IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v204y2020ics095183202030702x.html
   My bibliography  Save this article

An iterative information integration method for multi-level system reliability analysis based on Bayesian Melding Method

Author

Listed:
  • Xu, Yingchun
  • Yao, Wen
  • Zheng, Xiaohu
  • Chen, Xiaoqian

Abstract

For uncertainty modeling and reliability analysis of a complex system, there generally exists multi-source information, which should be fully considered and used synthetically. Research shows that the Bayesian Melding Method (BMM) is a useful tool to merge the multi-source information. However, how to apply BMM for the complex system with a multi-level hierarchical structure remains a challenging issue. To address this problem, this paper proposes an iterative information integration method for multi-level system structures so as to fully integrate the information between different levels. A complete single iteration consists of the updating process from the system bottom to top level and then from the system top to bottom level. To facilitate the updating process, the complex multi-level system is first decomposed into several basic double-level units, within which the information integration can be conveniently conducted with the proposed discrete or continuous BMM methods. To check the iteration convergence, the symmetric Kullback-Leibler Divergence (SKLD) is adopted to measure the difference between the updated system distributions obtained in the two consecutive iteration processes.Finally, three case studies with discrete and continuous information integration problems are used to demonstrate and validate the proposed method.

Suggested Citation

  • Xu, Yingchun & Yao, Wen & Zheng, Xiaohu & Chen, Xiaoqian, 2020. "An iterative information integration method for multi-level system reliability analysis based on Bayesian Melding Method," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
  • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s095183202030702x
    DOI: 10.1016/j.ress.2020.107201
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202030702X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2020.107201?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. Guo, Jian & (Steven) Li, Zhaojun & (Judy) Jin, Jionghua, 2018. "System reliability assessment with multilevel information using the Bayesian melding method," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 146-158.
    2. Wang, Lizhi & Pan, Rong & Wang, Xiaohong & Fan, Wenhui & Xuan, Jinquan, 2017. "A Bayesian reliability evaluation method with different types of data from multiple sources," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 128-135.
    3. Karanki, D.R. & Rahman, S. & Dang, V.N. & Zerkak, O., 2017. "Epistemic and aleatory uncertainties in integrated deterministic and probabilistic safety assessment: Tradeoff between accuracy and accident simulations," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 91-102.
    4. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xianqi, 2019. "Improved compression inference algorithm for reliability analysis of complex multistate satellite system based on multilevel Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 123-142.
    5. Yao, Wen & Chen, Xiaoqian & Huang, Yiyong & van Tooren, Michel, 2013. "An enhanced unified uncertainty analysis approach based on first order reliability method with single-level optimization," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 28-37.
    6. Mark A Burgman & Marissa McBride & Raquel Ashton & Andrew Speirs-Bridge & Louisa Flander & Bonnie Wintle & Fiona Fidler & Libby Rumpff & Charles Twardy, 2011. "Expert Status and Performance," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-7, July.
    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. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Wang, Ning, 2024. "Algorithms for Bayesian network modeling and reliability inference of complex multistate systems with common cause failure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Jia, Xiang & Guo, Bo, 2022. "Reliability analysis for complex system with multi-source data integration and multi-level data transmission," Reliability Engineering and System Safety, Elsevier, vol. 217(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. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    2. Zheng, Xiaohu & Yao, Wen & Zhang, Yunyang & Zhang, Xiaoya, 2022. "Consistency regularization-based deep polynomial chaos neural network method for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    3. Yingchun Xu & Xiaohu Zheng & Wen Yao & Ning Wang & Xiaoqian Chen, 2021. "A sequential multi-prior integration and updating method for complex multi-level system based on Bayesian melding method," Journal of Risk and Reliability, , vol. 235(5), pages 863-876, October.
    4. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xianqi, 2019. "Improved compression inference algorithm for reliability analysis of complex multistate satellite system based on multilevel Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 123-142.
    5. Damircheli, Mahrad & Fakoor, Mahdi & Yadegari, Hamed, 2020. "Failure assessment logic model (FALM): A new approach for reliability analysis of satellite attitude control subsystem," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Chen, Xiaoqian, 2020. "Algorithms for Bayesian network modeling and reliability inference of complex multistate systems: Part I – Independent systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    7. Jia, Xiang & Guo, Bo, 2022. "Reliability analysis for complex system with multi-source data integration and multi-level data transmission," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    8. Zheng, Xiaohu & Yao, Wen & Zhang, Xiaoya & Qian, Weiqi & Zhang, Hairui, 2023. "Parameterized coefficient fine-tuning-based polynomial chaos expansion method for sphere-biconic reentry vehicle reliability analysis and design," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    9. Guo, Zehua & Dailey, Ryan & Feng, Tangtao & Zhou, Yukun & Sun, Zhongning & Corradini, Michael L & Wang, Jun, 2021. "Uncertainty analysis of ATF Cr-coated-Zircaloy on BWR in-vessel accident progression during a station blackout," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    10. Jean Hugé & Nibedita Mukherjee & Camille Fertel & Jean-Philippe Waaub & Thomas Block & Tom Waas & Nico Koedam & Farid Dahdouh-Guebas, 2015. "Conceptualizing the Effectiveness of Sustainability Assessment in Development Cooperation," Sustainability, MDPI, vol. 7(5), pages 1-17, May.
    11. Huimin Wang & Zhaojun Steven Li, 2022. "An AdaBoost-based tree augmented naive Bayesian classifier for transient stability assessment of power systems," Journal of Risk and Reliability, , vol. 236(3), pages 495-507, June.
    12. Zheng, Xiaohu & Yao, Wen & Xu, Yingchun & Wang, Ning, 2024. "Algorithms for Bayesian network modeling and reliability inference of complex multistate systems with common cause failure," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    13. Bellaera, R. & Bonifetto, R. & Di Maio, F. & Pedroni, N. & Savoldi, L. & Zanino, R. & Zio, E., 2020. "Integrated deterministic and probabilistic safety assessment of a superconducting magnet cryogenic cooling circuit for nuclear fusion applications," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    14. Geng, Sunyue & Liu, Sifeng & Fang, Zhigeng, 2021. "Resilient communication model for satellite networks using clustering technique," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Chen, Wen-Bin & Li, Xiao-Yang & Kang, Rui, 2022. "Integration for degradation analysis with multi-source ADT datasets considering dataset discrepancies and epistemic uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    16. Anca M. Hanea & Marissa F. McBride & Mark A. Burgman & Bonnie C. Wintle, 2018. "The Value of Performance Weights and Discussion in Aggregated Expert Judgments," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1781-1794, September.
    17. Woike, Jan K. & Hoffrage, Ulrich & Petty, Jeffrey S., 2015. "Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making," Journal of Business Research, Elsevier, vol. 68(8), pages 1705-1716.
    18. Anna Chrysafi & Vili Virkki & Mika Jalava & Vilma Sandström & Johannes Piipponen & Miina Porkka & Steven J. Lade & Kelsey Mere & Lan Wang-Erlandsson & Laura Scherer & Lauren S. Andersen & Elena Bennet, 2022. "Quantifying Earth system interactions for sustainable food production via expert elicitation," Nature Sustainability, Nature, vol. 5(10), pages 830-842, October.
    19. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    20. Yang Song & Yawen Wang & Dahai Jin, 2020. "A Bayesian Approach Based on Bayes Minimum Risk Decision for Reliability Assessment of Web Service Composition," Future Internet, MDPI, vol. 12(12), pages 1-20, December.

    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:204:y:2020:i:c:s095183202030702x. 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.