Improved C-scan imaging using a Bayesian approach

Conventional ultrasonic C-scan imaging in composite materials typically employs peak amplitude extraction where the obtained image quality is extremely dependent on the gate setup on the ultrasonic acquisition hardware. Additionally structural noise created by scattering phenomenon is often high enough to bury meaningful reflection echoes, due to the non-homogeneous nature of such materials. This paper investigates the use of Bayesian inference as a method to construct C-scan images of composite material. The approach was implemented using experimental pulse-echo data, obtained by single-sided inspection of carbon fibre reinforced composite plates containing impact damages. The results were compared to through-transmission measurements and show that the defect image contrast can be improved by using the Bayes' method.