IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v13y2024i1p123-d1557572.html
   My bibliography  Save this article

Fuzzy Fault Tree Maintenance Decision Analysis for Aviation Fuel Pumps Based on Nutcracker Optimization Algorithm–Graph Neural Network Improvement

Author

Listed:
  • Weidong He

    (The School of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China)

  • Xiaojing Yin

    (The School of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China)

  • Yubo Shao

    (The School of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China)

  • Dianxin Chen

    (The School of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China)

  • Jianglong Mi

    (The School of Mechanical and Electrical Engineering, Changchun University of Technology, Changchun 130012, China)

  • Yang Jiao

    (Aviation Foundation Institute, Air Force Aviation University, Changchun 130012, China)

Abstract

As a critical component of the engine, the failure of aviation fuel pumps can lead to serious safety accidents, necessitating the development of effective maintenance programs. Fault Tree Analysis (FTA) has a clear structure and strong interpretability in maintenance decision making. However, it heavily relies on expert knowledge, which is subject to uncertainty and incoherence. Therefore, this paper proposes the NOA (Nutcracker Optimization Algorithm)–GNN (Graph Neural Network) model to enhance the accuracy and robustness of FTA by mitigating the uncertainty and inconsistency in expert knowledge. The NOA algorithm efficiently searches the solution space to identify globally optimal solutions. An FTA-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) maintenance decision-making framework has also been developed. By integrating FTA with TOPSIS, the proposed method provides a comprehensive and systematic approach that combines qualitative and quantitative analyses, thereby improving the effectiveness and reliability of maintenance decision making.

Suggested Citation

  • Weidong He & Xiaojing Yin & Yubo Shao & Dianxin Chen & Jianglong Mi & Yang Jiao, 2024. "Fuzzy Fault Tree Maintenance Decision Analysis for Aviation Fuel Pumps Based on Nutcracker Optimization Algorithm–Graph Neural Network Improvement," Mathematics, MDPI, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:gam:jmathe:v:13:y:2024:i:1:p:123-:d:1557572
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/13/1/123/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/13/1/123/
    Download Restriction: no
    ---><---

    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:gam:jmathe:v:13:y:2024:i:1:p:123-:d:1557572. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.