This research is focused on the analysis of parameter estimation problem guessing the structural parameters from the measured structural response and system characteristics. Accurate estimation of joint parameters is very important in model updating and diagnosis. Because of the measurement incompleteness and noise, the estimation result is generally inaccurate and highly depends on the experiment condition.
The main results of this research are the presentation of optimal sensor placement criterion for the mechanical parameter identification process, and the proposition of a reliable and non-time consuming sensor placement guide. The optimal criteria are derived to get a minimum covariance in parameter estimation process. By using this criteria, an efficient sensor placement guide can be proposed. Unlike most of the other methods, the method in this research does not rely on computationally exhaustive search technique. This method bases on an iterative scheme similar to other methods, which are originated from orthogonal projection scheme and mainly used in state estimation and control processes. In order to overcome a shortcoming of the previous researchers, this method proposes an idea to delete a bunch of degrees of freedom at each iteration stage to get an optimum sensor configuration safely. According to our simulation and experiment results, reliability and rapidity in degree selection process is highly dependent on the choice of information loss at each iteration step. And an efficient parameter identification scheme by minimizing the modal input force is developed to cope with measurement incompleteness and joint uncertainty. The accuracy of proposed method is also dependent on the measurement positions. However proposed measurement position selection guide make the proposed estimation process be robust one. The validity and feasibility of the proposed method are demonstrated both numerically and experimentally. By using this approach parameter estimation process is performed so that the estimated parameters may have least uncertainty. The FE model is then updated such that it accurately describes the real structure. It can then be used successfully in structural dynamic analysis, such as structural dynamic modification(SDM) and control problem.
구조물내 연결부위의 정확한 특성파악은 구조물의 재설계, 제어, 동적해석 및 이상진단 등에 매우 중요하다. 그러나, 측정 장비의 제한과 측정 시 발생하는 노이즈등으로 인하여 연결부 특성의 파악은 매우 어렵거나 때론 불가능 경우가 대부분이며 실험조건에 상당한 영향을 받는다.
본 연구에서는 일반적인 변수 추정 방법에 있어서 어떠한 인자가 예측치의 신뢰도를 좌우하는 가를 알아보았고, 이를 이용하여 신뢰도를 높이기 위한 실험 설계의 방안으로써, 최적 측정점 선정에 대한 효과적 방안을 제시하였다.
제시된 측정점 선정에 대한 방법을 대형 우주 구조물인 인공위성 태양전지판의 힌지부 특성파악에 적용하여 효율성 및 정확성을 검증하였고, 또한 실험적으로 간단한 T형 빔 구조물의 연결부 특성 파악에 적용하여 매우 정확한 결과를 얻어내었다.
