3D reconstruction of GMAW pool surface using composite sensor technology. (February 2019) - Jin, Zeshi; Li, Haichao; Li, Ran; Sun, Yunfei; Gao, Hongming
Highlights: A composite vision sensing system is proposed and used in our study. A spatial vision calibration is also proposed. A multistep predictive model is established to estimate pool tail height. The 3D surface of GMAW pool is estimated and reconstructed. Abstract: Weld pool is the most direct signal to reflect welding quality, that means measurement and reconstruction of the pool surface is one of the most urgent task in industrial robotic welding. A lot of researches have been done in this area, but the strong welding arc and the violent oscillation of weld pool affect their effectiveness. To better resolve this problem, a composite vision sensing system was proposed in our previous study, which consists of an active vision part and a passive vision part. The geometric parameters of the weld cross section and the weld pool have been successfully extracted by using this system. Based on the obtained information, the dynamic relationship between the weld speed and the bead geometric parameters is established by multistep predictive model based on neural network. By using the established model and iterative algorithm, the pool tail height is estimated in this paper. A spatial vision calibration is also proposed to calculate the real geometric parameters of the weld pool. Then the 3D surface of the weld pool is also reconstructed by the means of space curved surface fitting. Finally, the verification experiment is also conducted to verify the feasibility of this method.