AIP Advances (May 2023)

Research on the damage diagnosis model verification method of cable-stayed bridges

  • Jie Liu,
  • Jiameng Chen,
  • Qingkuan Liu,
  • Hailong Wang,
  • Jianqing Bu

DOI
https://doi.org/10.1063/5.0151067
Journal volume & issue
Vol. 13, no. 5
pp. 055216 – 055216-8

Abstract

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To solve the problem that the damage diagnosis model of cable-stayed bridges cannot quantitatively evaluate its validity, the verification method of the diagnosis model is investigated. A model validation method [Root-Mean-Square Error (RMSE)-Statistical Hypothesis Test (SHT), R–S] that combines the RMSE evaluation index and the SHT is proposed and applied to the reliability evaluation of the cable-stayed bridge data mining damage diagnosis model. First, the R–S method evaluates the diagnostic effect of the model via the evaluation index. Second, the SHT method is used to quantitatively compare the consistency between the output data of the diagnostic model and the actual structure output data. Finally, the validity of the model is quantitatively evaluated. The application process of the proposed method is demonstrated by an example. The results show that the diagnostic model has strong reliability and that the confidence level Pδ exceeds 90%, which indicates the effectiveness of the diagnostic model verification method.