摘要
Welding spatter seriously affects the surface quality of the product. Aiming at the automatic detection problem of spatter on welding plate surface, an in-situ detection algorithm of welding spatter based on machine vision is designed. In the extraction process of the welding spatter, the two-dimensional Fourier transform is adopted to obtain the frequency and phase information of image, and the elliptical high-pass filter is introduced to filter the low-frequency signal. The experimental results show that the proposed algorithm has higher extraction rate and extraction accuracy rate of welding spatter than the threshold method, the rectangular high-pass filter and the Canny operator, and it has the characteristics of high efficiency, high precision, and good robustness.
Welding spatter seriously affects the surface quality of the product. Aiming at the automatic detection problem of spatter on welding plate surface, an in-situ detection algorithm of welding spatter based on machine vision is designed. In the extraction process of the welding spatter, the two-dimensional Fourier transform is adopted to obtain the frequency and phase information of image, and the elliptical high-pass filter is introduced to filter the low-frequency signal. The experimental results show that the proposed algorithm has higher extraction rate and extraction accuracy rate of welding spatter than the threshold method, the rectangular high-pass filter and the Canny operator, and it has the characteristics of high efficiency, high precision, and good robustness.
作者
夏新苗
姜兆亮
许鹏飞
XIA Xin-miao;JIANG Zhao-liang;XU Peng-fei
基金
supported by the National Natural Science Foundation of China(No.51175304)
the Natural Science Foundation of Shandong Province(No.ZR2017MEE052)
