Rainbow particle tracking velocimetry (PTV) is a PTV method that enables three-dimensional (3D) three-component flow measurement using a single camera. Despite the advantage of its simple setup, the accuracy of the particle depth is restricted due to false color caused by image sensor arrays, such as Bayer arrangement. Since the false color occurs near sharp edges in the color gradient of in-focus individual particle images, we here introduced a defocusing technique to rainbow PTV to remove these false colors. Defocusing led to moon-shaped distorted particle images, which we applied an adaptive mask correlation technique to detect. Multi-cycle rainbow illumination was realized as an additional improvement on the defocusing technique. In particular, individual particle coordinates were obtained by a combination of the color and constitution of pixels. This dramatically increased the depth resolution of the 3D particle tracking. The feasibility of the proposed method was demonstrated by a flow driven by rotating impellers and a wake behind a twisted Savonius turbine. By the demonstration, it is confirmed that the twisted turbine suppresses the loss of kinetic energy by shedding streamwise vortices in the wake.

Graphic abstract

中文翻译：

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粒子散焦技术改进的多周期彩虹粒子跟踪测速技术的发展及其在萨沃纽斯涡轮机上的应用实例

彩虹粒子跟踪测速（PTV）是一种PTV方法，可使用单个摄像机进行三维（3D）三组分流量测量。尽管它具有简单设置的优点，但是由于图像传感器阵列（如拜耳排列）导致的伪色，粒子深度的准确性受到限制。由于虚假颜色出现在焦点对准的单个粒子图像的颜色梯度中的尖锐边缘附近，因此我们在此处为彩虹PTV引入了散焦技术以消除这些虚假颜色。散焦导致月亮形失真的粒子图像，我们应用了自适应蒙版相关技术进行检测。实现了多周期彩虹照明，这是对散焦技术的另一项改进。尤其是，通过像素的颜色和构成的组合获得单独的粒子坐标。这极大地提高了3D粒子跟踪的深度分辨率。旋转叶轮和扭曲的Savonius涡轮后面的尾流驱动气流，证明了该方法的可行性。通过演示，证实了扭曲的涡轮机通过在尾流中散开沿流的涡流来抑制了动能的损失。

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