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Purpose -The purpose of this paper is to analyze the characteristics of sound during gas tungsten argon welding (GTAW), which is very important to effectively monitor the welding quality in future by using the information extracted from sound. Design/methodology/approach -The hardware used in the experiment is described. Then the paper researches the influence of welding techniques (gas flow, welding speed, welding current, and arc length) on arc sound and the distribution of the welding sound field. Finally, the relation between welding power and sound are studied based on Fourier transforms and recursive least square methods. Findings -The sound pressure is affected greatly by gas flow, arc length, and current; welding sound source obeys the dipole model; the sound can be better predicted when the three orders derivative of the welding power are combined together. Originality/value -This paper provides a new insight into welding sound resource model and a detailed analysis of the influence of the welding sound caused by welding techniques.

Purpose -The control of weld penetration in gas tungsten-arc welding (GTAW) is required for fully automated systems to overcome variations in the welding process. The surface depression of weld pool, or weld pool height, has a close relationship with width of the backside bead in the fullpenetrated weld. The purpose of this paper is to inspect the pool height. Design/methodology/approach -A fast linear approach, based on shape from shading (SFS) algorithm, was employed to reconstruct a 3D shape of welding pool from a 2D image, which was obtained from a real welding pool. Then the pool height can be extracted. Furthermore, three methods were introduced to improve the above algorithm. Findings -The reconstructed pool height was in good agreement with the real height of weld pool from experiments.Research limitations/implications -The algorithm requires a uniform reflection on the pool surface. Practical implications -This method is applicable to inspect weld pool height in GTAW. It is a basis for future work on control of weld penetration. Originality/value -A faster SFS algorithm has been introduced to extract weld pool height in real-time. Moreover, the algorithm was improved to fit for extracting the surface shape of weld pool.

Arc welding process is characterized as nonlinear, time varying, and uncertain. So it is very difficult to design an effective control scheme by conventional modeling and control methods. Quality control of arc welding process is the key component in robotic welding system. This paper addresses model-free adaptive control with functional reinforce of Al alloy weld pool dynamics during pulsed gas tungsten arc welding (GTAW). This control method only needs the observed input output data and also has functional reinforce to improve the performance of the controller. The shape and size parameters for the weld pool are used to describe the weld pool geometry. The welding current is selected as the control variable, and the backside width of weld pool is selected as the controlled variable. To achieve the goal of full penetration and fine weld seam formation, a model-free adaptive controller with functional reinforce is designed for control of the maximum backside width. This controller of weld pool is independent on mathematic model. Numerical simulations confirmed that the developed control system is effective in achieving the desired fusion state.