叶栅纹影试验图像增强及流场密度处理探讨

Study of Image Enhancement Method and Flow Field Density Processing in Cascade Schlieren Test

叶栅纹影图像的背景噪声和流场结构信息接近,给识别流场结构和获取定量信息带来了困难。采用加权L_(0)梯度平滑和伪彩色技术,提高纹影图像中关键流场结构的识别度。并探讨了通过标定纹影图像灰度与光线偏移量(刀口切割量)的函数关系,反演试验流场中的密度分布。研究结果表明,采用上述方法获得的流场纹影图像质量良好,叶栅通道内激波、尾迹和膨胀波的分辨率高,流场信息可读性强。验证了纹影图像及密度处理程序的可行性,但流场密度的准确测量需要在试验件加工装配、试验前光学调校和图像灰度标定等多方面开展细致的准备工作。

The background noise of cascade schlieren image is close to the information of flow field structure,so it is difficult to identify the flow field structure and obtain the accurate quantitative information.Weighted L_(0)gradient smoothing and pseudo color technology are used to improve the recognition of key flow field structures in schlieren images.Furthermore,through calibrating the relationship between the gray value of schlieren image and the light offset(knife edge cutting),the density distribution in the cascade experimental flow field is inversed.The results show that the flow field schlieren image obtained by the above method has good quality,high resolution of shock wave,wake and expansion wave in cascade channel,and strong readability of flow field information.The feasibility of schlieren image and density processing program is verified,but the accurate measurement of density in flow field requires careful preparation in many aspects,such as test piece processing and assembly,optical adjustment before test and image gray scale calibration.