Journal
MECHANISM AND MACHINE THEORY
Volume 163, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.mechmachtheory.2021.104385
Keywords
Dynamic reliability; Wear and vibration; Multi-falilure modes; Active learning kriging; Linear guide; Machine tool worktable system
Categories
Funding
- Excellent Youth Foundation of Jiangsu Scientific Committee [BK20200029]
- Chinese National Natural Science Foundation [U1810124]
- NationalNatural Science Foundation of China [51875567]
- Fundamental Research Funds for the Central Universities [2020QN57]
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The wear and vibration of machine tool system are coupled and time-variant, influencing the dynamic performance of machine tool feed drive system. This study proposes a dynamic reliability approach to evaluate the system under multi-failure modes, improving calculation efficiency. Additionally, reliability-based sensitivity indices are presented to investigate the significance of random parameters.
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 fail-ure mechanisms considering the uncertainty of parameters. To evaluate the dynamic re-liability 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. (c) 2021 Elsevier Ltd. All rights reserved.
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