| Welding automation is a trend of welding technical development. Since the current"teaching and playback type"robot lack external information sensor feedback and the function of real-time adjusting, it could not meet the demands for the precision welding of complicated seam in aerospace high-tech product. Considering the uncertain factors of welding process, such as the welding distortion, alternate edge in the welded seams and the variable quantity of the gap, and they would affect the weld appearance quality directly.In this paper, several influence factors were analyzed synthetically by systematic method to emphasize in quantitative control of welding quality. Analysis and discussion from different angles, such as the prediction of the weld distortion, welding process optimization, system design, welding dynamic process modeling and weld appearance control, was studied. It is demonstrated that systematic method can meet the precision welding demands.Based on the non-linear finite element method, the numerical simulation of five-port connector was carried out using MSC.Marc software. The complex models are presented to normalize mechanical boundaries, thermal boundaries and heat source model. Based on the normalized finite element model, the above aerospace structure is calculated again, respectively studying the effects of the welding sequence and welding heat input quantity to welding distortion. On this basis, the welding fixture of the five-port connector was presented for the optimization design.In order to ensure the welding stability, welding heat input should be controlled precisely. And then the welding parameters could be adjusted according to the welding deformation and the dimension of the weld gap. Therefore, online quality control system for arc welding robot was established. The main functions of this system are listed as follows: arc start operation, welding parameters setting, the welding pool information acquisition and processing, real time adjusting and controlling the main parameters, and arc off operation.In order to extract the characteristic information of the weld pool accurately, several parameters about weld pool geometry and welding direction are defined. We make de-noising weld image by combining the Dual Tree Complex Transform Wavelet (DT_CWT) with the Biva-Shrink method. A new threshold segmentation algorithm of welding image with self-adaptive capacity and high precision was introduced. Aimed at the characteristic of the degradation weld pool, the shape parameter of the weld pool was obtained using boundary representation and description algorithm. Then, the restoration and geometry of the weld pool was extracted through the piecewise polynomial fitting method. For top-side weld pool image, the dimension information of the weld gap was extracted directly by the area filtering and Hough transform method. At last, plane flange weld and five port connector weld image was processed using above algorithms, and the results were reliable and stable.Arc welding procedure is the process, in which the welded material under the heat input started melting locally and then form weld pool. According to the characteristic of the weld process, non-linear Hammerstein model was led into the welding process. On this basis, IpVf-WbHt relation model was established. The results show that the model precision can meet the demands of the actual control. Meanwhile, the direct measurement of back-side width of the weld pool is very difficult, so RPROP dynamic prediction model was built to predict the Wb through procedure parameters and top-side information of the weld pool. The result shows that the RPROP algorithm provides both higher learning efficiency and stronger generalization capacity versus traditional method.The welding process is a complex, time-variant and uncertain system. In this paper, a quantitative rule (about wire feeding rate, welding current and the variable quantity of the gap) is introduced. On this basis, a nonlinear self-corrected controller and the compound intelligent controller with parameter preset was designed and its validation is conformed by Matlab Simulink toolbox. Butt welding experiments were conducted on unequal thickness test plate with varied gap. The results show that nonlinear self-corrected controller with weld current control variable could get better controlled performance.For the requirement of stabilizing backside width and weld reinforcement simultaneously, the compound intelligent controller with parameter preset can stabilize the shape of the weld pool under the conditions of the varied gap and alternate edge.In order to testify the reliability and stability of the compound intelligent controller in farther, the experiments were conducted on the plane flange and the spiral tube.It has been shown that the residual standard deviation of the back-side weld width and weld reinforcement are 0.84 mm,0.27 mm , 0.61 mm and 0.30mm, and it meets the demands of the space flight standard. Meanwhile, the maxium dimension of the gap is 1.8mm.In the end, based on the above development of robotic GTAW welding quality control system, the experiments were conducted on the five-port connector. After welding process, the distortion of the X,Y,Z direction are UX=0.6mm, UY=0.8mm, UZ=-0.3mm. The distortion of the Z direction was decreased by 73% than the traditional TIG process. The quality of the weldments met the standard of first-order (according to standard YS010-97).In general, the production quality was inproved increasingly. The work has laid the foundation for the engineering application in further.
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