基于机器视觉的焊接缺陷检测方法研究

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Abstract：In order to improve welding quality and production eficiency，an automatic welding defect detection method basedon machine vision is proposed in this paper.The methodrealizes intellgent detectionand quantitative evaluation of welding defects by constructing a system architecture including image acquisition， preprocessing and defect identification. Firstly，in the image processing，the median filter and Gaussian filter algorithm are comprehensively used to efctively suppress the noise，and the discernabilityof the weld and itsdefect features is significantly enhanced through the steps of gray-scale，binarization and morphological processing.Secondly， combined with edge detection technology and quantitative analysis of defect area，the commondefect types such as pores，cracks and non-fusion in welds are accurately identified，providing reliable data support for welding quality control.Finally，the experimental results show that the method hasa high detection accuracy for typical welding defects such as cracks，poresand non-fusion，and the average error betweenthe measured resultsand the measured values is controlled within 0.1cm ，which fully meets the practical application needs of industrial production.

Keywords： machine vision; welding defect detection;image processing; defect feature extraction; defect area measurement

1序言

焊接技术在现代工业产品制造过程中占据着至关重要的地位，焊接质量的好坏与产品的安全、使用寿命有着直接的关系。（剩余10038字）