Structural Joint Damage Assessment Using Neural Networks

신경망을 이용한 구조물 접합부의 손상도 추정

  • 방은영 (Univ. of California, Irvine, 박사후연구원과정) ;
  • 이진학 (한국과학기술원 토목공학과) ;
  • 윤정방 (한국과학기술원 토목공학과)
  • Published : 1998.03.01

Abstract

Structural damage is used to be modeled through reductions in the stiffness of structural elements for the purpose of damage estimation of structural system. In this study, the concept of joint damage is employed for more realistic damage assessment of a steel structure. The joint damage is estimated damage based on the mode shape informations using neural networks, The beam-to-column connection in a steel frame structure is represented by a rotational spring at the fixed end of a beam element. The severity of joint damage is defined as the reduction ratio of the connection stiffness with respect to the value of the intact joint. The concept of the substructural identification is used for the localized damage assessment in a large structure. The feasibility of the proposed method is examined using an example with simulated data. It has been found that the joint damages can be reasonably estimated for the case with the measurements of the mode vectors subjected to noise.

Keywords

system identification;joint damage assessment;neural networks;substructural method

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