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The influence of model and measurement uncertainties on damage detection of experimental structures through recursive algorithms

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  • Ebrahimi, Mehrdad
  • Nobahar, Elnaz
  • Mohammadi, Reza Karami
  • Noroozinejad Farsangi, Ehsan
  • Noori, Mohammad
  • Li, Shaofan

Abstract

In this work, we developed a framework for identifying frame-type structures regarding the measurement uncertainty and the uncertainty involved in inherent and structural parameters. The identification process is illustrated and examined on a one-eight-scale four-story moment-resisting steel frame under seismic excitation using two well-known recursive schemes: the Extended Kalman filter (EKF) and Unscented Kalman Filter (UKF) methods. The nonlinear system equations were assessed by applying a first-order instantaneous linearization approach through the EKF method. In contrast, the UKF algorithm employs several sample points to estimate moments of random variables’ nonlinear transformations. A nonlinear transformation is applied to distribute sample points to derive the precise mean and covariance up to the second order of any nonlinearity. Accordingly, it is theoretically expected that the UKF algorithm is more capable of identifying the nonlinear systems and determining the unknown parameters than the EKF algorithm. The capability of the EKF and UKF algorithms was assessed by considering a 4-story moment-resisting steel frame with several inherent uncertainties, including the material behavior model, boundary conditions, and constraints. In addition to these uncertainties, the combination of acceleration and displacement responses of different structural levels is employed to evaluate the capability of the algorithms. The information entropy measure is used to investigate further the uncertainty of a group of established model parameters. As highlighted, a good agreement is observed between the results using the information entropy measure criterion and those using the UKF and EKF algorithms. The results illustrate that using the responses of fewer levels placed in the proper positions may lead to improved outcomes than those of more improperly positioned levels.

Suggested Citation

  • Ebrahimi, Mehrdad & Nobahar, Elnaz & Mohammadi, Reza Karami & Noroozinejad Farsangi, Ehsan & Noori, Mohammad & Li, Shaofan, 2023. "The influence of model and measurement uncertainties on damage detection of experimental structures through recursive algorithms," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    • Handle: RePEc:eee:reensy:v:239:y:2023:i:c:s0951832023004453
    DOI: 10.1016/j.ress.2023.109531
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    as
    1. Nogal, M. & Nogal, A., 2021. "Sensitivity method for extreme-based engineering problems," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. 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).
    3. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Zhang, Yanping & Cai, Baoping & Liu, Yiliu & Jiang, Qiangqiang & Li, Wenchao & Feng, Qiang & Liu, Yonghong & Liu, Guijie, 2021. "Resilience assessment approach of mechanical structure combining finite element models and dynamic Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Tohme, Tony & Vanslette, Kevin & Youcef-Toumi, Kamal, 2023. "Reliable neural networks for regression uncertainty estimation," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    6. Hao, Peng & Tang, Hao & Wang, Yu & Wu, Tao & Feng, Shaojun & Wang, Bo, 2023. "Stochastic isogeometric buckling analysis of composite shell considering multiple uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Liu, Xintian & Yu, Xueguang & Tong, Jiachi & Wang, Xu & Wang, Xiaolan, 2021. "Mixed uncertainty analysis for dynamic reliability of mechanical structures considering residual strength," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    8. Mi, Jinhua & Lu, Ning & Li, Yan-Feng & Huang, Hong-Zhong & Bai, Libing, 2022. "An evidential network-based hierarchical method for system reliability analysis with common cause failures and mixed uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    9. Xiong, Qingwen & Du, Peng & Deng, Jian & Huang, Daishun & Song, Gongle & Qian, Libo & Wu, Zenghui & Luo, Yuejian, 2022. "Global sensitivity analysis for nuclear reactor LBLOCA with time-dependent outputs," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    10. Bai, Guangxing & Su, Yunsheng & Rahman, Maliha Maisha & Wang, Zequn, 2023. "Prognostics of Lithium-Ion batteries using knowledge-constrained machine learning and Kalman filtering," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    11. Takeda, Satoshi & Kitada, Takanori, 2021. "Simple method based on sensitivity coefficient for stochastic uncertainty analysis in probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    12. Reuven Rubinstein, 1999. "The Cross-Entropy Method for Combinatorial and Continuous Optimization," Methodology and Computing in Applied Probability, Springer, vol. 1(2), pages 127-190, September.
    13. Meng, Zeng & Zhao, Jingyu & Chen, Guohai & Yang, Dixiong, 2022. "Hybrid uncertainty propagation and reliability analysis using direct probability integral method and exponential convex model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    14. Gomes, Wellison José de Santana & Beck, André Teófilo, 2021. "A conservatism index based on structural reliability and model errors," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    15. Cheng, Kai & Lu, Zhenzhou, 2021. "Adaptive Bayesian support vector regression model for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    16. Zheng, Xiao-Wei & Li, Hong-Nan & Gardoni, Paolo, 2023. "Hybrid Bayesian-Copula-based risk assessment for tall buildings subject to wind loads considering various uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    17. Vishwanath, B Sharanbaswa & Banerjee, Swagata, 2023. "Considering uncertainty in corrosion process to estimate life-cycle seismic vulnerability and risk of aging bridge piers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    18. Xu, Min & Ouyang, Min & Hong, Liu & Mao, Zijun & Xu, Xiaolin, 2022. "Resilience-driven repair sequencing decision under uncertainty for critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    Full references (including those not matched with items on IDEAS)

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