Bayesian Estimation of Defect Patterns in Composite Materials using Through-Thickness Dielectric Measurements

摘要

Composite materials play important roles in multifunctional applications, and thus, the diagnosis of damagepatterns in composite materials becomes crucial to avoid "critical events" such as structural or functional failures.The impact of an individual damage in composite materials has been extensively studied, however, the interactionof defects/cracks, which leads to critical fracture paths, has not been understood well. In this paper, we developa Bayesian estimation based statistical analysis technique that estimates the damage pattern of a compositematerial, in particular, the relative positions of defects in the material, by measuring its through-thicknessdielectric properties. We first explain the fundamental dielectric principle that leads to the detection of defectpatterns. A capacitance model is then built to measure the material permittivity, and the relationship betweenthe dielectric permittivity and relative positions are found using COMSOL Multiphysicsr. The interactioneffects between defects observed in the simulation are interpreted using the fundamental dielectric principle. ABayesian estimation based statistical analysis model is then developed to estimate the relative positions of defectsin composite materials from the measured global dielectric properties.