Quality monitoring of resistance spot welding based on image processing of welding spot surface

A new methodwas explored to monitoring joint quality based on information processing in digital image of welding spot surface in resistance spot welding. At first, through analyzing the image character, 4 characteristic zones related to welding processing were mined from the image of welding spot surface.And then, their areas were measured to be taken as characteristic parameters for evaluating spot welded joint quality.Secondly, through the correlation analysis between 4 characteristic zones areas and tensile-shear strength of spotwelded joint, 3 characteristic parameterswere selected as input vectorsfrom them, and tensile-shear strength of the joint was target vectors.On the basis, Radical Basic Function neural networkmodel was set up to estimate the weld quality. At last, the results of simulation and test show that it is feazible that spot-welded joint quality can be monitored based on image information of welding spot surface.