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The Method of Thread Defect Detection Based on Machine Vision

机译:基于机器视觉的螺纹缺陷检测方法

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To resolve the problem of low accuracy and difficulty in detecting threads, this paper proposes a method of detecting based on machine vision. The image of the threaded part is collected online by an industrial CCD camera, and the image is gray scaled, enhanced, binary and de-noised. The de-noising method selects the mathematical morphology operation. Mathematical morphology of corrosion, expansion, open and closed operations effectively preserves thread shape characteristics and edge information of the threads. The algorithm detects the position of the thread defect by locating the defect of the thread using a subtraction operation. The experimental results show that the algorithm has strong ability to identify and detect defects and can effectively identify appearance defects such as no thread, less thread and irregular pitch, which meets the basic design requirements.
机译:为解决精度低,线程检测困难的问题,提出了一种基于机器视觉的检测方法。螺纹部分的图像由工业CCD相机在线收集,并且图像是灰度,增强,二进制和去噪的。去噪方法选择数学形态学运算。腐蚀,膨胀,打开和关闭操作的数学形态有效地保留了螺纹的形状特征和螺纹的边缘信息。该算法通过使用减法运算定位螺纹缺陷来检测螺纹缺陷的位置。实验结果表明,该算法具有较强的缺陷识别与检测能力,能够有效识别出无螺纹,螺纹少,节距不规则等外观缺陷,符合基本设计要求。

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