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Limits and accuracy of the Stereo-LFC PIV technique and its application to flows of industrial interest

机译:立体声LFC PIV技术的局限性和准确性及其在工业利益流中的应用

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Particle image velocimetry with local field correction (LFC PIV) has been tested in the past to obtain two components of velocity in a two dimensional domain (2D2C). When compared to conventional correlation based algorithms, this advanced technique has shown improvements in three important aspects: robustness, resolution and ability to cope with large displacements gradients. A further step in the development of PIV algorithms consists in the combination of LFC with the stereo technique, which is able to obtain three components of velocity in a plane (2D3C PIV). In this work this combination is implemented and its performance is evaluated carrying out the following two different tasks: Comparison of robustness and accuracy for large and small scale flow structures. This is carried out using three techniques: the conventional Stereo PIV, the Stereo-LFC PIV and the Stereo-Multigrid PIV enhanced with image distortion. Insight on the limit of resolvable scales for the Stereo-LFC. This task is relevant because the resolution attainable by this combination is higher than what has been obtained by the rest of the herein used algorithms. The first task has been achieved using synthetic images. Afterwards the coherence of the results has been checked with real images. The results show improvement of Stereo-LFC PIV in respect to Stereo-Multigrid PIV enhanced with image distortion. The performance of Stereo-LFC when only large scales are involved shows an increase of the dynamic range of measurable vorticity. When small scales are analysed, the magnitude of the error resulting when using Stereo-LFC is about half of the one obtained for the Stereo-Multigrid measurements. Results with errors below 20% have been achieved for some of the cases with peak vorticities as large as 1.8 Delta t(-1)(in the absence of out-of-plane displacements), out-of-plane loss of particle pairs of 65% (with a low peak vorticity of 0.06 Delta t(-1)) and peak vorticities as large as 1.5 Delta t(-1) stop with 50% particle pair loss. For the second task most of the information has been obtained using real images. It has been found that the resolution limit is very dependent on the robustness of the algorithms against image defects and variability. The results show a remarkable improvement when using the Stereo-LFC PIV processing, although a full quantification and characterization would need further study because of the variety of noise sources possible in a real image.
机译:过去已经对具有局部场校正的粒子图像测速技术(LFC PIV)进行了测试,以获得二维域(2D2C)中速度的两个分量。与传统的基于相关性的算法相比,这项先进的技术在三个重要方面均有改进:鲁棒性,分辨率和应对大位移梯度的能力。 PIV算法开发的又一步是将LFC与立体声技术相结合,该技术能够获得平面中三个速度分量(2D3C PIV)。在这项工作中,将执行以下两个不同任务来实现这种组合并评估其性能:比较大型和小型流动结构的鲁棒性和精度。这使用三种技术来执行:常规的立体声PIV,立体声LFC PIV和通过图像失真增强的立体声多重网格PIV。洞察立体声LFC的可分辨刻度的极限。该任务是有意义的,因为通过这种组合可获得的分辨率高于通过本文中其余算法获得的分辨率。使用合成图像已经实现了第一个任务。之后,已经用真实图像检查了结果的一致性。结果表明,相对于立体多重网格PIV,Stereo-LFC PIV的改进具有图像失真。仅涉及大尺度时,立体声LFC的性能表明可测量涡度的动态范围有所增加。当分析小比例尺时,使用Stereo-LFC时产生的误差幅度约为Stereo-Multigrid测量所获得误差的一半。对于某些峰值涡度高达1.8 Delta t(-1)(在没有平面外位移的情况下),粒子对的平面外损失的情况,已经获得了误差低于20%的结果65%(具有0.06 Delta t(-1)的低峰值涡度)和高达1.5 Delta t(-1)的峰值涡度会因50%的粒子对损失而停止。对于第二个任务,大多数信息是使用真实图像获得的。已经发现,分辨率极限非常依赖于针对图像缺陷和可变性的算法的鲁棒性。结果表明,使用立体声LFC PIV处理时,尽管实际图像中可能存在多种噪声源,但仍需要进一步研究完整的量化和表征,因此结果显示出显着改善。

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