Structural damage assessment in fiber reinforced composites using image decomposition

Abstract

Image decomposition techniques such as geometric moment descriptors, Fourier descriptors, wavelet descriptors etc. have been used commercially in the fields of biometrics for finger print, iris matching and face recognition for almost over a decade. Initial test results suggest that these techniques can be used to assess the type and extent of damage in composite panels. The assessment can be performed by comparing the key geometric features in the full-field displacement, strain or stress maps of damaged components with those in the corresponding maps of undamaged components. In this study two shape descriptors viz. Zernike moments and Fourier descriptors will be used to represent full-field maximum principal strain data obtained from digital image correlation for composite specimens with different levels of damage. The advantages and short-comings of these shape descriptors will be discussed together with the possibility of combining Fourier decomposition with Zernike moments to provide a simple index of damage.