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Image Processing of Vacuum Arc Based on Two-dimensional Segmentation Algorithm

机译:基于二维分割算法的真空弧的图像处理

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The processing technology of the arc image is an effective and direct way to study the arc variation. The accuracy of the subsequent arc feature extraction is related to the segmentation of arc image. A two-dimensional algorithm is applied to the image processing of vacuum arc in this paper. The intermediate-frequency vacuum arc has been captured by the high speed camera. The arc images are processed by the dual-threshold adaptive segmentation algorithm. The genetic algorithm is applied to obtain the optimal solution and the parameters of the two-dimensional space. Compared with the traditional subjective threshold, the threshold of this two-dimensional algorithm is self-adaptive. The arc image can be divided into the high energy plasma zone, the contour area and the background area. The results showed that the two-dimensional algorithm proposed in this paper can be used to segment the arc image at the whole combustion stage.
机译:电弧图像的处理技术是研究电弧变化的有效和直接的方法。随后的弧形特征提取的准确性与弧图像的分割有关。本文应用了二维算法对真空弧的图像处理。中频真空电弧已被高速摄像机捕获。电弧图像由双阈值自适应分割算法处理。遗传算法应用于获得最佳解决方案和二维空间的参数。与传统的主观阈值相比,该二维算法的阈值是自适应的。电弧图像可以分为高能等离子体区域,轮廓区域和背景区域。结果表明,本文提出的二维算法可用于在整个燃烧阶段分段电弧图像。

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