Parameters optimization of laser welding process of galvanized steel and 6016 aluminum alloy based on BP neural network and its microstructure and mechanical properties

The laser lap welding test on the galvanized steel and the 6016 aluminum alloy with tie fiber laser and no brazing filler metal addition was carried out in order to inhibit or reduce the formation of Fe/Al brittle intermetallic compound. The laser welding heat source model of steel and aluminum was established by using ANSYS software. The penetration depths under different process parameters were given based on the simulation and experiment results, the nonlinear relationship between the process parameters, such as laser power, welding velocity and focal position and the penetration depth was established by the BP network, the welding parameters were also optimized. The microstructure, fracture morphology, element distribution, the main phase of the welded joint regional and mechanical properties of welded joints were studied by optical microscopy, scanning electron microscopy, X-ray diffractometry and microcomputer tensile testing machine. The results show that the simulation temperatures are consistent with the measured temperatures of different positions on the workpiece surface and the heat source model can be applied to the actual laser welding process, the relative error of the penetration depth under different process parameters can be controlled within 10% according to the trained network forecast. Under the optimal process conditions, aluminum melting and steel melting with a little amount on the weld cross-section take place, the wetting and spreading of the liquid aluminum on the steel surface are seen to keep good conditions. The thickness of intermetallic compounds layer is about 9 μm, which are composed of FeAl and Fe3Al. The average shear strength is 27.70 MPa, and the fracture morphology of welding joint is in a ductile and quasi-cleavage mixing mode.