Abstract
In this study, the impact characteristics of non-sheared and sheared woven fabric composite structures were investigated by performing failure characterisations and estimating impact locations utilising several signal processing techniques based on a smart grid fabric (SGF) consisting of polyvinylidene difluoride ribbon sensors. To identify the effects of shear deformation on the impact characteristics of composite structures, SGF-embedded woven composite laminates with three different shear angles (0°, 30°, and 45°) were prepared. Additionally, impact characterisations of draped three-dimensional composite structures were performed by preparing an SGF-embedded composite hemisphere. Failure characterisations and impact localisations for these specimens were carried out by using a discrete wavelet transform and Bayesian regularised artificial neural network model, respectively. Finally, the feasibility of SGF in sheared composite structures was verified based on the results of various experiments and analyses.
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