Ultrasound material backscattered noise analysis by a duo wavelet-regression analysis

Fairouz Bettayeb

Internal material defects detection by ultrasound non destructive testing is widely used in industry, ultrasonic data are obtained from traveling waves inside the matter and captured by piezoelectric sensors. The natural inhomogeneous and anisotropy character of steel made material causes high acoustic attenuation and scattering effect. This adds complexity to data analysis. In this research we address the non linear features of back scattered ultrasonic waves from steel plates and welds.Indeed structural noise data files captured from specimens, and processed by a wavelet energy filtering approach, show significant insights into the relationship between backscattered noise and material microstructures. This algorithm along with correlation coefficients, residuals and interpolations calculations of processed ultrasonic data seems to be a well-adapted signal analysis tool for viewing material micro structural dimension scales. Experiments show a challenging 3D interface between material properties, calculations and ultrasonic wave propagation modeling. As well as they indicate a quasi linear signal energy distribution at micro structural levels. It suggests probable incidence of microstructure acoustic signatures at different energy scales of the material phases. Multi polynomial interpolations of the processed noise data exhibit an attractor shape which should involves chaos theory noise data modeling.

Mots clés: Ultrasonic characterization; wavelet analysis; regression analysis; NDT/NDE

Domaines: Acoustique [physics.class-ph]

Fairouz Bettayeb. Ultrasound material backscattered noise analysis by a duo wavelet-regression analysis. Acoustics 2012, Apr 2012, Nantes, France. ⟨hal-00810631⟩