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首页> 外文期刊>Experiments in Fluids: Experimental Methods and Their Applications to Fluid Flow >A generalized processing technique in digital particle image velocimetry with direct estimation of velocity gradients
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A generalized processing technique in digital particle image velocimetry with direct estimation of velocity gradients

机译:直接估计速度梯度的数字粒子图像测速中的通用处理技术

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摘要

A technique is proposed for the processing of digital particle image velocimetry (PIV) images, in one single step providing direct estimates of fluid velocity, out-of-plane vorticity and in-plane shear rate tensor. The method is based on a generalization of the standard PIV cross-correlation technique and substitutes the usual discrete cross-correlation of image pairs with a correlation of interpolated two-dimensional image intensity functions, being subject to affine transformations. The correlation is implemented by using collocation points, on which image intensity values are interpolated. The resulting six-dimensional correlation function is maximized using a general purpose optimization algorithm. The use of the method is demonstrated by application to different types of synthetically generated image pairs constructed with known particle displacement functions. The resulting errors are assessed and compared with those of a representative standard PIV method as well as with those of the present technique using no differential quantities in the search of the peak location. The examples demonstrate that significant improvements in accuracy can be obtained for flow fields with regions containing strong velocity gradients. [References: 24]
机译:提出了一种用于处理数字粒子图像测速(PIV)图像的技术,只需一步即可直接估算出流体速度,平面外涡度和平面内剪切速率张量。该方法基于标准PIV互相关技术的一般化,并使用经过仿射变换的插值二维图像强度函数的相关性替换图像对的常规离散互相关。通过使用并置图像强度值的并置点来实现相关性。使用通用优化算法可以使所得的六维相关函数最大化。通过将其应用于以已知的粒子位移函数构造的不同类型的合成生成的图像对,证明了该方法的使用。评估所得的误差,并将其与代表性标准PIV方法的误差以及与本技术的误差进行比较,而在寻找峰位置时不使用差分量。这些示例表明,对于包含强速度梯度区域的流场,可以在精度上取得显着提高。 [参考:24]

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