Yn4 / 5 Of Welding Parameters Optimization And Experimental Research

YN4/5 recliner welded by welding robot, which quantity is not stable in mass production, there also has too much spatter. Actual product line controlled by means of analysis metallographic phase at the beginning the each shift, this cost too much and bring efficient pressure especially with customer request volume increased. There also have other 2 robots welding line which for structure has the same problem. Hope to learn from the relationship between key parameter with welding quality and welding spatter, optimize on YN4/5 recliner weld cell, and apply it on the frame robot cell.The analysis start from the droplet formation and detachment theoretic, and also learn from the welding parameter current, voltage, stick out, welding speed, shielding gases how influence the weld width, weld penetration, seam high, and spatter. By the means of orthogonal test on YN4/5 recliner welding robot cell and by spatter collection, infer the function of the total spatter and the welding current, voltage, stick out. Set up total weld spatter model, get the optimize result by calculation of Matlab genetic algorithms tool.Find the rough current and voltage range by means of broad parameter test, and then select the key parameter from big influence of welding width, welding penetration and seam high by means of orthogonal test, and analysis the result by range to find how the parameter influence the welding quality: the crosstalk of the current and voltage have a big influence to the penetration, then the welding speed; the welding voltage have a big influence to the seam high; the stick out have a biggest influence to the weld width. Got the conclusion of current, voltage and stick out have a big influence of the welding quality; it's given the reference of the analysis of welding spatter.Secondly, only keep welding current, voltage and stick out as key parameter to collect spatter. Drawing the relation of welding current with total spatter weight, welding voltage, stick out, then infer the model of the total welding spatter weight, calculate the optimize result by genetic algorithms tool.Thirdly, validate the result calculated by genetic algorithms, which test result are quite close to the calculated result, what the inference of the welding current, voltage and stick out with the total spatter weight was proved.Finally, sum-up from what the above orthogonal test result and spatter analysis, got the YN4/5 welding parameter which could meet the technical requirement. These given the reference of optimize the structure welding.