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Uncertainty analysis of motion error for mechanisms and Kriging-based solutions

Author

Listed:
  • Zhou Changcong
  • Ji Mengyao
  • Zhao Haodong
  • Cao Fei

Abstract

In this work, the issue of uncertainty analysis of motion errors for mechanisms is studied. First, two definitions of motion errors, that is, maximum error and accumulative error, are introduced to measure the motion accuracy in a comprehensive way. Then, the method for performing an uncertainty analysis of the two errors is discussed. For the maximum error, an analysis of the failure probability and the corresponding sensitivity analysis are carried out. For the accumulative error, the variance-based sensitivity is studied to quantify the contributions of input variables to the mechanism performance. A Kriging-based method is proposed to reduce the computational cost of the uncertainty analysis of motion errors. Finally, four examples including the classical four-bar mechanism and the landing gear mechanism for aeronautical purposes are studied with the proposed method. Discussions on the results show that the uncertainty analysis of motion errors can provide helpful information for mechanisms.

Suggested Citation

  • Zhou Changcong & Ji Mengyao & Zhao Haodong & Cao Fei, 2021. "Uncertainty analysis of motion error for mechanisms and Kriging-based solutions," Journal of Risk and Reliability, , vol. 235(5), pages 731-743, October.
  • Handle: RePEc:sae:risrel:v:235:y:2021:i:5:p:731-743
    DOI: 10.1177/1748006X21999019
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    References listed on IDEAS

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    1. Mara, Thierry A. & Tarantola, Stefano, 2012. "Variance-based sensitivity indices for models with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 115-121.
    2. Borgonovo, E., 2007. "A new uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 771-784.
    3. Emanuele Borgonovo & Gordon B. Hazen & Elmar Plischke, 2016. "A Common Rationale for Global Sensitivity Measures and Their Estimation," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1871-1895, October.
    4. Wu, Jianing & Yan, Shaoze & Zuo, Ming J., 2016. "Evaluating the reliability of multi-body mechanisms: A method considering the uncertainties of dynamic performance," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 96-106.
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