Li, WM (Li, Wei-ming); Zhu,HP (Zhu, Hong-ping); Ding, LY (Ding, Lie-yun); Luo, HB (Luo, Han-bin)

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http://www.sciencedirect.com/science/article/pii/S0926580511001622

Abstract：Damage alwaysreduces structural stiffness, and changes the dynamic responses. Generally, thechanges are too slight to reveal the damage information directly. Therefore,more explicit and efficient methods are needed to reveal the underlying damageinformation. This study recognizes the damage existence, quantification, andlocation by classifying structural responses data into groups. Firstly, fourdamaged scenarios are designed to be investigated. Secondly, structural responsesand their statistical features are explored for damage recognition. Thirdly,the damage existence is recognized on grouped data based on the accelerationresponses according to the general Principal Component Analysis (PCA) theory.Fourthly, the damage existence, quantification, and location are recognized bygrouped data based on the model data according to the coordinate rotations inPCA. Finally, the damage information is recognized by modal shape data with twodifferent noise levels to show the robustness of the method.

Keywords:Structural vibration; Damage recognition;Grouped data; Statistical method; Principal Component Analysis