Guided wave sensitivity prediction for part and through-thickness crack-like defects

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Abstract

Guided waves allow for the efficient structural health monitoring of large structures using phased or distributed arrays of sensors. The sensitivity for specific defects can be improved by accounting for the angular scattering pattern. The scattering of the fundamental anti-symmetric guided wave mode (A0 Lamb mode) at through-thickness and part-through crack-like defects was studied experimentally and from three-dimensional finite element simulations. Experimentally, the scattered field around manufactured notches of different depths and lengths in an aluminium plate was measured using a laser interferometer. The scattered field was extracted by taking the complex difference in the frequency domain between baseline measurement and measurements around the defect. Good agreement was found between measurements and three-dimensional finite element simulations, and the amplitude and directionality pattern of the scattered field can be predicted accurately. The angular directionality pattern of the scattered field depending on the direction of the incident wave relative to the crack-like defect orientation, depth and length relative to the wavelength was investigated. For short and part-thickness defects, the main scattering effect is a reduction of the (forward) wave propagating past the defect with very limited backscattered amplitude. Significant energy scattered back towards the incident wave direction was only found for perpendicular incidence on long and deep defects. Even for large defects, almost no energy is scattered in certain directions from the defect, possibly complicating defect detection. Based on the predicted amplitude and angular dependency of the scattered guided waves, the sensitivity for defect detection using localized and distributed structural health monitoring sensor array systems can be quantified.

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APA

Fromme, P. (2020). Guided wave sensitivity prediction for part and through-thickness crack-like defects. Structural Health Monitoring, 19(3), 953–963. https://doi.org/10.1177/1475921719892205

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