基于BP神经网络的在役管道焊缝图像缺陷识别研究

Yin Jian, Gao Yuan
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引用次数: 0

摘要

本文采用计算机辅助技术对焊缝缺陷进行图像识别。并以缺陷的纵横比、圆度、紧密度、对称性、陡度、与背景的灰度对比、缺陷的位置作为缺陷的特征值。并应用BP神经网络对缺陷进行识别。并通过实验得到了特征值的最优值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the defects identify of the weld-line's image of the in-service pipeline based on BP neural network
This paper applied computer aided technique to do the image recognition work of the welding-line's defects. And this paper uses aspect ratio, roundness, compactness, symmetry, steepness, gray contrast of defect and the background, position of the defect as the defects' eigenvalues. And this paper applied BP neural network to recognize the defects. And experiments are used to get the best values of the eigenvalues.
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