Dynamic stress characteristics of bogie frames of high-speed trains and the life prediction study

Based on the line tracking test, the dynamic stress characteristics and fatigue reliability of critical areas in the bogie frame are investigated to address the problem of high-speed train bogie frame fatigue life prediction. The measured data are extracted based on the stress-time relationship, and the dynamic stress characteristics of each measurement point on the bogie are analyzed in both the time and frequency domains to examine changes in the bogie's dynamic stress during testing. Fatigue tests on the materials used in the bogie frames are conducted and combined with the modified Corten-Dolan nonlinear cumulative damage model to analyze the sensitivity of damage values at each measurement point to variations in material parameters under different survival rates, as well as the contribution of damage at each point under various working conditions. The measured dynamic stress data of the frame are segmented, and the relationship between accumulated test mileage and damage at each measurement point is calculated. Corresponding regression equations are fitted using the orthogonal distance regression algorithm and verified to predict the fatigue life of the bogie frame. The study results indicate that the sensitivity of damage at each measurement point to changes in material parameters significantly varies at different survival rates, with the damage values at points in the transverse damper region showing the highest sensitivity to parameter changes. The method of evaluating the bogie frame's life based on regression equations is reliable. The predicted lives of the frame based on the standard parameters of BS 7608 and the parameters of the P-S-N curves are 8.91×10 9 and 2.09×10 10 m, respectively, suggesting that the design of the bogie frame using grade QA and SMA materials meets the criteria for its intended design life. This research proposes a life prediction method based on a regression equation, which is reliable and can accurately assess the fatigue life of high-speed train bogies.