Abstract
Rotor-bearing systems play a vital role in machine tools, aero engines, and wind turbines. Generally, worn-induced degradation quantities and manufacturing errors of components are the main error sources that influence the precision reliability of rotor-bearing systems. The current precision reliability evaluation models are focusing on several error sources in only a few key components without agreeable results. Therefore, a precision reliability evaluation model is proposed considering all time-variant error sources and random error sources. Firstly, time-variant wear models for commonly occurred degradation types in a rotor-bearing system are developed. Secondly, the constructed time-variant wear models are inserted into the precision model with all moving components in the rotor-bearing system using meta-action structural decomposition method. Finally, the time-variant stochastic process discretization method is employed to establish the precision reliability evaluation model, and solve the precision reliability of the rotor-bearing systems. Case investigations are carried out to verify the performance of the present model, which provides a more accurate precision reliability evaluation model to estimate the conditions of rotor-bearing systems during the service period.
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Funding
This work was supported by the National Natural Science Foundation of China (No. U1909217), the Zhejiang Natural Science Foundation of China (No. LD21E050001), and the Wenzhou Major Science and Technology Innovation Project of China (No. ZG2021019, ZG2021027).
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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Hongwei Wang, Jiawei Xiang, and Yulong Li. The first draft of the manuscript was written by Hongwei Wang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Wang, H., Xiang, J., Zhao, X. et al. A kinematic precision reliability evaluation method for rotor-bearing systems considering multi-source wear degradations and random errors. Int J Adv Manuf Technol 124, 4159–4173 (2023). https://doi.org/10.1007/s00170-022-09383-x
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DOI: https://doi.org/10.1007/s00170-022-09383-x