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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Smart Structures and Systems, An International Journal Smart Structures and Systems, An International Journal Vol.15 No.3
- 발행연도
- 2015.1
- 수록면
- 751 - 767 (17page)
이용수
초록· 키워드
오류제보하기
A new procedure is proposed for assessing probabilistic condition of structures consideringeffect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified byusing weighting vectors that represent the uncertainty conditions of measured data. The distribution ofstructural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertaintyconditions, and the identified models are classified into groups according to their similarity by using aK-means method. The condition of a structure is then assessed probabilistically using FE models in theclassified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge,a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition ofthe bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. Thenumerical example shows that the proposed method can quantify uncertainty of measured data andsubsequently evaluate efficiently the probabilistic condition of bridges.
목차
등록된 정보가 없습니다.
참고문헌 (25)
참고문헌 신청
Beck, J.L. / 2002 / Bayesian updating of structural models and reliability using Markov chain Monte Carlo simulation / J. Eng. Mech. -ASCE 128(4):380~391
Bishop, C. M. / 2006 / Pattern Recognition And Machine Learning / springer
Ding, C. / 2004 / K-means clustering via principal component analysis / Proceedings of the 21th International Conference on Machine Learning, ACM
Friswell, M. / 1995 / Finite Element Model Updating In Structural Dynamics / Kluwer Academic Publishers
Govers, Y. / 2010 / Stochastic model updating—Covariance matrix adjustment from uncertain experimental modal data / Mech. Syst. Signal Pr 24(3):696~706
Bishop, C. M. / 2006 / Pattern Recognition And Machine Learning / springer
Ding, C. / 2004 / K-means clustering via principal component analysis / Proceedings of the 21th International Conference on Machine Learning, ACM
Friswell, M. / 1995 / Finite Element Model Updating In Structural Dynamics / Kluwer Academic Publishers
Govers, Y. / 2010 / Stochastic model updating—Covariance matrix adjustment from uncertain experimental modal data / Mech. Syst. Signal Pr 24(3):696~706
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