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首页> 外文期刊>Composite Structures >Impact characterisation of draped composite structures made of plain-weave carbon/epoxy prepregs utilising smart grid fabric consisting of ferroelectric ribbon sensors
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Impact characterisation of draped composite structures made of plain-weave carbon/epoxy prepregs utilising smart grid fabric consisting of ferroelectric ribbon sensors

机译:利用由铁电带传感器组成的智能电网织物,由透明碳/环氧树脂预浸料坯制成的悬垂复合结构的影响特征

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摘要

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 degrees, 30 degrees, and 45 degrees) 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.
机译:在该研究中,通过进行失效特征和利用基于聚偏二氟化族织带传感器组成的智能网格织物(SGF)的若干信号处理技术来研究非剪切和剪切织物复合结构的冲击特性。为了鉴定剪切变形对复合结构的冲击特性的影响,制备具有三种不同剪切角(0度,30度和45度)的SGF嵌入的编织复合层压层。另外,通过制备SGF嵌入复合半球进行垂直的三维复合结构的影响特征。通过使用离散小波变换和贝叶斯正规化的人工神经网络模型分别进行这些标本的故障特征和影响定位。最后,基于各种实验和分析的结果验证了剪切复合材料结构中SGF的可行性。

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