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확장칼만필터와 유전자 알고리즘을 사용하는 구조물 시스템 식별
윤다요 ( Yun Da Yo ),오병관 ( Oh Byung Kwan ),양수원 ( Yang Soo Won ),이설호 ( Lee Seol Ho ),박효선 ( Park Hyo Seon ) 한국구조물진단유지관리공학회 2017 한국구조물진단유지관리공학회 학술발표대회 논문집 Vol.21 No.2
Recently, as the awareness of safety has become more important, studies on damage assessment techniques for building structures have been actively conducted. The damage of the building structure is caused by the decrease of the stiffness which is inherent dynamic characteristic of the structural system, and the decrease of stiffness acts as a direct variable connected to the collapse of the structure. there have been developed techniques for estimating the inherent dynamics of a structure to identify and evaluate damage to the structure. In this study, we estimate the layer mass due to the modeling error through the optimization algorithm, Genetic Algorithm, and use the optimization algorithm GA to optimize the error covariance matrix, system noise and measured noise covariance matrix We propose an optimal state estimation algorithm. The objective function of the GA algorithm is obtained by the residual which is the difference between the measured values obtained from the EKF calculation and the values obtained from the system model. We verified the feasibility of the algorithm through a 4-DOF system.
고층건물의 모달 감쇠비 식별 기법들의 정확도 및 안정성 평가
윤다요(Yun, Da Yo),박효선(Park, Hyo Seon) 대한건축학회 2020 대한건축학회논문집 Vol.36 No.8
Structural health monitoring (SHM) technology has been developed and applied to ensure the safety of building structures. For the safety assessment through SHM, it is necessary to identify the modal parameters of the structure through the structural responses obtained using various sensors. System identification (SI) techniques for identifying modal parameters of building structures have been developed in various ways. Although various SI techniques have been developed, The study comparing the accuracy and stability of estimation results for modal damping ratio from currently representative SI techniques has not been conducted. However, It is important to assess the accuracy and stability of SI techniques, because the exact solution of the modal damping ratio cannot be known. In this study, The accuracy and stability for modal damping ratio of SI techniques have been identified using enhanced frequency domain decomposition (EFDD), stochastic subspace identification covariance-driven (SSI-COV), SSI data-driven (SSI-DATA), and numerical algorithms for subspace state-space system identification (N4SID) methods, which are currently representative SI methods for high-rise buildings in the field. The accuracy and stability of each method were compared and analyzed through the results of the probability density function of the identified modal damping ratio. As a result, there was a difference in accuracy and stability identified in each method. Furthermore, it was confirmed that each methods difference also occurred in the computational time required for analysis.