IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v188y2019icp221-232.html
   My bibliography  Save this article

Fatigue life reliability evaluation in a high-speed train bogie frame using accelerated life and numerical test

Author

Listed:
  • Lu, Yaohui
  • Zheng, Heyan
  • Zeng, Jing
  • Chen, Tianli
  • Wu, Pingbo

Abstract

Durability fatigue tests for full-scale structures are essential to ensure the fatigue reliability and operational safety of high-speed trains. An accelerated life test (ALT) method is first used to predict the fatigue life of a full-scale bogie frame. Three step-up acceleration load spectrum is compiled for an ALT on the basis of the failure mechanism consistency principle. The ALT of a full-scale bogie frame is conducted. Then, the acceleration coefficient and cycle times from the accelerated load level to the working load level are calculated. Based on the equal damage principle, combined with the finite element calculation, the fatigue life of the bogie frame under acceleration load spectrum is extrapolated. The ALT method is used to compile the acceleration load spectrum and to perform fatigue tests to analyze the acceleration coefficients and predict the fatigue life for a full-scale bogie frame, which provides a reference for the reliability evaluation of large structures.

Suggested Citation

  • Lu, Yaohui & Zheng, Heyan & Zeng, Jing & Chen, Tianli & Wu, Pingbo, 2019. "Fatigue life reliability evaluation in a high-speed train bogie frame using accelerated life and numerical test," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 221-232.
    • Handle: RePEc:eee:reensy:v:188:y:2019:i:c:p:221-232
    DOI: 10.1016/j.ress.2019.03.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018312742
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2019.03.033?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. Liu, Yongming & Liu, Liming & Stratman, Brant & Mahadevan, Sankaran, 2008. "Multiaxial fatigue reliability analysis of railroad wheels," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 456-467.
    2. Qian, C. & Fan, X.J. & Fan, J.J. & Yuan, C.A. & Zhang, G.Q., 2016. "An accelerated test method of luminous flux depreciation for LED luminaires and lamps," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 84-92.
    3. 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.
    4. Wang, Huan & Wang, Guan-jun & Duan, Feng-jun, 2016. "Planning of step-stress accelerated degradation test based on the inverse Gaussian process," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 97-105.
    5. Li, Xiaoyang & Chen, Wenbin & Sun, Fuqiang & Liao, Haitao & Kang, Rui & Li, Renqing, 2018. "Bayesian accelerated acceptance sampling plans for a lognormal lifetime distribution under Type-I censoring," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 78-86.
    6. Do, Duy Minh & Gao, Wei & Song, Chongmin & Tangaramvong, Sawekchai, 2014. "Dynamic analysis and reliability assessment of structures with uncertain-but-bounded parameters under stochastic process excitations," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 46-59.
    7. Nasir, Ehab A. & Pan, Rong, 2015. "Simulation-based Bayesian optimal ALT designs for model discrimination," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 1-9.
    8. Bedbur, S. & Kamps, U., 2019. "Confidence regions in step–stress experiments with multiple samples under repeated type-II censoring," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 181-186.
    9. Yin, Yi-Chao & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "An imprecise statistical method for accelerated life testing using the power-Weibull model," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 158-167.
    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. Peña-Ramírez, Fernando A. & Guerra, Renata Rojas & Canterle, Diego Ramos & Cordeiro, Gauss M., 2020. "The logistic Nadarajah–Haghighi distribution and its associated regression model for reliability applications," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    2. Lin, Shuai & Jia, Limin & Zhang, Hengrun & Zhang, Pengzhu, 2022. "Reliability of high-speed electric multiple units in terms of the expanded multi-state flow network," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    3. Shan Jiang & Yan-Fu Li, 2020. "Time-variant fatigue reliability evaluation of riveted lap joint under stationary random loading," Journal of Risk and Reliability, , vol. 234(4), pages 567-578, August.
    4. Shuai Lin & Limin Jia & Hengrun Zhang & Yanhui Wang, 2021. "A method for assessing resilience of high-speed EMUs considering a network-based system topology and performance data," Journal of Risk and Reliability, , vol. 235(5), pages 877-895, October.
