The main challenges in modern design of automobile bodies are reduction in weight and maximization of the structural stiffness and passive safety. The “tailored blank” has contributed to achieving a significant weight reduction which is single flat sheets joined by laser welding into the desired configuration without filler wire. Production of laser beam welded tailored blanks requires high speed, high precision and high quality. The welding robots that follow a preprogrammed path are often not able to guarantee a sufficient weld seam quality. Therefore, a seam tracking system is used to improve the reliability of the seam quality prediction. This paper describes the development of the seam tracking system for laser beam welding of tailored blanks. The system consists of DSP based vision camera and stripe-type laser diode. The total system is assembled into a compact module which can be attached ahead of welding torch. The images taken by the camera are analyzed using image processing algorithms. The image processing algorithms for extracting the feature points of weld seam are discussed depending on the characteristics of laser beam welding of tailored blanks. The accuracy of the industrial robots during the laser welding process was guaranteed by the compensation method A prototype sensor system has been developed and experimental results show its effectiveness and good performance.

1.
Reichert
C.
(
1998
)
Pre-and post-weld inspection using laser vision
.
The International Society for Optical Engineering
,
San Antonio, USA
,
3396
:
244
254
.
2.
Shibata
N
,
Hirai
A
,
Takano
Y
, et al (
1999
)
Development of Groove Recognition Algorithm with Vision sensor
.
Welding International.
13
(
10
),
9
17
.
3.
Sicard
P.
(
1989
)
Joint recognition and tracking for robotic arc welding
.
Systems, Man and Cybernetics.
19
(
4
),
714
728
.
4.
Haug
K.
,
Pritschow
G.
(
1998
)
Robust laser stripe sensor for the automated weld seam tracking in the shipbuilding industry
.
IECON’98-Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society
,
Aachen (Germany
).
2
,
1236
1241
.
5.
Jae
S. K.
,
Young
T. S.
,
Hyung
S.C.
(
1996
)
A robust method for vision-based seam tracking in robotic arc welding
.
Mechatronics.
6
(
2
),
141
163
.
6.
Hsing
C. K.
,
Li
J.W.
(
2000
)
An image tracking system for welded seams using fuzzy logic
.
Journal of Material Processing Technology.
120
(
1
),
169
185
.
7.
Ge
J. G.
,
Zhu
Z. Q.
(
2005
)
A vision-based algorithm for seam detection in a PAW process for large-diameter stainless steel pipes
.
International journal of advanced manufacturing technology.
26
(
10
),
1006
1011
.
8.
Xu
D.
,
Jiang
Z.M.
,
Wang
L.K.
. (
2004
)
Features extraction for structured light image of welding seam with arc and splash disturbance
.
The eighth international conference on control, automation, robotics, and vision (ICRACV 2004
).
Kunming, China
, December,
1559
1563
.
9.
Shen
H.Y.
,
Lin
T.
,
Chen
S.B.
(
2007
)
A study on vision-based real-time seam tracking in robotic arc welding
.
Robot. Weld., Intellige. & Automation, LNCIS
362
,
311
318
.
10.
Wlese
D.R.
. (
1989
)
Laser triangulation sensors: A good choice for high speed inspection
.
I&CS Control Technol. Eng. Mngmt.
62
(
9
),
27
29
.
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