Abstract

The frequency-shift-based scheme is one of the popular structural damage detectionmethods used in the field. Assuming that the damage will cause structural parameter(e.g. mass or stiffness) changes, one can detect damage by observing natural frequencyvariations before and after damage occurs. One of the major limitations of thefrequency-shift-based damage detection approach is that the natural frequencies could beinsensitive to local and small parameter variations (damages) in the structure. To addressthis problem, the concept of sensitivity-enhancing control has been developed andexplored by researchers. Recently, an eigenstructure (dual eigenvalue–eigenvector)assignment-based approach has been proposed to advance the state of the artof sensitivity-enhancing control design for multiple degrees-of-freedom systems(Jiang et al 2007 Trans. ASME, J. Vib. Acoust. 129 771–83). While promisingfeatures have been shown, the approach has not been experimentally verified. Inaddition, such a scheme requires an accurate analytical model, which is in generaldifficult to obtain for complex structures. The purpose of this research is to advancethe state of the art by exploring an experimental-based sensitivity-enhancingcontrol approach for structural damage detection. That is, we aim at utilizingmathematical models identified from experimental measurement data for controllerdesign and system analysis, and hence eliminate the requirement of an accurateanalytical model. With the identified model, an eigenstructure assignment-basedoptimization scheme is utilized to design the closed-loop control to best enhance thenatural frequency sensitivity to structural damages. An experimental investigationbased on a test bed beam structure is conducted to demonstrate and verify theproposed method. Sensitivity-enhancing controls are designed to increase thefirst two natural frequency sensitivities to mass changes in the beam structure.Experimental results show that by applying the designed sensitivity-enhancing controls tothe beam structure, the natural frequency sensitivities to mass variations canbe significantly enhanced. Results also show that the damage locations can besuccessfully identified and the damage severity can be predicted by using the measuredfrequency changes of the closed-loop systems before and after damage occurrence.

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