Research on high speed railway ballastless track fastening system damage detection with the machine learning approach

Objectives: damage detection of high speed railway ballastless track fastening system, development of the dynamic model and mechanical characteristics of the fastening system with some damage pattern based on laboratory tests, analysis of dominating vibration frequencies of rail and fastening system from hammer and wheelset excitation tests, development of a novel vehicle/track coupling system model with the consideration of flexible vibration of wheel set and the feature of the fastening system deterioration, development of AI damage detection model of fastening system with the machine learning approach, establisment of alert levels, detailed guidelines for the safe operation of the high speed railway.