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Regularization Method by Subset Selection for Structural Damage Detection  

Yun, Gun-Jin (Washington University 기계항공구조공학과)
Han, Bong-Koo (서울산업대학교 건설공학부)
Publication Information
Journal of the Computational Structural Engineering Institute of Korea / v.21, no.1, 2008 , pp. 73-82 More about this Journal
Abstract
In this paper, a new regularization method by parameter subset selection method is proposed based on the residual force vector for damage localization. Although subset selection using the fundamental modal characteristics as a residual function has been successful in detecting a single damage location, this method seems to have limited capabilities in the detection of multiple damage locations and typically requires cumbersome weighting values. The method is presented herein and considers cases in which damage detection must be achieved using incomplete measurements of the structural responses. Model expansion is incorporated to deal with this challenge. The unique advantage of employing the new regularization method is that it can reliably identify multiple damage locations. Through an illustrative example, the proposed damage detection method is demonstrated to be a reliable tool for identifying multiple damage locations for a planar truss structure.
Keywords
regularization; subset selection; damage detection; structural health monitoring; model updating;
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