d)

Sensing and control during bead-on-plate welding

For the single frequency approach a control frequency in the full penetration range has to be chosen.

As an example, Figure 7 shows the results of a bead-on-plate weld on a 3 mm thick mild steel workpiece welded at a travel speed of 2 mm/s. The initial base current was set at 115 A. The control frequency is set at 50 Hz. This value is calculated by means of equation 3. During the first part of the weld the feedback system was not activated. As can be seen the current is constant. At the start of welding a partial penetration situation exists and the oscillation process has to be stabilised. This period (until t= 6s) is associated with the occurrence of a relatively high frequency. As the weld pool size increases during welding, full penetration is obtained and the oscillation frequency starts to drop (from t= 6s). Finally, severe sagging of the weld pool occurs. At t=22s the feedback system is switched on. As can be seen in the figure, the base current is reduced in order to increase the oscillation frequency of the weld pool by reducing the weld pool bottom width. The measured oscillation frequency is increasing until the control frequency is reached. The width of the penetration remains constant when the feedback system is active.

30 Time (s)

40

50

60

Figure 7: Bead-on plate weld on 3 mm thick mild steel; a) top view of the weld, b) bottom view of the weld, c) oscillation frequency as function of time, d) welding current as function of time.

a)

Sensing and control during orbital tube welding

The oscillation frequency and the current response were also measured during orbital tube welding on 2.0 mm thick stainless steel AISI 316L. The initial base current was 50 A and a control frequency of 40 Hz was selected. The feedback system was activated before welding started. An example of the results obtained is presented in Figure 8. Figure 8a shows the measured oscillation frequency as function of time. After full penetration is achieved, the oscillation frequency is maintained at the control frequency by small current adjustments (Figure 8b). The reduction in current in the final part of the weld is directly related with the accumulation of heat in the tube. Less current is required to maintain full penetration.

Inspection of the welds shows that correct penetration is achieved along the entire weld and that the overall quality is excellent, see Figure 8c.

It should be expected that the welding position, in the case of orbital welding, has an influence on the weld pool behaviour. However, it appears that the influence of gravity on the oscillation behaviour is limited and therefore can be neglected [2].

Oscillation frequency (Hz)

c)

0+

Figure 8) Orbital weld on 2mm stainless steel; a) oscillation frequency versus time, b) welding current versus time, c) penetration appearance.

CONCLUSIONS

On the basis of the results of the research carried out in the field of penetration sensing by means of weld pool oscillation monitoring the following conclusions can be drawn:

1. Partially and fully penetrated weld pools oscillate in different oscillation modes.

2. The oscillation frequency depends on the mode of oscillation, weld pool size and physical properties of the liquid metal.

3. The oscillation frequency drops when full penetration is achieved. This change in oscillation frequency can be used for in-process control of weld pool penetration.

4. The use of sensing in combination with feedback results in excellent weld quality.

ACKNOWLEDGEMENTS

The authors wish to express their gratitude to Y.H. Xiao, A.J.R. Aendenroomer and B. Hu for their contributions and to W.A.J. Brabander, F.J.A.M. Bosman for their technical assistance.

REFERENCES

1. Madigan R.B. and R.J. Renwick; 'Computer based control of full penetration GTA welds using pool oscillation sensing', Proc. 1st Int. Conf. On Computer Technology in Welding, London, UK, 1986, 165-174.

2. Xiao Y.H. and G. den Ouden; 'A study of GTA weld pool oscillation', Welding Journal, Vol. 69, No.8, 1990, 289s-293s.

3. Sorensen C.D. and T.W. Eagar; Modeling of oscillation in partial penetration weld pools', Journal of Dynamic Systems, Measurement and Control, 1990, 112, 469-474.

4. Xiao Y.H. and G. den Ouden; Weld pool oscillation during GTA welding of mild steel', Welding Journal, Vol 72, No.8, 1993, 428s-434s.

5. Bicknell A., J.S. Smith and J. Lucas; 'Arc voltage sensor for monitoring of penetration in TIG welds', IEE Proc. Sci. Meas. Technol. Vol 141, No. 6, 1994, 513-520.

6. Anderson K., G.E. Coock, R.J. Barnett and A.M. Strauss; 'Synchronous weld pool monitoring and control', IEEE transactions on industry applications Vol. 33, No. 2, March/April 1997, 464-471.

7. Aendenroomer A.J.R. and G. den Ouden; 'Weld pool oscillation as a tool for penetration sensing during pulsed GTA welding', Welding Journal, Vol 77, 5, 1998, 181s-187s.

8. Hu B. and G. den Ouden; Weld penetration sensing and control during GTA welding using weld pool oscillation, in Proceeding Int. Conf. on trends in welding research, Pine Mountain, Georgia, USA, Juni 1998, 1125-1130.

9. Rehfeldt D. and T. Polte; 'Arc sensor as a quality assurance element for uniform full penetration welding', Schweissen und Schneiden, Vol. 52, No. 10, 2000, E228-E231.

