Based on full scale model of 1-beam and end-plate welding assembly with medium plate, welding temperature field and residual stress were simulated, infrared thermometers were employed to measure the real-time temperat...Based on full scale model of 1-beam and end-plate welding assembly with medium plate, welding temperature field and residual stress were simulated, infrared thermometers were employed to measure the real-time temperature Jbr verification purposes. Results show that the measured thermal cycle curves match well with the simulation result. Simulation results of welding residual stress indicate that the values of longitudinal and transverse stress on the upper surface of the plate are higher than the normal stress; higher tensile stresses exist at the end of the web weld toes and in the central area of the flange weld toes. The dangerous zones are located at the central areas of weld toes of the flange welds and near weld toes of the web welds.展开更多
The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The ...The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.展开更多
In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emp...In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.展开更多
基金This research was supported by the National Natural Science Foundation of China （51171093）.
文摘Based on full scale model of 1-beam and end-plate welding assembly with medium plate, welding temperature field and residual stress were simulated, infrared thermometers were employed to measure the real-time temperature Jbr verification purposes. Results show that the measured thermal cycle curves match well with the simulation result. Simulation results of welding residual stress indicate that the values of longitudinal and transverse stress on the upper surface of the plate are higher than the normal stress; higher tensile stresses exist at the end of the web weld toes and in the central area of the flange weld toes. The dangerous zones are located at the central areas of weld toes of the flange welds and near weld toes of the web welds.
基金The Natural Science Foundation of Jiangsu Province,China(No.BK20200470)China Postdoctoral Science Foundation(No.2021M691595)Innovation and Entrepreneurship Plan Talent Program of Jiangsu Province(No.AD99002).
文摘The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.
基金The National Natural Science Foundation of China(No.51675100)the National Numerical Control Equipment Major Project of China(o.2016ZX04004008)
文摘In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.
