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POSSIBLE APPLICATIONS

In the following the possible areas of application of the system are presented. They represent the current status of the requirement specification for this research project and were determined in cooperation with experienced welders.

Welding preparation

The first application possibility is the use during welding preparation. Constructional details can be displayed, e.g. the material type, desired values of the welding power supply or the desired welding seam.

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Figure 7: Possible insertions: welding seam and welding parameters

Welding Process

During the welding process an online quality control is possible utilizing the parameters extracted from the image data, e.g. the measurement of the welding seam geometry. This also allows an online adaptation of the welding parameters when welding long seams with changes in the work piece geometry.

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Figure 8: Possible insertions: work piece geometry, welding seam, splashes, wire feed, height of the arc, welding current and welding voltage

Quality control

The system can also be used for quality control. At present this is done via radiometric examination after the welding process, which is very complex and expensive. Additionally this method does not allow any conclusions on occurrences during the welding process.

With the new system during safety-relevant welds the images can be stored together with relevant welding parameters, which can be easily assigned to each individual picture [1], [2]. The example shows splashes caused by a to high welding current.

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Figure 9: a. Image of the welding process; b. Synchronized and simultaneously measured electrical welding parameters current and voltage including the time of the image recording

Education

A further possible application is the use in education of welders. By using of a second headmounted display, teacher and trainee can observe the same welding process. The influence of changing welding parameters on the weld quality can be directly examined.

SUMMARY

The system described in this paper combines a conventional welding helmet with a headmounted display and two HDRC cameras. The welding scene is observed with the cameras. A portable computer provides further enhancement of the image quality and displays the images in real time in the head-mounted display. The welder has a detailed view on the welding pool, welding seam and his environment. By methods of virtual and augmented reality additional information (e.g. welding parameters or constructional details) can be inserted depending upon the application. The system can be used for getting information about the welding task before the beginning of the welding process, for the observation of the welding process including online quality control, for quality control after the welding process and for education.

CONCLUSION

By the visual observation of the welding process in combination with the representation of relevant welding parameters the welder receives a completely new status of information and is able to do his work much more precisely. Thus the simplification of manual welding and an improvement of the welding result are achieved, leading to a better and more constant quality and therefore to a reduction of the inspection expenditure in quality control

ACKNOWLEDGEMENT

The presented research project is supported by the German Federal Ministry for Education and Research (bmb+f) under 01IRA07A. This research project is executed in cooperation with

research institutes: Institute of Automation, University of Bremen, Germany; Institute of Industrial Engineering and Ergonomics, RWTH Aachen, Germany

a shipbuilder: Lürssen Yachts - Super Yachts, Sail and Motor Boats, Bremen, Germany

a manufacturer of welding supplies and devices: EWM HIGHTEC Welding GmbH, Mündersbach, Germany

a manufacturer of autodarkening welding masks: Optrel AG, Wattwil, Switzerland

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REFERENCES

Nordbruch, S.; Tschirner, P.; Gräser, A. 2000. Visual Online Monitoring of PGMAW
without a Lighting Unit. International Sheet Metal Welding Conference IX, 18.-20.
October 2000, Detroit, Michigan, USA. Paper Nr. 4-4

Nordbruch, S.; Tschirner, P.; Gräser, A. 2000. Visual Online Optimization of Pulse
Gas Metal Arc Welding with a HDRC-Camera without a Lighting Unit. UKACC In-
ternational Conference Control 2000. 4.-7. September 2000, University of Cambridge,
UK. Paper Nr. 190

Neycenssac, F.; 1993. Contrast Enhancement Using the Laplacian-of-a-Gaussian-
Filter. Computer Vision, Graphics, and Image Processing, No. 55, pp. 447-463
Tschirner, P.. 1999. Visuelle Analyse von HDRC-Kamerabildern des Werkstoffüber-
gangs des MSG-Schweißprozesses. Diploma Thesis, Institute of Automation, Univer-
sity of Bremen, Germany

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