Document Type
Article
Publication Date
2019
DOI
10.1177/1687814019853351
Publication Title
Advances in Mechanical Engineering
Volume
11
Issue
5
Pages
1-13 pp.
Abstract
Rubber sealing ring is one of the most widely used seals. It is always stored for a period of time before put into use, especially in aeronautic and aerospace applications. It is necessary to evaluate the storage lifetime of rubber sealing rings. However, due to the long storage lifetime of rubber sealing rings, two issues need to be handled, including model uncertainty and lack of storage lifetime data. A Bayesian model averaging based storage lifetime assessment method for rubber sealing rings is proposed in this article. The Gamma distribution model and Weibull distribution model are selected as the candidate models and combined based on Bayesian model averaging method. The Bayesian model averaging method is applied to handle the model uncertainty. Considering the lack of storage lifetime data, the degradation data are utilized to give the priors of model probability and distribution parameters based on the similarity principle. The results indicate that the proposed method has smaller minus log-likelihood value and is better than the other discussed method, considering both goodness of fit and complexity.
Original Publication Citation
Di, L., Shaoping, W., Chao, Z., & Tomovic, M. M. (2019). Bayesian model averaging based storage lifetime assessment method for rubber sealing rings. Advances in Mechanical Engineering, 11(5), 13 pp. doi:10.1177/1687814019853351
Repository Citation
Liu, Di; Wang, Shaoping; Zhang, Chao; and Tomovic, Mileta M., "Bayesian Model Averaging Based Storage Lifetime Assessment Method for Rubber Sealing Rings" (2019). Engineering Technology Faculty Publications. 135.
https://digitalcommons.odu.edu/engtech_fac_pubs/135
Comments
Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/ open-access-at-sage).
© The Author(s) 2019