IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v215y2021ics0951832021004257.html
   My bibliography  Save this article

Correlation reliability assessment of artillery chassis transmission system based on CBN model

Author

Listed:
  • Ding, Feng
  • Wang, Yihua
  • Ma, Guoliang
  • Zhang, Xinrui

Abstract

The traditional Bayesian Network (BN) has defects in the reliability assessment problem of multivariate correlation. In this paper, the Copula Bayesian Network (CBN) model is introduced into the artillery chassis transmission system for the first time to solve these problems. The model uses the Copula function to express the relationship between variables, and combines Bayesian Network probabilistic reasoning. On the basis of the traditional BN topology structure, the Copula function is introduced and transformed into CBN topology structure. The edge distribution of each node and the correlation coefficient matrix are used to construct the local connection function. It can realize the conversion of multi-variables into binary variables and construct high-dimensional functions. Bayesian network reasoning can get the failure probability of each node. Finally, the CBN model was used to assess the reliability of a certain type of artillery chassis transmission system for the first time. This method converts the multiple variables of the transmission system into a binary relationship, which is suitable for engineering applications and can express the correlation in the system. The computational result of this model is better than that of the traditional BN model.

Suggested Citation

  • Ding, Feng & Wang, Yihua & Ma, Guoliang & Zhang, Xinrui, 2021. "Correlation reliability assessment of artillery chassis transmission system based on CBN model," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021004257
    DOI: 10.1016/j.ress.2021.107908
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832021004257
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2021.107908?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lee, Dooyoul & Choi, Dongsu, 2020. "Analysis of the reliability of a starter-generator using a dynamic Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    2. Renyan Jiang, 2015. "Introduction to Quality and Reliability Engineering," Springer Series in Reliability Engineering, Springer, edition 127, number 978-3-662-47215-6, January.
    3. Pan, Yue & Ou, Shenwei & Zhang, Limao & Zhang, Wenjing & Wu, Xianguo & Li, Heng, 2019. "Modeling risks in dependent systems: A Copula-Bayesian approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 416-431.
    4. Fang, Guanqi & Pan, Rong & Hong, Yili, 2020. "Copula-based reliability analysis of degrading systems with dependent failures," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Zheng, Xiao-Wei & Li, Hong-Nan & Gardoni, Paolo, 2023. "Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    3. Chen, Rentong & Zhang, Chao & Wang, Shaoping & Zio, Enrico & Dui, Hongyan & Zhang, Yadong, 2023. "Importance measures for critical components in complex system based on Copula Hierarchical Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 230(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hajiha, Mohammadmahdi & Liu, Xiao & Lee, Young M. & Ramin, Moghaddass, 2022. "A physics-regularized data-driven approach for health prognostics of complex engineered systems with dependent health states," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Li, Yaohan & Dong, You & Guo, Hongyuan, 2023. "Copula-based multivariate renewal model for life-cycle analysis of civil infrastructure considering multiple dependent deterioration processes," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    3. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    4. Jiang, Deyin & Chen, Tianyu & Xie, Juanzhang & Cui, Weimin & Song, Bifeng, 2023. "A mechanical system reliability degradation analysis and remaining life estimation method——With the example of an aircraft hatch lock mechanism," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    5. Zhiqiang Liu & Wenbo Zhu & Hongzhou Zhang & Shengjin Wang & Lu Fang & Weijun Hong & Hua Shao & Guopeng Wang, 2020. "Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network," International Journal of Distributed Sensor Networks, , vol. 16(3), pages 15501477209, March.
    6. Sun, Fuqiang & Fu, Fangyou & Liao, Haitao & Xu, Dan, 2020. "Analysis of multivariate dependent accelerated degradation data using a random-effect general Wiener process and D-vine Copula," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Bahareh Tajiani & Jørn Vatn, 2023. "Adaptive remaining useful life prediction framework with stochastic failure threshold for experimental bearings with different lifetimes under contaminated condition," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1756-1777, October.
    8. Zhang, Jiusi & Jiang, Yuchen & Li, Xiang & Huo, Mingyi & Luo, Hao & Yin, Shen, 2022. "An adaptive remaining useful life prediction approach for single battery with unlabeled small sample data and parameter uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    9. Liang, Qingzhu & Yang, Yinghao & Peng, Changhong, 2023. "A reliability model for systems subject to mutually dependent degradation processes and random shocks under dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    10. Chengye Ma & Yongjun Du & Lijun Shang & Li Yang & Kaiye Gao, 2023. "Random Maintenance Strategy Modeling of Warranted Products with Reliability Heterogeneity," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
    11. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    12. Zheng, Xiao-Wei & Li, Hong-Nan & Gardoni, Paolo, 2023. "Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    13. Liu, Wenli & Chen, Elton J. & Yao, Erlei & Wang, Yanyu & Chen, Yangyang, 2021. "Reliability analysis of face stability for tunnel excavation in a dependent system," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    14. Minhe Luo & Ding Wang & Xuchun Wang & Zelin Lu, 2023. "Analysis of Surface Settlement Induced by Shield Tunnelling: Grey Relational Analysis and Numerical Simulation Study on Critical Construction Parameters," Sustainability, MDPI, vol. 15(19), pages 1-21, September.
    15. Wang, Fan & Li, Heng & Dong, Chao, 2021. "Understanding near-miss count data on construction sites using greedy D-vine copula marginal regression," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    16. Eryilmaz, Serkan & Ozkut, Murat, 2020. "Optimization problems for a parallel system with multiple types of dependent components," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    17. Xu, Jun & Liang, Zhenglin & Li, Yan-Fu & Wang, Kaibo, 2021. "Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    18. Wang, Yueyao & Lee, I-Chen & Hong, Yili & Deng, Xinwei, 2022. "Building degradation index with variable selection for multivariate sensory data," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    19. Saberzadeh, Zahra & Razmkhah, Mostafa & Amini, Mohammad, 2023. "Bayesian reliability analysis of complex k-out-of-n: â„“ systems under degradation performance," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    20. Liu, Lujie & Yang, Jun & Kong, Xuefeng & Xiao, Yiyong, 2022. "Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations," Reliability Engineering and System Safety, Elsevier, vol. 219(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021004257. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.