Weld penetration sensing and control with a weld-face sensor are among the most relevant research issues in automated welding. Previous studies showed that the geometry of the weld pool contains accurate, instantaneous information about the weld penetration. In this study, the weld pool is measured in real-time to provide the feedback of the weld penetration, and the welding current is selected as the control variable. Analyses reveal that the influence of mandatory variations in welding conditions on the process dynamics can be described by an interval model that has bounded parameter intervals. A robust control algorithm with guaranteed closed-loop stability is used to overcome the interval uncertainty in the process dynamics. Dynamic experiments are performed using different welding conditions and varied welding parameters. From the experimental data the bounded parameter intervals are identified for the model of the process being controlled. Closed-loop control experiments are done under different perturbations. Experimentation shows that the variations encountered in practical welding can be overcome by the developed control system. In addition to penetration control, this work provides an example for developing robust manufacturing process control systems based on objective quantitative descriptions of the process uncertainty.

Issue Section:
Research Papers
Topics:
Robust control, Welding, Control systems, Dynamics (Mechanics), Uncertainty, Algorithms, Feedback, Geometry, Manufacturing, Sensors, Stability
1.
Mills
K. C.
, and
Keene
B. J.
,
1990
, “
Factors Affecting Variable Weld Penetration
,”
International Materials Reviews
, Vol.
35
, No.
4
, pp.
185
–
216
.
2.
Zhang
Y. M.
,
Kovacevic
R.
, and
Wu
L.
,
1996
, “
Dynamic Analysis and Identification of Gas Tungsten Arc Welding Process for Full Penetration Control
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
118
, No.
1
, pp.
123
–
136
.
3.
Renwick
R. J.
, and
Richardson
R. W.
,
1983
, “
Experimental Investigation of GTA Weld Pool Oscillations
,”
Welding Journal
, Vol.
62
, No.
2
, pp.
29s–35s
29s–35s
.
4.
Zacksenhouse
M.
, and
Hardt
D. E.
,
1984
, “
Weld Pool Impedance Identification for Size Measurement and Control
,”
ASME Journal of Dynamic Systems, Measurement, and Control
, Vol.
105
, No.
3
, pp.
179
–
184
.
5.
Xiao
Y. H.
, and
Ouden
G. Den
,
1990
, “
A Study of GTA Weld Pool Oscillation
,”
Welding Journal
, Vol.
69
, No.
8
, pp.
298s–293s
298s–293s
.
6.
Xiao
Y. H.
, and
Ouden
G. den
,
1993
, “
Weld Pool Oscillation During GTA Welding of Mild Steel
,”
Welding Journal
, Vol.
72
, No.
8
, pp.
428s–434s
428s–434s
.
7.
Hardt
D. E.
, and
Katz
J. M.
,
1984
, “
Ultrasonic Measurement of Weld Penetration
,”
Welding Journal
, Vol.
63
, No.
9
, pp.
273s–281s
273s–281s
.
8.
Carlson
N. M.
, and
Johnson
J. A.
,
1988
, “
Ultrasonic Sensing of Weld Pool Penetration
,”
Welding Journal
, Vol.
67
, No.
11
, pp.
239s–246s
239s–246s
.
9.
Carlson
N. M.
, et al.,
1992
, “
Ultrasonic NDT Methods for Weld Sensing
,”
Material Evaluation
, Vol.
50
, No.
11
, pp.
1338
–
1343
.
10.
Yang, J., et al., 1994, “Ultrasonic Weld Penetration Depth Sensing with a Laser Phased Array,” Proceedings of 1994 ASME International Mechanical Engineering Congress, PED-Vol. 68-1, Manufacturing Science and Engineering, pp. 245–254, Nov. 6–11, Chicago, IL.
11.
Chen
W.
, and
Chin
B. A.
,
1990
, “
Monitoring Joint Penetration Using Infrared Sensing Techniques
,”
Welding Journal
, Vol.
69
, No.
4
, pp.
181s–185s
181s–185s
.
12.
Banerjee
P.
, et al.,
1995
, “
Infrared Sensing for On-line Weld Shape Monitoring and Control
,”
ASME JOURNAL OF ENGINEERING FOR INDUSTRY
, Vol.
117
, pp.
323
–
330
.
13.
Lin, M. L., and Eagar, T. W., 1984, “Influence of Surface Depression and Convection on Arc Weld Pool Geometry,” Transport Phenomena in Materials Processing, ASME, New York, N.Y. pp. 63–69.
14.
Rokhlin
S. I.
, and
Guu
A. C.
,
1993
, “
A Study of Arc Force, Pool Depression, and Weld Penetration During Gas Tungsten Arc Welding
,”
Welding Journal
, Vol.
72
, No.
8
, pp.
381s–390s
381s–390s
.
15.
Zhang
Y. M.
,
Cao
Z. N.
, and
Kovacevic
R.
,
1996
, “
Numerical Analysis of Fully Penetrated Weld Pools in GTA Welding
,”
Proc. Instn. Mech. Engrs., Part C: Journal of Mechanical Engineering Science
, Vol.
210
, No.
2
, pp.
187
–
195
.
16.
