Abstract
Gas metal arc (GMA) additive manufacturing (AM) is one of the significant wire and arc AM processes with the ability to produce large-scale metal parts in a layer by layer fashion. Despite this fact, techniques to realize process sensing and geometry control have not been perfectly developed. This study aims at molten pool width control in GMA AM using a passive vision sensing technique. A virtual binocular vision sensing system consisting of a biprism and a camera is designed to monitor the molten pool geometry. The molten pool width in a captured image pair is extracted by a series of procedures, such as sensor calibration, image pair rectification, disparity calculation, and width reconstruction. A verification test is conducted and reveals that the detection error of the sensing system is less than 3%. To keep consistent layer width in each layer, the deviation of the molten pool width is compensated by designing a fuzzy intelligent controller to adjust the arc current in real time. The effectiveness of the controller is evaluated via the deposition of thin-walled parts. The results indicate that the consistency of the molten pool width in GMA AM can be improved when employing the fuzzy controller.
Published Version
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