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TECHNICAL PAPERS

Adaptive Nontransferred Plasma Charge Sensor and Its Applications

[+] Author and Article Information
Wei Lu

Department of Electrical and Computer Engineering and Center for Manufacturing, University of Kentucky, Lexington, KY 40506

Y. M. Zhang

Department of Electrical and Computer Engineering and Center for Manufacturing, University of Kentucky, Lexington, KY 40506ymzhang@engr.uky.edu

John Emmerson

 Mangatech Limited Partnership, East Granby, CT

J. Manuf. Sci. Eng 129(1), 180-189 (Jun 28, 2006) (10 pages) doi:10.1115/1.2401627 History: Received May 31, 2005; Revised June 28, 2006

Practical welding control systems require durable/compact sensors to sense the welding process and appropriate control algorithms to produce smooth welds. A novel arc welding sensor, referred to as nontransferred plasma charge sensor, which requires no additional attachment to the torch, has been proved to be reliable for weld pool surface sensing. Aiming at eliminating the effect of manufacturing conditions on the sensor performance, this paper proposes two simple yet effective methods. Specifically, reference signals are sampled either from the bottom or the top surface of the work-piece and used to define relative signals, which can measure the depth of the weld pool with better accuracy. Using improved sensing methods, two groups of welding control experiments, keyhole plasma arc welding and all-position pipe welding, have been conducted, and the effectiveness of the developed sensing/control systems in producing quality welds under various conditions is verified.

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Copyright © 2007 by American Society of Mechanical Engineers
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Figures

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Figure 1

Arc behavior and weld pool surface. (a) Influence of weld pool deformation on arc behavior. (b) Ideal behavior.

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Figure 2

Nontransferred plasma charge sensor principle

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Figure 3

Monitoring of weld pool using bottom surface as reference. (a) Reference. (b) Distance to the reference.

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Figure 4

Possible control schemes for keyhole welding using bottom surface as reference. (a) Adjusting CONP. (b) Adjusting travel speed.

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Figure 5

Monitoring of weld pool using top surface as reference. (a) Reference. (b) Distance to the reference.

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Figure 6

Keyhole welding experimental result in tracking 0.3V setpoint. (a) Output. (b) Input. (c) Front side. (d) Back side.

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Figure 7

Keyhole welding experimental result in tracking 0.3V setpoint with current disturbance. (a) Output. (b) Input. (c) Front side. (d) Back side.

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Figure 8

Keyhole welding experimental result in tracking 0.3V setpoint with standoff disturbance. (a) Output. (b) Input. (c) Front side. (d) Back side.

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Figure 9

Illustration of forces on weld pool during all-position pipe welding

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Figure 10

Pipe welding system used

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Figure 11

Experimental result of interval model algorithm controlled pipe welding: bead-on-plate. (a) Output. (b) Input. (c)α2. (d)b1. (e) Welded pipe.

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Figure 12

Experimental result of interval model algorithm controlled pipe welding: butt-joint. (a) Output/Input. (b)α2∕b1. (c) Welded pipe.

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