IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v182y2019icp120-132.html
   My bibliography  Save this article

Trans-layer model learning: A hierarchical modeling strategy for real-time reliability evaluation of complex systems

Author

Listed:
  • Tan, Zhixue
  • Zhong, Shisheng
  • Lin, Lin

Abstract

Techniques addressing the loading condition of components in complex systems are of great significance for the real-time reliability analyses of systems. To recover component observabilities with combined condition monitoring data and empirical rules, an information criterion identifying the necessary data/rule set for the modeling of systems with the same hierarchical topologies to real-in-world realizations, referred to as trans-layer model learning (TLML), is proposed and proved. Then, with regard to general multi-component dynamic systems, a specific TLML algorithm is proposed. In this algorithm, the loss function and alternative training scheme of component models are specified for harnessing the information from sensor readings and empirical rules to serve the modeling. TLML is applied first on a simulation system to testify its ability to reveal component loading conditions, and then on an aircraft engine to test its effectiveness in improving the Residual Useful Life (RUL) prediction performance of engine turbine blades. Results show that TLML can provide real-time estimations of component loading conditions with sufficient accuracy, and thus improve the precision and reliability of the RUL estimation of system parts.

Suggested Citation

  • Tan, Zhixue & Zhong, Shisheng & Lin, Lin, 2019. "Trans-layer model learning: A hierarchical modeling strategy for real-time reliability evaluation of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 120-132.
    • Handle: RePEc:eee:reensy:v:182:y:2019:i:c:p:120-132
    DOI: 10.1016/j.ress.2018.09.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018302047
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2018.09.016?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. Yann LeCun & Yoshua Bengio & Geoffrey Hinton, 2015. "Deep learning," Nature, Nature, vol. 521(7553), pages 436-444, May.
    2. Li, Heping & Deloux, Estelle & Dieulle, Laurence, 2016. "A condition-based maintenance policy for multi-component systems with Lévy copulas dependence," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 44-55.
    3. Peng, Weiwen & Li, Yan-Feng & Yang, Yuan-Jian & Huang, Hong-Zhong & Zuo, Ming J., 2014. "Inverse Gaussian process models for degradation analysis: A Bayesian perspective," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 175-189.
    4. Barker, C.T. & Newby, M.J., 2009. "Optimal non-periodic inspection for a multivariate degradation model," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 33-43.
    5. Zhou, Xiaojun & Huang, Kaimin & Xi, Lifeng & Lee, Jay, 2015. "Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 231-237.
    6. Izenman, Alan Julian, 1975. "Reduced-rank regression for the multivariate linear model," Journal of Multivariate Analysis, Elsevier, vol. 5(2), pages 248-264, June.
    7. Rasmekomen, Nipat & Parlikad, Ajith Kumar, 2016. "Condition-based maintenance of multi-component systems with degradation state-rate interactions," Reliability Engineering and System Safety, Elsevier, vol. 148(C), pages 1-10.
    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. Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," 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. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    2. Xia, Tangbin & Xi, Lifeng & Pan, Ershun & Ni, Jun, 2017. "Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 87-98.
    3. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    4. Wang, Jun & Zhu, Xiaoyan, 2021. "Joint optimization of condition-based maintenance and inventory control for a k-out-of-n:F system of multi-state degrading components," European Journal of Operational Research, Elsevier, vol. 290(2), pages 514-529.
    5. Liu, Jie & Zio, Enrico, 2017. "Weighted-feature and cost-sensitive regression model for component continuous degradation assessment," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 210-217.
    6. Zhang, Nan & Cai, Kaiquan & Zhang, Jun & Wang, Tian, 2022. "A condition-based maintenance policy considering failure dependence and imperfect inspection for a two-component system," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    7. Yang, Ao & Qiu, Qingan & Zhu, Mingren & Cui, Lirong & Chen, Weilin & Chen, Jianhui, 2022. "Condition-based maintenance strategy for redundant systems with arbitrary structures using improved reinforcement learning," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    8. Nguyen, Kim-Anh & Do, Phuc & Grall, Antoine, 2017. "Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 249-261.
    9. 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).
    10. Zhang, Chengjie & Qi, Faqun & Zhang, Ning & Li, Yong & Huang, Hongzhong, 2022. "Maintenance policy optimization for multi-component systems considering dynamic importance of components," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    11. Olde Keizer, Minou C.A. & Teunter, Ruud H. & Veldman, Jasper, 2017. "Joint condition-based maintenance and inventory optimization for systems with multiple components," European Journal of Operational Research, Elsevier, vol. 257(1), pages 209-222.
    12. Uit Het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1119-1131.
    13. Wu, Tianyi & Yang, Li & Ma, Xiaobing & Zhang, Zihan & Zhao, Yu, 2020. "Dynamic maintenance strategy with iteratively updated group information," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    14. Olde Keizer, Minou C.A. & Flapper, Simme Douwe P. & Teunter, Ruud H., 2017. "Condition-based maintenance policies for systems with multiple dependent components: A review," European Journal of Operational Research, Elsevier, vol. 261(2), pages 405-420.
    15. Li, Heping & Zhu, Wenjin & Dieulle, Laurence & Deloux, Estelle, 2022. "Condition-based maintenance strategies for stochastically dependent systems using Nested Lévy copulas," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    16. Zhang, Nailong & Si, Wujun, 2020. "Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    17. Xia, Tangbin & Sun, Bowen & Chen, Zhen & Pan, Ershun & Wang, Hao & Xi, Lifeng, 2021. "Opportunistic maintenance policy integrating leasing profit and capacity balancing for serial-parallel leased systems," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    18. Zhao, Yixin & Cozzani, Valerio & Sun, Tianqi & Vatn, Jørn & Liu, Yiliu, 2023. "Condition-based maintenance for a multi-component system subject to heterogeneous failure dependences," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    19. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    20. Liu, Bin & Pandey, Mahesh D. & Wang, Xiaolin & Zhao, Xiujie, 2021. "A finite-horizon condition-based maintenance policy for a two-unit system with dependent degradation processes," European Journal of Operational Research, Elsevier, vol. 295(2), pages 705-717.

    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:182:y:2019:i:c:p:120-132. 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.