Techno Press

Smart Structures and Systems   Volume 5, Number 1, January 2009, pages 1-21
A two-stage damage detection approach based on subset selection and genetic algorithms
Gun Jin Yun, Kenneth A. Ogorzalek, Shirley J. Dyke and Wei Song

Abstract     [Full Text]
    A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.
Key Words
    damage detection; structural health monitoring; genetic algorithms; subset selection and model updating.
Gun Jin Yun; Department of Civil Engineering, University of Akron, Akron, OH, USA
Kenneth A. Ogorzalek; Department of Civil Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
Shirley J. Dyke and Wei Song; Department of Mechanical, Aerospace and Structural Engineering, Washington University in St. Louis, St. Louis, MO, USA

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