    5. Woo, Seong-woo & Pecht, Michael & O'Neal, Dennis L., 2020. "Reliability design and case study of the domestic compressor subjected to repetitive internal stresses," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Cheng, Yao & Liao, Haitao & Huang, Zhiyi, 2021. "Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    7. Xia, Weifu & Wang, Yanhui & Hao, Yucheng & He, Zhichao & Yan, Kai & Zhao, Fan, 2024. "Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    8. Zhang, Chunfang & Wang, Liang & Bai, Xuchao & Huang, Jianan, 2022. "Bayesian reliability analysis for copula based step-stress partially accelerated dependent competing risks model," Reliability Engineering and System Safety, Elsevier, vol. 227(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. Cheng, Yao & Liao, Haitao & Huang, Zhiyi, 2021. "Optimal degradation-based hybrid double-stage acceptance sampling plan for a heterogeneous product," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    2. Sun, Bo & Fan, Xuejun & van Driel, Willem & Cui, Chengqiang & Zhang, Guoqi, 2018. "A stochastic process based reliability prediction method for LED driver," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 140-146.
    3. Abdullah AH Ahmadini & Frank PA Coolen, 2020. "Statistical inference for the Arrhenius-Weibull accelerated life testing model with imprecision based on the likelihood ratio test," Journal of Risk and Reliability, , vol. 234(2), pages 275-289, April.
    4. Starling, James K. & Mastrangelo, Christina & Choe, Youngjun, 2021. "Improving Weibull distribution estimation for generalized Type I censored data using modified SMOTE," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Wang, Xiaofei & Wang, Bing Xing & Jiang, Pei Hua & Hong, Yili, 2020. "Accurate reliability inference based on Wiener process with random effects for degradation data," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Mohammad Ali Farsi & S. Masood Hosseini, 2019. "Statistical distributions comparison for remaining useful life prediction of components via ANN," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 429-436, June.
    8. Rong Yuan & Debiao Meng & Haiqing Li, 2016. "Multidisciplinary reliability design optimization using an enhanced saddlepoint approximation in the framework of sequential optimization and reliability analysis," Journal of Risk and Reliability, , vol. 230(6), pages 570-578, December.
    9. 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.
    10. Zhang, Wei & Li, Xiang & Ma, Hui & Luo, Zhong & Li, Xu, 2021. "Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    11. Ikuzwe, Alice & Ye, Xianming & Xia, Xiaohua, 2020. "Energy-maintenance optimization for retrofitted lighting system incorporating luminous flux degradation to enhance visual comfort," Applied Energy, Elsevier, vol. 261(C).
    12. Cai, Xia & Tian, Yubin & Ning, Wei, 2019. "Change-point analysis of the failure mechanisms based on accelerated life tests," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 515-522.
    13. Bi Liu & Yunlong Teng & Qi Huang, 2020. "RETRACTED: A novel imprecise reliability prediction method for incomplete lifetime data based on two-parameter Weibull distribution," Journal of Risk and Reliability, , vol. 234(1), pages 208-218, February.
    14. Ma, Zhonghai & Liao, Haitao & Ji, Hui & Wang, Shaoping & Yin, Fanglong & Nie, Songlin, 2021. "Optimal design of hybrid accelerated test based on the Inverse Gaussian process model," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    15. Insua, David Rios & Ruggeri, Fabrizio & Soyer, Refik & Wilson, Simon, 2020. "Advances in Bayesian decision making in reliability," European Journal of Operational Research, Elsevier, vol. 282(1), pages 1-18.
    16. Peihua Jiang, 2022. "Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    17. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    18. Chen, Gaige & Chen, Jinglong & Zi, Yanyang & Miao, Huihui, 2017. "Hyper-parameter optimization based nonlinear multistate deterioration modeling for deterioration level assessment and remaining useful life prognostics," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 517-526.
    19. Ahmed Zohair Djeddi & Ahmed Hafaifa & Abdellah Kouzou & Salam Abudura, 2017. "Exploration of reliability algorithms using modified Weibull distribution: application on gas turbine," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1885-1894, November.
    20. Yan, Weian & Xu, Xiaofan & Bigaud, David & Cao, Wenqin, 2023. "Optimal design of step-stress accelerated degradation tests based on the Tweedie exponential dispersion process," Reliability Engineering and System Safety, Elsevier, vol. 230(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:eee:reensy:v:188:y:2019:i:c:p:221-232. 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.