주파수응답기반 인공신경망을 이용한 항만케이슨 지반-구조 경계부의 손상식별
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Title
- 주파수응답기반 인공신경망을 이용한 항만케이슨 지반-구조 경계부의 손상식별
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Alternative Title
- Damage Identification for Foundation-Structure Interface of Harbor Caisson using Frequency Response-based ANN
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Author(s)
- 이소영; 홍동수; 김정태; 한상훈
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Alternative Author(s)
- 한상훈
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Publication Year
- 2012-06-01
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Abstract
- In this paper, damage identification for foundation-structure interface of harbor caisson structure using frequency response-basedartificial neural network (ANN) is presented. To achieve the objective, the following approaches are implemented. Firstly, frequency-response-basedANN model is designed. Power spectral densities (PSDs) are employed as the input parameter. Secondly, caisson-structure FE model isconstructed to evaluate the performance of ANN-based damage identification procedure, numerically. Thirdly, training scenarios are designedand changes of frequency domain responses are analyzed. Finally, neural networks are trained for the training scenario andfoundation-structure damage of harbor caisson is identified.lemented. Firstly, frequency-response-basedANN model is designed. Power spectral densities (PSDs) are employed as the input parameter. Secondly, caisson-structure FE model isconstructed to evaluate the performance of ANN-based damage identification procedure, numerically. Thirdly, training scenarios are designedand changes of frequency domain responses are analyzed. Finally, neural networks are trained for the training scenario andfoundation-structure damage of harbor caisson is identified.
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/27692
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Bibliographic Citation
- 한국해양과학기술협의회 공동학술대회, pp.1799 - 1802, 2012
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Publisher
- 한국해양과학기술협의회
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Type
- Conference
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Language
- Korean
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