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首页> 外文期刊>Structural health monitoring >Damage detection via electrical impedance tomography in glass fiber/epoxy laminates with carbon black filler
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Damage detection via electrical impedance tomography in glass fiber/epoxy laminates with carbon black filler

机译:通过具有碳黑填料的玻璃纤维/环氧树脂层压板的电阻抗层析成像检测损坏

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摘要

The conductivity of glass fiber reinforced polymers with nanocomposite matrices can be leveraged for structural health monitoring. Since nanocomposite matrices depend on well-connected networks of conductive nanofillers for electrical conductivity, matrix damage will sever the connection between fillers and result in a local conductivity loss. Monitoring composite conductivity changes can therefore give insight into the state of the matrix. Existing conductivity-based structural health monitoring methods are either insensitive to matrix damage or employ large electrode arrays. This research advances the state of the art by combining the superior imaging capabilities of electrical impedance tomography with conductive networks of nanofillers in the composite matrix. Electrical impedance tomography for damage detection in glass fiber/epoxy laminates with carbon black nanocomposite matrices is characterized by identifying a lower threshold of through-hole detection, demonstrating the capability of electrical impedance tomography to accurately resolve multiple through holes, and locating impact damage. It is found that through holes as small as 3.18 mm in diameter can be detected, and electrical impedance tomography can detect multiple through holes. However, sensitivity to new through holes is diminished in the presence of existing through holes unless a damaged baseline is used. Finally, it is shown that electrical impedance tomography is also able to accurately locate impact damage. These research findings demonstrate the considerable potential of conductivity-based health monitoring for glass fiber reinforced polymer laminates with conductive networks of nanoparticles in the matrix.
机译:具有纳米复合材料基质的玻璃纤维增​​强聚合物的电导率可用于结构健康监测。由于纳米复合材料矩阵的导电性取决于导电纳米填料的良好连接的网络,因此基质破坏会切断填料之间的连接,并导致局部导电性损失。因此,监测复合材料电导率变化可以洞悉基质状态。现有的基于电导率的结构健康监测方法要么对基质损坏不敏感,要么采用大型电极阵列。这项研究通过将电阻抗断层成像的卓越成像功能与复合基质中纳米填料的导电网络相结合,从而推动了最新技术的发展。具有碳黑纳米复合材料矩阵的玻璃纤维/环氧树脂层压板中用于损伤检测的电阻抗层析成像的特征在于,可以识别出较低的通孔检测阈值,证明了电阻抗层析成像能够准确分辨多个通孔并确定冲击损伤的能力。发现可以检测到直径为3.18 mm的通孔,而电阻抗层析成像可以检测到多个通孔。但是,除非存在损坏的基线,否则在存在现有通孔的情况下,对新通孔的敏感性会降低。最后,显示了电阻抗层析成像技术还能够准确地定位冲击损伤。这些研究结果表明,对于在基质中具有纳米颗粒导电网络的玻璃纤维增​​强聚合物层压板,基于导电率的健康监测具有巨大潜力。

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