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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Structural Engineering and Mechanics, An Int'l Journal Structural Engineering and Mechanics, An Int'l Journal Vol.70 No.4
- 발행연도
- 2019.1
- 수록면
- 457 - 466 (10page)
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초록· 키워드
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This study develops a damage detection method based on neural networks. The performance of the method is numerically and experimentally verified using a three-story shear building model. The framework is mainly composed of two hierarchical stages to identify damage location and extent using artificial neural network (ANN). The normalized damage signature index, that is a normalized ratio of the changes in the natural frequency and mode shape caused by the damage, is used to identify the damage location. The modal parameters extracted from the numerically developed structure for multiple damage scenarios are used to train the ANN. The positive alarm from the first stage of damage detection activates the second stage of ANN to assess the damage extent. The difference in mode shape vectors between the intact and damaged structures is used to determine the extent of the related damage. The entire procedure is verified using laboratory experiments. The damage is artificially modeled by replacing the column element with a narrow section, and a stochastic subspace identification method is used to identify the modal parameters. The results verify that the proposed method can accurately detect the damage location and extent.
목차
등록된 정보가 없습니다.
참고문헌 (45)
참고문헌 신청
Jaouher Ben Ali / 2015 / Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals / Applied Acoustics 89:16~27
Allemang, R. J. / 2003 / The modal assurance criterion-twenty years of use and abuse / Sound Vib 37(8):14~23
Norhisham Bakhary / 2016 / Structure Damage Detection Using Neural Network with Multi-Stage Substructuring / Advances in Structural Engineering 13(1):95~110
Young-Jin Cha / 2017 / Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks / Computer-Aided Civil and Infrastructure Engineering 32(5):361~378
장민우 / 2018 / SMIT를 활용한 지진하중을 받는 전단 구조물의 응답모드 특성에 관한 연구 / 한국지진공학회논문집 22(3):201~210
Allemang, R. J. / 2003 / The modal assurance criterion-twenty years of use and abuse / Sound Vib 37(8):14~23
Norhisham Bakhary / 2016 / Structure Damage Detection Using Neural Network with Multi-Stage Substructuring / Advances in Structural Engineering 13(1):95~110
Young-Jin Cha / 2017 / Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks / Computer-Aided Civil and Infrastructure Engineering 32(5):361~378
장민우 / 2018 / SMIT를 활용한 지진하중을 받는 전단 구조물의 응답모드 특성에 관한 연구 / 한국지진공학회논문집 22(3):201~210
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