IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v235y2023ics0951832023001333.html
   My bibliography  Save this article

Operational reliability evaluation and analysis framework of civil aircraft complex system based on intelligent extremum machine learning model

Author

Listed:
  • Jia-Qi, Liu
  • Yun-Wen, Feng
  • Da, Teng
  • Jun-Yu, Chen
  • Cheng, Lu

Abstract

To reasonably implement the operational reliability analysis and describe the importance of the influencing parameters for the operation status, a framework for operational reliability evaluation and analysis is proposed. First, an operational reliability evaluation model (OREM) is established based on the data envelopment analysis (DEA) method, which takes quick access recorder (QAR)data as input to comprehensively evaluate the operational characteristics of complex systems to obtain the operational reliability Pr. Then, to enhance the modeling efficiency and simulation performance for the operational reliability analysis of the complex system, we propose an intelligent extremum machine learning model (IEMLM), by integrating extremum response surface method (ERSM), artificial neural network (ANN), improved particle swarm optimization (PSO) algorithm, and Bayesian regularization (BR) algorithm. The operational reliability analysis of a braking system of a civil aircraft is conducted to validate the effectiveness and feasibility of this developed method, by considering the comprehensive influence of system-environment-human. The comparison of IEMLM, RF, and ANN shows that IEMLM improves the analysis accuracy and calculation efficiency. The proposed framework and models can provide useful references for civil aircraft operational reliability analysis, special situation treatment, maintenance, and design.

