| Arc additive manufacturing is a hotspot of current research on additive manufacturing.Double-wire MIG welding is an efficiency,low spatter,low porosity and high adaptability process in arc additive manufacturing.However,the deposition forming will deteriorate with the increase of the welding speed in double-wire MIG welding,which is caused by the inconsistency of the penetration depth and the fusion width.In order to resovle the above problems,this paper proposed an additive manufacturing method for double-wire MIG welding based on additional shielding gas.By introducing an additional shielding gas device,the impact force of the additional shielding gas and the extended protection time acting on the liquid molten pool were adjusted to form the welding seam,expanding the welding process window,and improving the efficiency of double-wire MIG welding additive manufacturing.The main work of the thesis is as follows:(1)A double-wire MIG welding additive manufacturing robot platform with an additional shielding gas was establish,and the process control algorithm,and a fuzzy evaluation method for quality of double wire MIG welding additive manufacturing sample.were studied.The platform included additional shielding gas device,double-wire MIG welding power source,additive manufacturing robot control system and double-wire MIG welding additive manufacturing sample quality fuzzy evaluation system,which could collect and analyze the current and voltage waveforms of the welding process in real time during the layer-by-layer deposition process,display and store it on the human-machine interactive interface of computer,and also could monitor the forming situation of the additive manufacturing in real time,and thereby control the progress of the additive manufacturing.In addition,fuzzy rules were used for fuzzy evaluation of the quality of double-wire MIG welding additive manufacturing samples.(2)The Simulink model of the dual-wire MIG welding system was established.On the basis of the model,the current waveform comparison tests of classic PID control and neuron network PID control,particle swarm optimization neuron network PID adaptive control were carried out.The experiment proved that the particle swarm optimization neuron network PID adaptive control performance was superior to the neuron network PID control and classic PID control,and had a faster response speed,stronger anti-interference ability and good forming quality to the pulse current output in the additive manufacturing process.(3)A double-wire MIG welding additive manufacturing process test with the additional shielding gas,a self-programmed robot platform and a double-wire welding power supply was carried out.The test showed that the additional shielding gas could be used to manufacture straight-wall parts by the double-wire MIG welding and the forming quality and mechanical properties had an improving effect.Moreover,the high-speed MIG welding test with additional shielding gas proved that the additional shielding gas had the effect of reducing heat input and improving the mechanical properties of the weld.The best additional shielding gas process parameters were selected and used in the additive manufacturing test.The additional protection was analyzed by comparing the three parameters of the additional gas flow rate,the angle between the nozzle and the welding gun and the scanning speed.The effect of gas on the microstructure and mechanical properties of single-pass multilayer deposition specimens showed that the new process of additional shielding gas could significantly inhibit defects such as unmelted,undercut and hump weld bead in high-speed welding,and significantly improve welding speed,the appearance and mechanical properties of specimens.The optimal flow rate of additional protective gas for additive manufacturing was 18L/min,and the angle between the welding gun and the additional protective gas nozzle was 28 degrees.Under this parameter,additive manufacturing with a scanning speed of 2 m/min could be realized. |
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