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Structural System Identification Using Extended Kalman Filter and Genetic Algorithm

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  • URLhttps://db.koreascholar.com/Article/Detail/334151
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한국구조물진단유지관리공학회 (The Korea Institute For Structural Maintenance and Inspection)
초록

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.

저자
  • 윤다요(연세대학교, 건축공학과, 석박통합과정) | Yun, Da Yo
  • 오병관(연세대학교, 건축공학과, 박사과정) | Oh, Byung Kwan
  • 양수원(연세대학교, 건축공학과, 석사과정) | Yang, Soo Won
  • 이설호(연세대학교, 건축공학과, 석사과정) | Lee, Seol Ho
  • 박효선(연세대학교 건축공학과 교수, 공학박사) | Park, Hyo Seon Corresponding author