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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Vision inspection system for the identification and classification of defects in MIG welding joints
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Vision inspection system for the identification and classification of defects in MIG welding joints

机译：视觉检查系统，用于对MIG焊接接头中的缺陷进行识别和分类

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摘要

The variety of vision inspection systems for welding defects in the present manufacturing scenario is needed for overcoming certain limitations such as the problem of inaccuracy in the images, non-uniformed illumination, noise and deficient contrast, and confusion in defects if they occur in the same spot at the surface and subsurface. Hence, it is imperative to design a new vision inspection system which will enable to overcome the aforementioned problems in welding. A sophisticated new vision inspection system using machine vision has been developed for this study to identify and classify the surface defects of butt joint as per standard EN25817 in metal inert gas (MIG) welding. In this proposed vision system, images of welding surfaces are captured through a CCD camera. Four frames of sequence of images are obtained using four zones of LEDs using the front light illumination system in this method. From these images, the regions of interest are segmented and the average gray levels of the characteristic features of these images are calculated. The same process can be extended further to four zones (four quadrants) of four types of welded joints. Finally, welded joints can be classified into one of the four predefined ones based on the back-propagation neural network. The proposed system demonstrates an overall accuracy of 95% from the 80 real samples tested.
机译：为了克服某些局限性，例如图像中的不准确，照明不均匀，噪声和对比度不足以及缺陷（如果它们在同一环境中出现）的混淆等问题，需要在当前制造场景中使用多种用于焊接缺陷的视觉检查系统。在表面和地下发现斑点。因此，必须设计一种新的视觉检测系统，以克服焊接中的上述问题。针对这项研究，已经开发了一种使用机器视觉的先进的新型视觉检测系统，以根据金属惰性气体（MIG）焊接中的标准EN25817来对接接头的表面缺陷进行识别和分类。在该提出的视觉系统中，焊接表面的图像通过CCD摄像机捕获。在这种方法中，使用前灯照明系统使用四个LED区域获得四帧图像序列。从这些图像中，分割出感兴趣的区域，并计算出这些图像的特征的平均灰度级。可以将同一过程进一步扩展到四种类型的焊接接头的四个区域（四个象限）。最后，基于反向传播神经网络，可以将焊接接头分类为四个预定义的接头之一。所提出的系统从80个实际样本中显示出95％的整体精度。

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