基于ga的表面应变测量激光散斑图数字图像相关方法

Arka Das, E. Divo, F. Moslehy, A. Kassab
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引用次数: 0

摘要

本文介绍了一种将基于遗传算法(GA)的数字图像相关与激光散斑摄影相结合的创新技术,用于估计结构中的表面位移。利用数码相机对变形前后的图像进行数字化处理,并通过图像处理算法对灰度强度矩阵进行读取和处理。然后将图像的两个矩阵输入到基于遗传算法的优化器中,该优化器利用先进的相互关联适应度函数来近似表面位移。此外,利用径向基函数微分和插值法从位移中计算表面应变。将计算得到的位移与边界元法的模拟结果进行了比较。这两种计算结果非常接近,证明了所开发的非接触技术在精确估计表面位移和应变方面的有效性。这些实验估计的位移可以进一步用于逆技术来检测和表征结构中的地下空腔。
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GA-based laser speckle pattern digital image correlation method for surface strain measurements
This article introduces an innovative technique that integrates a genetic algorithm (GA)-based digital image correlation with laser speckle photography for the estimation of surface displacements in structures. The images (before and after deformation) are digitized using a digital camera, and the grayscale intensity matrices are read and processed by an image processing algorithm. The two matrices of the images are then inputted into GA-based optimizer that utilizes an advanced cross-correlation fitness function to approximate the surface displacements. Furthermore, the surface strains are computed from the displacements using radial basis function differentiation and interpolation. The computed displacements are compared with simulated results obtained by the boundary element method. Close agreement between the two results proves the validity of the developed noncontact technique for accurately estimating surface displacements and strains. These experimentally estimated displacements can further be used in an inverse technique to detect and characterize subsurface cavities in structures.
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