Abstract
Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Objective functions related to natural frequencies, mode shapes, modal flexibility and modal strain energy have been used, and their performances have been analyzed in varying noise conditions. Three beams were analyzed: two of which were simulated beams with single and multiple damage scenarios and one was an experimental beam. In order to do this, SAP 2000 (v14, Computers and Structures Inc., Berkeley, CA, United States, 2009) is linked with MATLAB (r2015, The MathWorks, Inc., Natick, MA, United States, 2015). The genetic algorithm (GA), an evolutionary algorithm (EA), was used to update the damaged structure for damage detection. Due to the degradation of the performance of objective functions in varying noisy conditions, a modified objective function based on the concept of regularization has been proposed, which can be effectively used in combination with EA. All three beams were used to validate the proposed procedure. It has been found that the modified objective function gives better results even in noisy and actual experimental conditions.
Highlights
Structural identification of constructed systems typically requires the integration of structural conceptualization, finite element (FE) modeling, experimental execution, data processing, model calibration, simulation, interpretation and decisions [1]
Three different objective functions based on frequencies, modal assurance criteria (MAC), modal strain
Three different objective functions based on frequencies, MAC, modal strain energy and flexibility have been analyzed for damage detection
Summary
Function I based on frequencies and MAC has worked better in damage detection than Objective Functions II and III in noisy conditions. Probable reasons for the better performance of Objective Function I as compared to the other two were discussed. A regularization function was added in the objective functions based on the a priori modeling of the structure. The results show that the regularization function performed well even in noisy conditions for Objective Function I. The multiple damage scenario has been simulated in Case 2 where three elements were damaged. The regularization function has performed well for Objective. It was found that detections in non-damaged elements were of greater magnitude for Objective Functions II and III as compared to Objective Function I. Iwith regularization, which further proves the performance of the proposed approach in actual experimental conditions.
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