A Dual-Branch Deep Learning Framework for Macroscopic Area and Microscopic Contour Prediction of EMU Wheelset Wear
Accurately predicting the nonlinear degradation trajectories of electric multiple-unit (EMU) wheelset treads is crucial for ensuring dynamic safety and optimizing predictive maintenance. However, existing data-driven methods struggle to simultaneously quantify macroscopic material loss and reconstruct microscopic worn...