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Evaluation of the use of fiber optic sensors in identification of fresco fracturing patterns

机译:评估光纤传感器在识别壁画压裂样式中的应用

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Ageing of materials and extreme events tend to damage structures, and ancient historical monuments are particularly vulnerable due to their age and long-term exposure to adverse events and influences. As an example, the wall paintings (frescoes) from the seventeenth century BCE found at the archaeological site of Akrotiri (Santorini, Greece) were recovered from volcanic ash in fragments with dimensions ranging from a few centimeters to a few decimeters. Identification of the fracturing patterns is helpful to the process of piecing together the fragments of frescos. Previous work has involved looking at fracturing patterns in frescos that have been reassembled. Recent work has looked at the process by which fractures develop. Current identification techniques involve experimental study of fracture development on plaster molds using a high-speed camera combined with sophisticated algorithms for pattern recognition. However, the use of a high-speed camera is challenging due to very demanding data processing and analysis and some inaccuracies in identification of fracture initialization generated by light conditions. This paper aims to evaluate whether or not short-gauge fiber optic sensors (FOS) based on Fiber Brag-Gratings (FBG), can be used to help identify the fracturing patterns of falling frescoes as a complement to high-speed cameras. In total four tests were performed using surface and embedded sensors on various plaster molds. The data taken by sensors installed on the surface of the mold were more complex to analyze and interpret than the data taken by embedded sensors, since the former reflected combined influence from fracture and bending. While their practicality is challenged by cost, moderately dense arrays of embedded FOS are found to be a plausible complement to the high speed-camera in the experiments.
机译:材料的老化和极端事件往往会损坏建筑物,而古老的历史古迹由于年代久远和长期遭受不良事件和影响而特别脆弱。例如,从阿克罗蒂里考古遗址(希腊圣托里尼)发现的公元前十七世纪的壁画(壁画)是从火山灰中回收的,碎片的大小从几厘米到几分米不等。压裂模式的识别有助于将壁画的碎片拼合在一起的过程。先前的工作涉及查看已重新组装的壁画的压裂模式。最近的工作研究了骨折发展的过程。当前的识别技术涉及使用高速相机结合用于模式识别的复杂算法对石膏模具上的裂缝发展进行实验研究。但是,由于对数据的处理和分析要求很高,并且在识别由光照条件引起的断裂初始化方面存在一些不准确之处,因此使用高速摄像机具有挑战性。本文旨在评估是否可以使用基于光纤布拉格光栅(FBG)的短规格光纤传感器(FOS)来帮助识别掉落的壁画的断裂模式,以作为高速相机的补充。使用表面和嵌入式传感器在各种石膏模具上总共进行了四项测试。安装在模具表面上的传感器所获取的数据比嵌入式传感器所获取的数据更难以分析和解释,因为前者反映了断裂和弯曲的综合影响。尽管它们的实用性受到成本的挑战,但在实验中发现中等密度的嵌入式FOS阵列可能是高速相机的合理补充。

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