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• W2728758610 abstract "A novel clustering stabilization diagram combined with self adaptive differential evolution algorithm is proposed to identify the modal parameters of civil engineering structures. Compared with the traditional stabilization diagram, the clustering diagram has drawn more attention because it can distinguish physical and spurious modes due to its automatic performance. In this paper, a self adaptive differential evolution algorithm is proposed to optimize the initial clustering centers so as to improve the clustering stabilization diagram. Moreover, this paper presents a new idea that the modal assurance criterion (MAC) composed of mode shapes is selected as the <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML><mml:mi>Y</mml:mi></mml:math>-axis to replace the model orders or damping ratios in existing stabilization diagrams. The results of a benchmark test of bridge Z24 and the numerical simulation of a continuous beam and a cable-stayed bridge demonstrate the advantages of the proposed approaches and the reliability of detecting the modal parameters." @default.
• W2728758610 created "2017-07-14" @default.
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• W2728758610 date "2017-06-30" @default.
• W2728758610 modified "2023-09-25" @default.
• W2728758610 title "Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification" @default.
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• W2728758610 doi "https://doi.org/10.21595/jve.2017.17629" @default.
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