基于深度融合的全自动石英坩埚气泡检测方法

针对石英坩埚透明层中气泡检测依赖于人工肉眼检测，存在着效率低、准确性不高的问题，提出了一种基于深度融合 气泡检测算法(DFBDA) 。 首先，利用智能机械臂夹持工业显微镜，自动采集石英坩埚透明层的气泡视频图像；然后，使用融合 形态学变换的气泡分割和轮廓提取算法，以确保对气泡的准确分割；最后，通过深度融合方法对多帧相似气泡进行融合，实现 了对气泡准确位置的三维重建。针对不同坩埚样品的测试验证，实验结果表明，方法对气泡的平均识别准确率达到了 98.7%,速度和精度都满足工业需求。

Automatic quartz crucible bubble detection method based on deep fusion

Targeting the issue of low efficiency and accuracy in manually detecting bubbles within the transparent layer of quartz crucibles,this paper introduces a deep fusion bubble detection algorithm(DFBDA).Firstly,an intelligent robotic arm is employed to automatically capture video images of bubbles within the transparent layer of quartz crucibles using an industrial microscope.Next,a bubble segmentation and contour extraction algorithm,employing fused morphological transformations,ensures accurate bubble segmentation.Lastly,employing a deep fusion technique,similar bubbles across multiple frames are merged, enabling a precise three-dimensional reconstruction of bubble positions. Experimentation across various crucible samples validates the method,demonstrating an average bubble identification accuracy of 98.7%,meeting both speed and precision requirements in industrial settings.