抑压水池淹没射流图像自动处理与分析

抑压水池中淹没射流导致的喘振现象对抑压系统的可靠性有较大影响，而气泡行为直接关系到喘振的机理。为更好地识别喘振现象中的气泡行为，本文提出了一种基于改进的分水岭图像分割算法的蒸汽淹没射流图像自动处理方法。基于像素矩阵建立微分模型，提取气泡二维信息并近似估计三维信息，进而获取射流体积变化情况。借助图像灰度方差信息，提取气泡冷凝周期。算法提高了射流气泡的识别精度。通过与人工标定比对，图像区域识别误差控制在10%以内；经验证，简化椭圆模型计算图像投影面积的相对误差较小；气泡参数与冷凝周期提取结果符合实验表征与理论规律。

Automatic Processing and Analysis of Submerged Jet Image in Suppression Pool

The surge caused by submerged jets in the suppression pool has a major impact on the reliability of the suppression system. And the bubble behavior is directly related to the mechanism of the surge. In order to better identify the bubble behavior in the surge phenomenon, an automatic image processing method of steam submerged jet based on improved watershed image segmentation algorithm is proposed. The differential model is established based on the pixel matrix, the two-dimensional information of the bubble is extracted and the three-dimensional information is approximately estimated, and then the variation of the jet volume is obtained. The bubble condensation period is extracted by using the gray variance information of the image. The algorithm improves the identification accuracy of jet bubbles. Compared with manual calibration, the error of image area recognition is controlled within 10%; It is proved that the relative error of image projection area calculated by the simplified ellipse model is small, and the extraction results of bubble parameters and condensation period are consistent with the experimental characterization and theoretical law.