A Study Of Forming Information Acquisition And Accuracy Control In Additive Manufacturing Based On Arc Welding Robot

Gas metal arc- additive manufacturing(GMA-AM) is a process of metal additive manufacturing, with the advantages of low cost, high efficiency and flexibility, etc. However, the deposition process is susceptible to interference, which leads to the deviation of the bead dimension. The subsequent process may not be strictly run in project with the accumulative deviation, and the forming parts are usually unqualified. So, improving the forming accuracy of GMA-AM has become an urgent problem need to solve. In this paper, an intelligent GMA-AM system was set up, in order to focus on the research of the forming information acquisition and the closed-loop control of multi-layer multi-bead structure made by GMA-AM.Firstly, according to the requirement of intelligent GMA-AM, an intelligent system was designed and set up based on the technology of arc welding robot and active vision sensing. With this system, bead dimension could be real-time measured by sensor, and saved, plotted by man-machine interface during the deposition process. Besides, with the interface of depositing parameters adjustment for operator, the system supports man-machine cooperation. Both of the operator and the machine can make decisions on the process, which may lay a good foundation for the closed-loop control.In this system, a line-structured laser sensor is used to collect the section ring data of the bead during the deposition process, and transform these data into point cloud data. A real-time algorithm based on the point cloud data was developed to measure the bead dimension of the GMA-AM multi-layer multi-bead structure. It extracts the characteristics of the vertex and weld toe from the point cloud data according to the morphological features of structured light, in order to calculate the height, the width, and the center distance of the bead. The result is modified by the bead section area to make it close to the real bead dimension.The transfer functions between the bead dimension and the depositing parameters were identified through analyzing the step responses. The strategy of controlling the bead width as the main goal, controlling the bead height and the layer smoothness as the second target was established. According to this strategy and the though of man-machine cooperation, a Single nerve cell self-study PI controller was designed for bead width control by adjusting the deposition velocity, and a controller based on experience rule was designed for bead height control by adjusting the deposition voltage, at the same time, the center distance was adjusted by operator to ensure the layer smoothness.Finally, in this paper, the depositing tests with close-loop control were carried out to deposit the parts, whose each layer has 2 overlapping beads. The results show that, the bead width accuracy is less than 0.5mm, and the height deviation has no obvious accumulation, each layer has smooth surface as well. It means that under the action of the control strategy and the controller designed in this paper, the dimensions of the forming parts are consistent with the project, and the goal of improving the accuracy of GMA-AM has achieved.