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논문 기본 정보

자료유형
학술저널
저자정보
Yi Zhang (Tsinghua University) Chul-Woo Kim (Kyoto University) Lian Zhang (Kyoto University) Yongtao Bai (Chongqing University) Hao Yang (Leibniz University Hanover) Xiangyang Xu (Leibniz University Hanover) Zhenhao Zhang (Changsha University of Science and Technology)
저널정보
국제구조공학회 Smart Structures and Systems, An International Journal Smart Structures and Systems, An International Journal Vol.25 No.3
발행연도
2020.1
수록면
285 - 299 (15page)

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초록· 키워드

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Long term structural health monitoring has gained wide attention among civil engineers in recent years due to the scale and severity of infrastructure deterioration. Establishing effective damage indicators and proposing enhanced monitoring methods are of great interests to the engineering practices. In the case of bridge health monitoring, long term structural vibration measurement has been acknowledged to be quite useful and utilized in the planning of maintenance works. Previous researches are majorly concentrated on linear time series models for the measurement, whereas nonlinear dependences among the measurement are not carefully considered. In this paper, a new bridge health monitoring method is proposed based on the use of long term vibration measurement. A combination of the fundamental ARMA model and copula theory is investigated for the first time in detecting bridge structural damages. The concept is applied to a real engineering practice in Japan. The efficiency and accuracy of the copula based damage indicator is analyzed and compared in different window sizes. The performance of the copula based indicator is discussed based on the damage detection rate between the intact structural condition and the damaged structural condition.

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