Damage imaging in plates by evaluating local entropy in guided wavefield data

Abstract

This paper presents a new algorithm called broadband entropy-based two-stage damage imaging (BE2DI) for the detection and imaging of defects in multi-layer plates.The method differentiates defects from either local scattering phenomena of propagating Lamb waves or locally increased vibrational activity for stimulated global plate resonances by exploiting the higher vibrational activity of full-field broadband vibration signals at defective regions and the distinct spatial behavior of defects and artifacts. Using these features, first, a candidate damage map is constructed by means of iterative thresholding based on descriptive statistics of broadband data. Afterwards, an adaptive regional damage index based on local entropy is introduced, which utilizes operational deflection shapes to process previously identified candidate regions and subsequently reveal both shallow and deep defects. BE2DI can be seen as an automated local defect resonance identification approach in the case of shallow defects. Multiple plates having various defect types with different sizes and depths are investigated. Broadband chirp signals are used to excite the plates using low-power piezoelectric actuators, and vibrational data is registered by 3D scanning laser Doppler vibrometry. The obtained results quantitatively and qualitatively demonstrate that the proposed method can effectively detect different kinds of damage, regardless of being shallow or deep.