Control of deposition height in WAAM using visual inspection of previous and current layers

Jun Xiong (), Yiyang Zhang and Yupeng Pi
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Jun Xiong: Southwest Jiaotong University
Yiyang Zhang: Southwest Jiaotong University
Yupeng Pi: Southwest Jiaotong University

Journal of Intelligent Manufacturing, 2021, vol. 32, issue 8, No 9, 2209-2217

Abstract: Abstract Wire plus arc additive manufacturing (WAAM) has been demonstrated to be a powerful technique to produce large-scale metal parts with low cost. However, techniques to achieve accurate geometry control and high process stability have not yet been perfectly developed. Although implementing vision sensing and closed-loop control can contribute to promoting the levels of process automation and stability, it is difficult to markedly improve the geometry precision of parts by only performing the current layer detection due to a large detection lag with vision-based sensors. To deal with this issue, this study proposes a novel strategy of introducing the previous layer information into the current deposition height to increase the response speed of the control system. The previous and current layer heights are monitored by a passive vision sensor. The height features are extracted by image processing algorithms mainly including edge detection, threshold division, and line fitting. Deviations in deposition height are automatically compensated via controlling the wire feed speed based on a PID controller. A helpful software interface is implemented in the Visual C++ environment to study the automatic detection and control system. In comparison to the closed-loop control using only the current layer detection, the deposition height of thin-walled parts can be excellently controlled by the proposed control system using the visual inspection of previous and current layers, significantly increasing the process stability and achieving accurate height control in WAAM.

Keywords: Wire plus arc additive manufacturing; Automatic control; Visual sensing; Previous and current layers (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-020-01634-6

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