人工神经网络在图像测速技术中的应用

Artificial neural network application to image velocimetry technique

为了准确、快速地进行图像测速，介绍了一种前向三层自组织竞争人工神经网络，并将其应用于图像测速技术的粒子轨迹测速中。人工神经网络在图像测速技术中的应用才刚刚起步，该方法利用神经网络智能与快速的特点完成粒子的匹配，从而获得流场的速度。与以往的算法相比，神经网络方法具有检测准确和速度快的优点，但对图像质量要求较高。在恒定流流动表面流速的测量和Ｏｓｓｅｎ涡的模拟中分别使用了神经网络方法，获得了良好的测量结果，并证明了该方法在图像测速技术中的应用潜力。

A kind of forward three layers self organizing and competitive neural network is introduced. Its application of particle trajectory velocimetry, a kind of image velocimetry, is also presented. The application of artificial neural network to image velocimetry has just started. This new method found corresponding particles successfully by the means of intelligence and fast speed of a neural network. The velocity field can be obtained. Compared with other algorithms, neural network technique has advantages of accurate and fast detection. But it needs high quality images. Such a technique has applied to measurements of constant flow's surface velocity and Ossen vortex's simulation. The measurement results are good. These results demonstrate that the application of artificial neural network to image velocimetry is much useful and has a great potentiality.