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Hybrid Particle Image Velocimetry with the Combination of Cross-Correlation and Optical Flow Method

机译:互相关和光流方法相结合的混合粒子图像测速

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摘要

Particle Image Velocimetry (PIV) has been of relevant discussions lately as the equipment used to obtain temporally and spatially resolved flow fields have advanced rapidly. Despite these advancements, the accuracy of evaluating these images have yet to exceed expectations. Current techniques typically utilize one method, either correlation based (frequently) or optical flow (non-frequently), and both are vulnerable to specific conditions incorporated in the PIV images. Only through the combination of two methods, cross correlation and optical flow, can a technique benefit from the strengths of each method while concealing the flaws each individual method contains. The Hybrid Particle Image Velocimetry method utilizes the fairly unrestricted cross-correlation method, which can process images that contain particles with relatively large displacements, and the high resolution analysis of the Optical Flow method. Susceptible to large displacements, the Optical flow method is restricted to images with particularly small displacements. Combining the two methods requires the constraints set forth on the Optical flow method to be conserved. Meaning that the Cross-correlation results have to be manipulated into a form applicable for the Optical Flow method. Thus steps such as interpolation, shifting the image, and filtering the image are crucial for transitioning cross-correlation results to optical flow analysis. Validating the accuracy of the Hybrid method was conducted through standard PIV images that encompassed various parameters encountered in PIV. Each set of images were analyzed by the hybrid method and three other commonly-used correlation techniques in order to compare the hybrid method\u27s accuracy with current methods. Results confirmed that the Hybrid method is consistently more accurate than the other methods, especially near the boundaries. Additionally, for cases dealing with large particles or small displacement, the Hybrid method attains more accurate results.
机译:随着用于获得时间和空间分辨流场的设备的迅速发展,粒子图像测速技术(PIV)一直是最近的相关讨论。尽管取得了这些进步,但评估这些图像的准确性仍未超出预期。当前的技术通常利用一种方法,要么基于相关(频繁),要么基于光流(不​​频繁),并且这两种方法都容易受到PIV图像中包含的特定条件的影响。只有通过将互相关和光流这两种方法结合起来,一种技术才能从每种方法的优势中受益,同时掩盖每种方法所包含的缺陷。混合粒子图像测速方法利用了相当不受限制的互相关方法,该方法可以处理包含位移相对较大的粒子的图像,以及光流方法的高分辨率分析。易受大位移影响,光流法仅限于位移特别小的图像。两种方法的组合要求保留关于光流方法提出的约束。这意味着必须将互相关结果处理为适用于“光流”方法的形式。因此,诸如插值,图像移位和图像滤波等步骤对于将互相关结果转换为光流分析至关重要。通过包含PIV中遇到的各种参数的标准PIV图像来验证混合方法的准确性。通过混合方法和其他三种常用的相关技术对每组图像进行分析,以比较混合方法与当前方法的准确性。结果证实,混合方法始终比其他方法更准确,尤其是在边界附近。此外,对于处理大颗粒或小位移的情况,混合方法可获得更准确的结果。

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    Johnson, Mark Bradley;

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  • 年度 2016
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