现有光流法解算基于荧光油膜的摩阻测量方程耗时长，制约了荧光油膜试验技术在生产型风洞中的推广应用。为此，提出了荧光油膜速度场的空间自适应快速光流解法，一方面通过推导构造共轭迭代式，较现有光流法的雅可比矩阵分割迭代式，有更小的存储量、更高的收敛性与稳定性；另一方面结合荧光油膜图像的灰度梯度信息，对图像进行空间自适应降采样进行共轭迭代快速获得大流动结构，再升到满分辨率迭代和全局优化，即可准确捕捉到精细的流动结构，大幅提高荧光油膜速度场的解算速度。仿真实验表明：在给定收敛误差限下本算法较现有光流法计算速度提升26.6%，在相同预设迭代次数下，平均误差减小1.4%，最大误差减小2.3%。多个高速风洞的油膜试验结果表明：本算法测得壁面流动现象正确、流谱清晰精细，较现有光流法计算速度平均提升了23%，优势明显，工程应用价值大。

The existing optical flow methods takes a long time to solve the friction measurement equations based on the fluorescent oil film， restricting the application of fluorescent oil film tests in the wind tunnel. Therefore， a spatially adaptive fast optical flow method for the fluorescent oil film velocity field is proposed. The conjugate iterative formula of the optical flow is constructed， with a smaller storage capacity， higher convergence and stability than those of theJacobian-like matrix segmentation iteration used by the existing optical flow methods. On the other hand， based on the grayscale gradients of a given fluorescent oil film image， the prominent flow structures can be quickly obtained by a spatially adaptive down sampling method， then up sampling to obtain the refined flow structures by conjugate iteration and executing global optimization， and the speed of solving the velocity field of the fluorescent oil film is significantly improved. Simulation examples show that the calculation speed of this algorithm is 26.6% higher than that of the existing optical flow method under the given convergence error limits， the average errors are reduced by 1.4%， and the maximum error is reduced by 2.3% under the same preset number of iterations. The results of the oil film tests in the wind tunnel show that the wall flow phenomenon measured by this algorithm is correct， and the flow spectrum is clear and precise. Compared with the existing optical flow method， this new method has a speed increase of 23% on average， exhibiting important application value in engineering.