operating on a full-scale roller rig. For comparison, the original UNet model is directly used to detect the RWRD. Two quantities, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), are applied for quantitative analysis and the results show that the VPT method can identify the RWRD more reliably and accurately.