10. H. Wohlfahrt, K. Thomas and S. Wiesner; 'Welding voltage measurements during TIG and MIG welding with the objective of controlling the weld penetration', Schweissen und Schneiden, Vol. 53, No. 2, 2001, E29-E31.

11. Maruo H. and Y. Hirata; 'Natural frequency and oscillation modes of weld pools', Welding International, Vol. 7, No. 8, 1993, 614-619.

REAL-TIME MOLTEN POOL AREA EXTRACTION FOR CONTROL OF GAS

TUNGSTEN ARC WELDING

Y. Z. Wang, Z. Jandric and R. Kovacevic"

ABSTRACT

This paper presents a real-time molten pool area extraction method for the control of gas tungsten arc welding (GTAW) with a wire filler in the hybrid rapid prototyping and tooling (RP&T) technique based on welding and CNC milling. The molten pool shape and size were strongly influenced by the two-dimensional geometry of the built part. A coaxial machine vision unit is used to acquire images of molten pool and its surrounding area through the torch. After image processing, the boundary of the molten pool is extracted. Because the molten pool is partially hidden by the tungsten electrode, its boundary is incomplete. The molten pool area is selected as the feedback to the closed-loop control of the GTAW process. In order to calculate the area of the molten pool with an incomplete boundary, a neural network is used. By changing welding parameters, the neural network is trained for different sizes of molten pools. The testing of the neural network is performed by another group of molten pool images.

INTRODUCTION

Nowadays, industry is under constant and growing pressure for shortening the time-to-market lead time. Rapid prototyping (RP) techniques have been developed for fulfilling this demand. For many years, rapid prototyping techniques have been used almost exclusively on materials such polymers, waxes, or paper (Ref. 1). The rapid prototyped parts had limited dimensions, and they had a tendency to distort due to shrinkage.

Three-dimensional welding has the ability to rapidly produce strong, fully dense metallic parts in the form of layers (Refs. 2, 3). To increase the surface quality and accuracy of the metallic parts made by the 3D welding, a promising hybrid rapid prototyping and tooling (RP&T) technique based on gas tungsten arc welding (GTAW) and CNC milling has been under development at the Research Center for Advanced Manufacturing (RCAM) at Southern Methodist University, Dallas, TX (Ref. 4). This hybrid process allows the fabrication of metallic parts with high dimensional accuracy and with complex external and internal geometrical features.

In the hybrid RP&T technique, the GTAW process with a wire filler provides depositing materials and energy to fuse the added material. For the needs of RP&T, the welding process is required to provide lower heat input and lower bead penetration that is exactly opposite to the conventional welding process. In order to generate uniform and fairly flat beads and layers, a metal deposition rate and molten pool size should be invariant of the alternations of the welding

Research Center for Advanced Manufacturing, Southern Methodist University 1500 International Pkwy, Suite 100, Richardson TX 75081

corresponding author.

Tel: 1-214-768-4865, Fax: 1-214-768-0812, Email: kovacevi@seas.smu.edu

conditions. The geometry of the molten pool can provide abundant, accurate and instantaneous information about the welding process. Hence, closed-loop control of the welding process, with the information of the molten pool size as a feedback, is a necessity.

Although several indirect approaches, such as monitoring the pool oscillation, the ultrasonic technique, infrared sensing, and radiography, have been proposed to sense the geometry of the molten pool, machine vision, being non-intrusive, seems to be the most promising technique for obtaining the clear geometry of a molten pool.

Machine vision systems have been extensively used for the molten pool sensing and seam tracking for more than two decades, mostly with the idea to simulate the eye sensing and process actuation of experienced human welders. Previous research works for sensing the molten pool in GTAW with machine vision was conducted without a wire filler.

In the GTAW process with a wire filler, it is necessary to ensure that the wire is always fed in front of the moving arc. In order to avoid blocking the optical path between the molten pool and the CCD camera by the wire filler, a coaxial machine vision unit, developed by Richardson et al. (Ref. 5), is used in this paper. The lens of a CCD camera is coaxially mounted with the electrode. The electrode tip is used to block the bright core of the arc light from the overpowering exposure on the CCD target. After the image of the molten pool is captured, the Laplacian operator is used to detect the edges. Then, the image was segmented into a binary one with an adaptive threshold. The boundary of the molten pool is extracted from the binary image.

The molten pool size and shape in the hybrid RP&T are strongly influenced by the twodimensional geometrical features of the part to be built. Fig. 1 demonstrates the molten pools at the flat surface (point 6), the edge (point 5), and the corners with different angles (points 1 to 4), while keeping the welding parameters constant. This paper is concentrated on the acquisition and processing of the shape of the molten pool at the flat surface (point 6).

Figure 1. The shapes of the molten pool as a function of 2D geometrical features of substrate

Fig. 2 illustrates the schematic presentation of the hybrid RP&T machine, consisting of a central controller, a CNC milling machine, a GTAW unit, and a coaxial machine vision unit. The central controller acquires the measured data and controls the welding current, wire feeding speed, and