주파수응답기반 인공신경망을 이용한 항만케이슨 지반-구조 경계부의 손상식별

Title
주파수응답기반 인공신경망을 이용한 항만케이슨 지반-구조 경계부의 손상식별
Alternative Title
Damage Identification for Foundation-Structure Interface of Harbor Caisson using Frequency Response-based ANN
Author(s)
이소영; 홍동수; 김정태; 한상훈
Publication Year
2012-06-01
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.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/27692
Bibliographic Citation
한국해양과학기술협의회 공동학술대회, pp.1799 - 1802, 2012
Publisher
한국해양과학기술협의회
Type
Conference
Language
Korean
Publisher
한국해양과학기술협의회
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