Dynamic reliability analysis of mechanical system with wear and vibration failure modes

The wear and vibration of machine tool system are coupled and time-variant, which have significant influences on the dynamic performance of machine tool feed drive system in different time scales. In this study, the coupling effects between the wear of linear guide and the vibration of machine worktable system are studied based on the infinitesimal method. A nonlinear dynamic model is developed to analyze the wear and vibration failure mechanisms considering the uncertainty of parameters. To evaluate the dynamic reliability of the machine worktable system under multi-failure modes, a time-variant and conditional reliability approach based on the active learning Kriging model and Monte Carlo Simulation is proposed. The approach gets rid of repeated calculating of the real limit state function values and the calculation efficiency is enhanced greatly. Additionally, reliability-based sensitivity indices are presented to investigate the significance of random parameters to the reliability of the system. Besides of the reliability analysis for machine worktable systems, the proposed framework and corresponding method are also suitable for the reliability evaluation of other complex mechanical systems with the conditional multi-failure modes.