IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i13p2843-d1178553.html
   My bibliography  Save this article

A Reliability-Based Robust Design Optimization Method for Rolling Bearing Fatigue under Cyclic Load Spectrum

Author

Listed:
  • Shiyuan E

    (School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China)

  • Yanzhong Wang

    (School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China)

  • Bin Xie

    (School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China)

  • Fengxia Lu

    (National Key Laboratory of Science and Technology on Helicopter Transmission, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

Reliability-based robust design methods have been widely used in the field of product design; however, they are difficult to apply to the fatigue reliability design process of rolling bearings due to the problems of determining fatigue accumulated damage caused by the internal cyclic time-varying load distribution of rolling bearings and the computational cost of time-varying reliability. Therefore, a reliability-based robust design method for rolling bearing fatigue failure is proposed, which derives the formula for fatigue accumulated damage of a rolling bearing under cyclic load spectrum and significantly reduces the computational cost of rolling bearing time-varying reliability compared with existing methods. First, the state response of a rolling bearing under random design parameters is obtained by finite element simulation. Then, the adaptive kriging method is used to characterize the correlation between the random parameters and the state response. The Miner fatigue cumulative damage theory is improved and the rolling bearing fatigue time-varying equation of state under cyclic load spectrum is derived. Subsequently, a fatigue time-varying reliability model based on an improved fourth-order moment method is developed, and a reliability robust optimization design method is proposed. Finally, a rolling bearing example is presented to demonstrate that the method achieves time-varying fatigue reliability design under cyclic load spectrum and effectively improves the reliability and robustness of the product design.

Suggested Citation

  • Shiyuan E & Yanzhong Wang & Bin Xie & Fengxia Lu, 2023. "A Reliability-Based Robust Design Optimization Method for Rolling Bearing Fatigue under Cyclic Load Spectrum," Mathematics, MDPI, vol. 11(13), pages 1-16, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2843-:d:1178553
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/13/2843/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/13/2843/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liao, Ding & Zhu, Shun-Peng & Correia, José A.F.O. & De Jesus, Abílio M.P. & Veljkovic, Milan & Berto, Filippo, 2022. "Fatigue reliability of wind turbines: historical perspectives, recent developments and future prospects," Renewable Energy, Elsevier, vol. 200(C), pages 724-742.
    2. Kam, Olle Michel & Noël, Stéphane & Ramenah, Harry & Kasser, Pierre & Tanougast, Camel, 2021. "Comparative Weibull distribution methods for reliable global solar irradiance assessment in France areas," Renewable Energy, Elsevier, vol. 165(P1), pages 194-210.
    3. Tian Cheng & Dylan Dah-Chuan Lu & Yam P. Siwakoti, 2022. "Circuit-Based Rainflow Counting Algorithm in Application of Power Device Lifetime Estimation," Energies, MDPI, vol. 15(14), pages 1-13, July.
    4. Shuto, Susumu & Amemiya, Takashi, 2022. "Sequential Bayesian inference for Weibull distribution parameters with initial hyperparameter optimization for system reliability estimation," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    5. Iannacone, Leandro & Sharma, Neetesh & Tabandeh, Armin & Gardoni, Paolo, 2022. "Modeling Time-varying Reliability and Resilience of Deteriorating Infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Hau T. Mai & Jaewook Lee & Joowon Kang & H. Nguyen-Xuan & Jaehong Lee, 2022. "An Improved Blind Kriging Surrogate Model for Design Optimization Problems," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
    7. Yingbin Chai & Kangye Huang & Shangpan Wang & Zhichao Xiang & Guanjun Zhang, 2023. "The Extrinsic Enriched Finite Element Method with Appropriate Enrichment Functions for the Helmholtz Equation," Mathematics, MDPI, vol. 11(7), pages 1-25, March.
    Full references (including those not matched with items on IDEAS)

    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. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Liu, Juncai & Tian, Li & Yang, Meng & Meng, Xiangrui, 2024. "Probabilistic framework for seismic resilience assessment of transmission tower-line systems subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    4. Liang, Zhenglin & Li, Yan-Fu, 2023. "Holistic Resilience and Reliability Measures for Cellular Telecommunication Networks," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    5. Sun, Qin & Li, Hongxu & Wang, Yuzhi & Zhang, Yingchao, 2022. "Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    6. Phan, Hieu Chi & Dhar, Ashutosh Sutra & Bui, Nang Duc, 2023. "Reliability assessment of pipelines crossing strike-slip faults considering modeling uncertainties using ANN models," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Yu, Juanya & Sharma, Neetesh & Gardoni, Paolo, 2024. "Functional connectivity analysis for modeling flow in infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    8. Maddah, Negin & Heydari, Babak, 2024. "Building back better: Modeling decentralized recovery in sociotechnical systems using strategic network dynamics," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    9. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    10. Sun, Qin & Li, Hongxu & Zhong, Yuanfu & Ren, Kezhou & Zhang, Yingchao, 2024. "Deep reinforcement learning-based resilience enhancement strategy of unmanned weapon system-of-systems under inevitable interferences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    11. Jia, Rui & Du, Kun & Song, Zhigang & Xu, Wei & Zheng, Feifei, 2024. "Scenario reduction-based simulation method for efficient serviceability assessment of earthquake-damaged water distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    12. Hirofumi Michimae & Takeshi Emura, 2022. "Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
    13. Jiang, Fengyuan & Dong, Sheng, 2024. "Probabilistic-based burst failure mechanism analysis and risk assessment of pipelines with random non-uniform corrosion defects, considering the interacting effects," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    14. Liu, Yushan & Li, Luyi & Chang, Zeming, 2023. "Efficient Bayesian model updating for dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    15. Mühlhofer, Evelyn & Koks, Elco E. & Kropf, Chahan M. & Sansavini, Giovanni & Bresch, David N., 2023. "A generalized natural hazard risk modelling framework for infrastructure failure cascades," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    16. Baibhaw Kumar & Gábor Szepesi & Zsolt Čonka & Michal Kolcun & Zsolt Péter & László Berényi & Zoltán Szamosi, 2021. "Trendline Assessment of Solar Energy Potential in Hungary and Current Scenario of Renewable Energy in the Visegrád Countries for Future Sustainability," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    17. Zhong, Yuanfu & Li, Hongxu & Sun, Qin & Huang, Zhiwen & Zhang, Yingchao, 2024. "A kill chain optimization method for improving the resilience of unmanned combat system-of-systems," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    18. Hughes, William & Watson, Peter L. & Cerrai, Diego & Zhang, Xinxuan & Bagtzoglou, Amvrossios & Zhang, Wei & Anagnostou, Emmanouil, 2024. "Assessing grid hardening strategies to improve power system performance during storms using a hybrid mechanistic-machine learning outage prediction model," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    19. Sonal, & Ghosh, Debomita, 2022. "Impact of situational awareness attributes for resilience assessment of active distribution networks using hybrid dynamic Bayesian multi criteria decision-making approach," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Mendoza, Jorge & Bismut, Elizabeth & Straub, Daniel & Köhler, Jochen, 2022. "Optimal life-cycle mitigation of fatigue failure risk for structural systems," Reliability Engineering and System Safety, Elsevier, vol. 222(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:gam:jmathe:v:11:y:2023:i:13:p:2843-:d:1178553. 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: 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.