Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
289016 | Journal of Sound and Vibration | 2011 | 19 Pages |
In recognition of the obvious limitations of most global vibration-based and local guided-wave-based damage detection techniques, a novel inverse identification approach was developed by canvassing the local perturbance to equilibrium characteristics of the structural component under inspection. Characterized by high-order spatial derivatives, this approach has in particular proven sensitivity to structural damage. Most importantly, it requires neither benchmark structures nor baseline signals; neither global models nor additional excitation sources as long as the structure undergoes steady vibration under its normal operation. Independent of a global model, prior knowledge on structural boundary conditions is not compulsory. To minimize unavoidable influence of measurement noise on high-order spatial derivatives, various de-noising treatments, including wavenumber filtering, optimal selection of measurement configuration and hybrid information fusion were introduced independently. Using a simple beam as a representative structural component for illustration, relationships among vibration frequency, density of measurement points and size of detectable damage were explored, facilitating a judicious selection of measurement parameters. Proof-of-concept validation was numerically conducted, and then experimentally demonstrated using a scanning laser vibrometer. In principle, this proposed methodology is applicable to a complex system comprising various structural components, provided that the local equilibrium relationships of the components are known a priori.
► A novel damage detection approach with advantages over conventional approaches. ► High sensitivity to damage of tiny dimension due to high-order spatial derivatives. ► Independence of benchmark signals, global models, excitation, boundary conditions. ► Potential for damage detection in complex system comprising various components.