Suggested Citation

  • Jia-Qi, Liu & Yun-Wen, Feng & Da, Teng & Jun-Yu, Chen & Cheng, Lu, 2023. "Operational reliability evaluation and analysis framework of civil aircraft complex system based on intelligent extremum machine learning model," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    • Handle: RePEc:eee:reensy:v:235:y:2023:i:c:s0951832023001333
    DOI: 10.1016/j.ress.2023.109218
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832023001333
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2023.109218?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, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    2. He, Jingjing & Huang, Min & Wang, Wei & Wang, Shaohua & Guan, Xuefei, 2021. "An asymptotic stochastic response surface approach to reliability assessment under multi-source heterogeneous uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Lu, Cheng & Teng, Da & Chen, Jun-Yu & Fei, Cheng-Wei & Keshtegar, Behrooz, 2023. "Adaptive vectorial surrogate modeling framework for multi-objective reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Chen, Jun-Yu & Feng, Yun-Wen & Teng, Da & Lu, Cheng & Fei, Cheng-Wei, 2022. "Support vector machine-based similarity selection method for structural transient reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    5. Tiassou, Kossi & Kanoun, Karama & Kaâniche, Mohamed & Seguin, Christel & Papadopoulos, Chris, 2013. "Aircraft operational reliability—A model-based approach and a case study," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 163-176.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Guo, Yongjin & Wang, Hongdong & Guo, Yu & Zhong, Mingjun & Li, Qing & Gao, Chao, 2022. "System operational reliability evaluation based on dynamic Bayesian network and XGBoost," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    8. Matthias Schonlau & Rosie Yuyan Zou, 2020. "The random forest algorithm for statistical learning," Stata Journal, StataCorp LP, vol. 20(1), pages 3-29, March.
    9. Keshtegar, Behrooz & Kisi, Ozgur, 2018. "RM5Tree: Radial basis M5 model tree for accurate structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 49-61.
    10. Zhu, Shun-Peng & Huang, Hong-Zhong & Peng, Weiwen & Wang, Hai-Kun & Mahadevan, Sankaran, 2016. "Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 1-12.
    11. Sarazin, Gabriel & Morio, Jérôme & Lagnoux, Agnès & Balesdent, Mathieu & Brevault, Loïc, 2021. "Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    12. Zio, E., 2009. "Reliability engineering: Old problems and new challenges," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 125-141.
    13. Gao, Shuzhi & Zhang, Sixuan & Zhang, Yimin & Gao, Yue, 2020. "Operational reliability evaluation and prediction of rolling bearing based on isometric mapping and NoCuSa-LSSVM," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    14. Lee, Seunggyu, 2021. "Monte Carlo simulation using support vector machine and kernel density for failure probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    15. Jenab, K. & Rashidi, K., 2009. "Operational reliability assessment of an aircraft environmental control system," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 456-462.
    16. Roland Müller & Christopher Drax, 2014. "Operational Risk Management as an Integrated Part of Safety Management Systems," Management for Professionals, in: Roland Müller & Andreas Wittmer & Christopher Drax (ed.), Aviation Risk and Safety Management, edition 127, chapter 7, pages 73-76, Springer.
    17. Wang, Lei & Wu, Changxu & Sun, Ruishan, 2014. "An analysis of flight Quick Access Recorder (QAR) data and its applications in preventing landing incidents," Reliability Engineering and System Safety, Elsevier, vol. 127(C), pages 86-96.
    18. Betz, Wolfgang & Papaioannou, Iason & Straub, Daniel, 2022. "Bayesian post-processing of Monte Carlo simulation in reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 227(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. Zhang, Ruixing & An, Liqiang & He, Lun & Yang, Xinmeng & Huang, Zenghao, 2024. "Reliability analysis and inverse optimization method for floating wind turbines driven by dual meta-models combining transient-steady responses," Reliability Engineering and System Safety, Elsevier, vol. 244(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. Jia-Qi, Liu & Yun-Wen, Feng & Cheng, Lu & Wei-Huang, Pan, 2024. "Decomposed-coordinated framework with intelligent extremum network for operational reliability analysis of complex system," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Pan, Wei-Huang & Feng, Yun-Wen & Lu, Cheng & Liu, Jia-Qi, 2023. "Analyzing the operation reliability of aeroengine using Quick Access Recorder flight data," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Bui, Ha & Sakurahara, Tatsuya & Pence, Justin & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 405-428.
    4. Zhang, Zheng & Wang, Pan & Hu, Huanhuan & Li, Lei & Li, Haihe & Yue, Zhufeng, 2022. "Efficient reliability-based design optimization for hydraulic pipeline with adaptive sampling region," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    5. Khalili-Damghani, Kaveh & Amiri, Maghsoud, 2012. "Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 35-44.
    6. Li, Xin & Yang, Yu & Wu, Zhantao & Yan, Ke & Shao, Haidong & Cheng, Junsheng, 2022. "High-accuracy gearbox health state recognition based on graph sparse random vector functional link network," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    7. Wang, Yanzhong & Xie, Bin & E, Shiyuan, 2022. "Adaptive relevance vector machine combined with Markov-chain-based importance sampling for reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    8. Teng, Da & Feng, Yun-Wen & Chen, Jun-Yu & Liu, Jia-Qi & Lu, Cheng, 2024. "Multi-polynomial chaos Kriging-based adaptive moving strategy for comprehensive reliability analyses," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    9. Chiachío, Manuel & Saleh, Ali & Naybour, Susannah & Chiachío, Juan & Andrews, John, 2022. "Reduction of Petri net maintenance modeling complexity via Approximate Bayesian Computation," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Gao, Haifeng & Wang, Anjenq & Zio, Enrico & Bai, Guangchen, 2020. "An integrated reliability approach with improved importance sampling for low-cycle fatigue damage prediction of turbine disks," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    11. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.
    12. repec:lan:wpaper:1115 is not listed on IDEAS
    13. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    14. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    15. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    16. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    17. Bowlin, W. F., 1995. "A characterization of the financial condition of the United States' aerospace-defense industrial base," Omega, Elsevier, vol. 23(5), pages 539-555, October.
    18. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    19. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    20. Helmi Hammami & Thanh Ngo & David Tripe & Dinh-Tri Vo, 2022. "Ranking with a Euclidean common set of weights in data envelopment analysis: with application to the Eurozone banking sector," Annals of Operations Research, Springer, vol. 311(2), pages 675-694, April.
    21. Sascha O. Becker, Sascha O & Voth, Hans-Joachim, 2023. "From the Death of God to the Rise of Hitler," The Warwick Economics Research Paper Series (TWERPS) 1478, University of Warwick, Department of Economics.

    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:235:y:2023:i:c:s0951832023001333. 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.