IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v231y2017i5p573-586.html
   My bibliography  Save this article

Extending first-passage method to reliability sensitivity analysis of motion mechanisms

Author

Listed:
  • Wenxuan Wang
  • Hangshan Gao
  • Pengfei Wei
  • Changcong Zhou

Abstract

Identifying the parameters that substantially affect the time-dependent reliability is critical for reliability-based design of motion mechanism. The time-dependent local reliability sensitivity and global reliability sensitivity are the two effective techniques for this type of analysis. This work extends the first-passage method and PHI2 method, which are commonly used for estimating the time-dependent reliability, for efficiently estimating the time-dependent local reliability sensitivity and global reliability sensitivity indices of the motion mechanism. Both the local reliability sensitivity and global reliability sensitivity indices are analytically derived based on the Poisson assumption–based first-passage method and the first-order Taylor’s expansion of the motion error function. Compared with the current envelope function method for estimating the time-dependent local reliability sensitivity and global reliability sensitivity indices, the developed method does not need to estimate the second-order derivatives of motion error function, thus is more applicable. The accuracy and effectiveness of the proposed method are demonstrated by a numerical example and a satellite antenna, the direction of which is controlled by a four-bar function generator mechanism.

Suggested Citation

  • Wenxuan Wang & Hangshan Gao & Pengfei Wei & Changcong Zhou, 2017. "Extending first-passage method to reliability sensitivity analysis of motion mechanisms," Journal of Risk and Reliability, , vol. 231(5), pages 573-586, October.
  • Handle: RePEc:sae:risrel:v:231:y:2017:i:5:p:573-586
    DOI: 10.1177/1748006X17717614
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X17717614
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X17717614?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
    ---><---

    References listed on IDEAS

    as
    1. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    2. Wei, Pengfei & Song, Jingwen & Lu, Zhenzhou & Yue, Zhufeng, 2016. "Time-dependent reliability sensitivity analysis of motion mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 107-120.
    3. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    4. Wang, Zequn & Wang, Pingfeng, 2013. "A new approach for reliability analysis with time-variant performance characteristics," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 70-81.
    5. Liu, Qiao & Homma, Toshimitsu, 2009. "A new computational method of a moment-independent uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1205-1211.
    6. Song, Shufang & Lu, Zhenzhou & Qiao, Hongwei, 2009. "Subset simulation for structural reliability sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 658-665.
    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. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    2. Zio, E. & Pedroni, N., 2012. "Monte Carlo simulation-based sensitivity analysis of the model of a thermal–hydraulic passive system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 90-106.
    3. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2021. "Simultaneous estimation of complementary moment independent and reliability-oriented sensitivity measures," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 721-737.
    4. Wei, Pengfei & Song, Jingwen & Lu, Zhenzhou & Yue, Zhufeng, 2016. "Time-dependent reliability sensitivity analysis of motion mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 107-120.
    5. Pengfei Wei & Chenghu Tang & Yuting Yang, 2019. "Structural reliability and reliability sensitivity analysis of extremely rare failure events by combining sampling and surrogate model methods," Journal of Risk and Reliability, , vol. 233(6), pages 943-957, December.
    6. Pengfei Wei & Jingwen Song & Zhenzhou Lu, 2016. "Global reliability sensitivity analysis of motion mechanisms," Journal of Risk and Reliability, , vol. 230(3), pages 265-277, June.
    7. Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.
    8. Derennes, Pierre & Morio, Jérôme & Simatos, Florian, 2019. "A nonparametric importance sampling estimator for moment independent importance measures," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 3-16.
    9. Wei, Pengfei & Lu, Zhenzhou & Yuan, Xiukai, 2013. "Monte Carlo simulation for moment-independent sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 60-67.
    10. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "Global sensitivity analysis in high dimensions with PLS-PCE," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    11. Marrel, Amandine & Chabridon, Vincent, 2021. "Statistical developments for target and conditional sensitivity analysis: Application on safety studies for nuclear reactor," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    12. Zdeněk Kala, 2024. "Global Sensitivity Analysis of Structural Reliability Using Cliff Delta," Mathematics, MDPI, vol. 12(13), pages 1-18, July.
    13. Ma, Yuan-Zhuo & Jin, Xiang-Xiang & Zhao, Xiang & Li, Hong-Shuang & Zhao, Zhen-Zhou & Xu, Chang, 2024. "Reliability-oriented global sensitivity analysis using subset simulation and space partition," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    14. Zhang, Kaichao & Lu, Zhenzhou & Cheng, Kai & Wang, Laijun & Guo, Yanling, 2020. "Global sensitivity analysis for multivariate output model and dynamic models," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    15. Sinan Xiao & Zhenzhou Lu & Pan Wang, 2018. "Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2703-2721, December.
    16. Wei, Pengfei & Liu, Fuchao & Tang, Chenghu, 2018. "Reliability and reliability-based importance analysis of structural systems using multiple response Gaussian process model," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 183-195.
    17. Chakraborty, Souvik & Chowdhury, Rajib, 2017. "A hybrid approach for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 50-57.
    18. Peng, Yongbo & Ma, Yangying & Huang, Tianchen & De Domenico, Dario, 2021. "Reliability-based design optimization of adaptive sliding base isolation system for improving seismic performance of structures," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    19. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "A framework for global reliability sensitivity analysis in the presence of multi-uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    20. Li, Luyi & Lu, Zhenzhou & Wu, Danqing, 2016. "A new kind of sensitivity index for multivariate output," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 123-131.

    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:sae:risrel:v:231:y:2017:i:5:p:573-586. 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: SAGE Publications (email available below). General contact details of provider: .

    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.