Study on extraction method of liquid jet trajectory in low-speed air crossflow based on image processing
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摘要: 为研究低速横流条件下不同工况液体射流破碎的轨迹特征和影响因素，采用高速摄像仪拍摄射流破碎图像，结合图像处理技术提出针对低速横流情况下液体射流破碎弯曲轨迹的提取方法。该方法首先采用直方图均衡化对灰度化后的原始图像进行增强处理，然后利用最佳直方图熵法（KSW法）及传统遗传算法对图像进行二阈值分割，最后结合Sobel算子和凸包算法对射流轮廓进行检测提取以获得射流轨迹的数据点集。对不同工况下典型射流破碎模式的轨迹提取及非线性拟合结果表明，所提出的方法能够准确提取液体射流轨迹，实现低速横流作用下不同破碎模式的轨迹提取，并且通过非线性拟合得到的射流破碎经验公式可以准确预测射流弯曲轨迹。Abstract: In order to study the trajectory characteristics and influencing factors of liquid jets injected into low-speed air crossflow under different working conditions, the liquid jet breakup image is attained by the high speed camera, and the extraction method of trajectory characteristics of liquid jets injected into air crossflow is proposed, combined with image processing technology. Firstly, histogram equalization is used to enhance the gray-scale original image. Secondly, the optimal histogram entropy method (KSW entropy method) and traditional genetic algorithm are employed to achieve threshold segmentation. Finally, the Sobel operator and convex hull algorithm are served for extracting the jet edge contour, and obtaining the data point set of the jet trajectory. The results of trajectory extraction and fitting of typical jet breakup modes under different working conditions show that the proposed method can effectively extract the characteristics of the liquid jet fracture trajectory, and adapt to the track extraction of different liquid jet breakup modes under the action of low speed air crossflow. Besides, the empirical formula of jet breakup obtained by nonlinear fitting can predict the jet trajectory well.
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图 10 多帧图像的轮廓点提取对比
Figure 10. Comparison of multi-frame images trajectory point extraction
图 12 q=41.33、Wej=60.82工况下射流轨迹拟合结果
Figure 12. Jet penetration fitting result under q=41.33, Wej=60.82
表 1 实验工况
Table 1. Test conditions
实验参数 参数值 液体射流速度uj/(m·s-1) 0~10 液体密度ρj/(kg·m-3) 997 横向气流速度ug/(m·s-1) 5~30 气体密度ρg/(kg·m-3) 1.17 表面张力σ/(N·m-1) 0.0709 液/气动量通量比q=ρjvj2/ρgug2 2~400 射流Reynolds数Rej=ρjvjdj/μj 781~6837 液体Weber数Wej=ρjvj2dj/σ 20~1000 气体Weber数Weg=ρgug2dj/σ 0~20 
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