非定常三维复杂流动的单相机层析PIV测量系统研究

层析PIV技术作为最新的体PIV测量技术，通过MART算法有效解决了PIV体测量中示踪粒子浓度不能太高的问题，使测量的空间分辨率大大提高，并开始被应用于实验测量。然而复杂的多相机实验平台使得层析PIV测量成本高昂且操作困难，这些都限制它的应用推广。为了使层析PIV具有更广的适用性，能更好应用于非定常复杂三维流动的测量，项目将研制一种单相机层析PIV测量的系统。该系统包括实验平台和数据处理软件，在保证传统层析PIV测量精度的前提下，仅利用一台相机实现时间解析的3D3C速度场测量。在简化实验平台的同时，系统将采用更为优化的层析PIV算法，数据处理实现并行计算和GPU硬件加速。同时，探索三维模态分解和三维旋涡辨识等针对3D3C实验数据的流场诊断技术。最终，将利用单相机层析PIV系统实现湍流边界层流动的多尺度测量，以验证单相机层析PIV系统的可靠性和实用性。

As the most advanced volumetric particle image velocimetry (PIV), tomographic PIV overcomes the issue of low tracer density in volumetric PIV measurements because of its multiplicative algebraic reconstruction technique (MART). Tomographic PIV has been widely used in experimental measurements due to its good performance on spatial resolution comparing to other volumetric PIV techniques. However, the costliness and complicity of a tomographic PIV system with multiple cameras slow down its expansion on application. For better applying tomographic PIV technique to measure complex and turbulent flows, this project aims to develop a single-camera tomographic PIV system. The system includes hardware and software, which only uses one camera to achieve a three-dimensional three-component (3D3C) velocity measurement with equivalent accuracy of a general tomographic PIV system. Besides the simplification of the setup, the data processing algorithms will be optimized as well as applying parallel processing and acceleration using the technique of graphics processing unit (GPU) in the software. Meanwhile, data analysis methods on a 3D3C experimental velocity field will be studied, such as three-dimensional mode-decomposition techniques and vortex identification algorithms. Eventually, the new system will be tested on a measurement of turbulent boundary layer flow using single-camera tomographic PIV system to verify the reliability and practicability of the new developed measurement system.