• Title/Summary/Keyword: 열응답 실험

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Estimation of Dynamic Vertical Displacement using Artificial Neural Network and Axial strain in Girder Bridge (인공신경망과 축방향 변형률을 이용한 거더 교량의 동적 수직 변위 추정)

  • Ok, Su Yeol;Moon, Hyun Su;Chun, Pang-Jo;Lim, Yun Mook
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.6
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    • pp.1655-1665
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    • 2014
  • Dynamic displacements of structures shows general behavior of structures. Generally, It is used to estimate structure condition and trustworthy physical quantity directly. Especially, measuring vertical displacement which is affected by moving load is very important part to find or identify a problem of bridge in advance. However directly measuring vertical displacement of the bridge is difficult because of test conditions and restriction of measuring equipment. In this study, Artificial Neural Network (ANN) is used to suggest estimation method of bridge displacement to overcome constrain conditions, restriction and so on. Horizontal strain and vertical displacement which are measured by appling random moving load on the bridge are applied for learning and verification of ANN. Measured horizontal strain is used to learn ANN to estimate vertical displacement of the bridge. Numerical analysis is used to acquire learning data for axis strain and vertical displacement for applying ANN. Moving load scenario which is made by vehicle type and vehicle distance time using Pearson Type III distribution is applied to analysis modeling to reflect real traffic situation. Estimated vertical displacement in respect of horizontal strain according to learning result using ANN is compared with vertical displacement of experiment and it presents vertical displacement of experiment well.