Zhang
Y. M.
, et al.,
1993
, “
Determining Joint Penetration in GTAW with Vision Sensing of Weld-Face Geometry
,”
Welding Journal
, Vol.
72
, No.
10
, pp.
463s–469s
463s–469s
.
17.
Zhang
Y. M.
,
Kovacevic
R.
, and
Li
L.
,
1996
, “
Adaptive Control of Full Penetration GTA Welding
,”
IEEE Transactions on Control Systems Technology
, Vol.
4
, No.
4
, pp.
394
–
403
.
18.
Kovacevic
R.
,
Zhang
Y. M.
, and
Li
L.
,
1996
, “
Monitoring of Weld Penetration Based on Weld Pool Appearance
,”
Welding Journal
, Vol.
75
, No.
10
, pp.
317s–329s
317s–329s
.
19.
Zhang
Y. M.
,
Li
L.
, and
Kovacevic
R.
,
1997
, “
Dynamic Estimation of Full Penetration Using Geometry of Adjacent Weld Pools
,”
ASME JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING
, Vol.
119
, No.
4
, pp.
631
–
643
.
20.
Shirali
A. A.
, and
Mills
K. C.
,
1993
, “
The Effect of Welding Parameters on Penetration in GTA Welds
,”
Welding Journal
, Vol.
72
, No.
7
, pp.
347s–353s
347s–353s
.
21.
Cao
Z. N.
,
Zhang
Y. M.
, and
Kovacevic
R.
,
1998
, “
Numerical Transition Analysis of GTA Weld Pools
,”
ASME Journal Of Manufacturing Science And Engineering
, Vol.
120
, No.
1
, pp.
173
–
178
.
22.
Dahleh
M.
,
Tesi
A.
, and
Vicino
A.
,
1993
, “
An Overview of Extreme Properties for Robust Control of Interval Plants
,”
Automatica
, Vol.
29
, pp.
707
–
721
.
23.
Doumanidis
C. C.
, and
Hardt
D. E.
,
1990
, “
Simultaneous In-process Control of Heat-affected Zone and Cooling Rate During Arc Welding
,”
Welding Journal
, Vol.
69
, No.
5
, pp.
186s–196s
186s–196s
.
24.
Henderson
D. E.
,
Kokotovic
P. V.
,
Schiano
J. L.
, and
Rhode
D. S.
,
1993
, “
Adaptive Control of an Arc Welding Process
,”
IEEE Control Systems Magazine
, Vol.
13
, No.
1
, pp.
49
–
53
.
25.
Nishar
D.
,
Schiano
J. L.
,
Perkins
W.
, and
Weber
R.
,
1994
, “
Adaptive Control of Temperature in Arc Welding
,”
IEEE Control Systems Magazine
, Vol.
14
, No.
4
, pp.
4
–
12
.
26.
Jayasuriya
A.
, “
A Frequency Domain Design for Robust Performance Under Parametric, Unstructured, or Mixed Uncertainties
,”
ASME Journal of Dynamic Systems, Measurement, and Control
, Vol.
115
, pp.
439
–
351
, 50th Anniversary Issue, June
1993
.
27.
Smith, R. S., and Dahleh, M., The Modeling of Uncertainty in Control Systems, Lecture Notes in Control and Information Sciences, Vol. 192, Springer-Verlag, 1993.
28.
Barmish
B. R.
,
1989
, “
A Generalization of Kharitonov’s Four Polynomial Concept for Robust Stability Problems with Linearly Development Coefficient Perturbations
,”
IEEE Transactions on Automatic Control
, Vol.
34
, pp.
157
–
165
.
29.
Abdallah
C.
, et al.,
1995
, “
Controller Synthesis for a Class of Interval Plants
,”
Automatica
, Vol.
31
, pp.
341
–
343
.
30.
Olbrot
A. W.
, and
Nikodem
M.
,
1994
, “
Robust Stabilization: Some Extensions of the Gain Margin Maximization Problem
,”
IEEE Transactions on Automatic Control
, Vol.
39
, pp.
652
–
657
.
31.
Chapellat
H.
,
Dahlehand
M.
, and
Bhattacharyya
S. P.
,
1990
, “
Robust Stability Under Structured and Unstructured Perturbations
,”
IEEE Transactions on Automatic Control
, Vol.
35
, pp.
1100
–
1108
.
32.
Zhang
Y. M.
, and
Kovacevic
R.
,
1997
, “
Robust Control of Interval Plants: A Time Domain Method
,”
IEE Proceedings, Part D: Control Theory and Applications
, Vol.
114
, No.
4
, pp.
347
–
353
.
33.
Cheung
M. F.
,
Yurkovich
S.
, and
Passino
K.
,
1993
, “
An Optimal Volume Ellipsoid Algorithm for Parameter Set Estimation
,”
IEEE Transactions on Automatic Control
, Vol.
38
, No.
8
, pp.
1292
–
1296
.
34.
Hoffman
T.
,
1991
, “
Real-time Imaging for Process Control
,”
Advanced Material & Processes
, Vol.
140
, No.
3
, pp.
37
–
43
.
This content is only available via PDF.
Copyright © 1999
 by The American Society of Mechanical Engineers
You do not currently have access to this content.