论文标题
基于计算机视觉的结构使用3D数字图像相关性
Computer Vision based Tomography of Structures Using 3D Digital Image Correlation
论文作者
论文摘要
可以通过医学成像工具(例如超声设备,磁共振成像(MRI)和光学相干断层扫描(OCT)(OCT)观察到样品的内部特性,这些工具基于依赖材料密度或化学组成的变化[1-21]。作为初步研究,检测内部缺陷的可行性是从仅使用表面全场测量和有限元模型更新作为逆优化算法更新的三维异质样本弹性模量分布所推断出的,而无需假定局部均匀性和弹性模量的任何假设。最近,作者将数字图像相关技术的优势视为全尺度钢组件的本构属性识别中的全场测量[22-27]。为了扩展以前的作品的扩展,在此简短的技术说明中,旨在使用结构识别的3D数字图像相关性,旨在在结构组件的三维异质空间内部恢复未见的体积缺陷分布[28-57]。作为概念的证明,本文的结果说明了通过拟议的计算机视觉技术识别无形内部缺陷的潜力,这为新的机会提供了为其机械性能分布和状况状态表征内部异质材料的新机会。
Internal properties of a sample can be observed by medical imaging tools, such as ultrasound devices, magnetic resonance imaging (MRI) and optical coherence tomography (OCT) which are based on relying on changes in material density or chemical composition [1-21]. As a preliminary investigation, the feasibility to detect interior defects inferred from the discrepancy in elasticity modulus distribution of a three-dimensional heterogeneous sample using only surface full-field measurements and finite element model updating as an inverse optimization algorithm without any assumption about local homogeneities and also the elasticity modulus distribution is investigated. Recently, the authors took advantages of the digital image correlation technique as a full field measurement in constitutive property identification of a full-scale steel component [22-27]. To the extension of previous works, in this brief technical note, the new idea intended at recovering unseen volumetric defect distributions within the interior of three-dimensional heterogeneous space of the structural component using 3D-Digital Image Correlation for structural identification [28-57]. As a proof of concept, the results of this paper illustrate the potential to identify invisible internal defect by the proposed computer vision technique establishes the potential for new opportunities to characterize internal heterogeneous materials for their mechanical property distribution and condition state.