Welded joints of dissimilar materials increase the flexibility in design and manufacturing process greatly and, hence, have been widely used in aerospace, rail transportation, and other related industries. Due to the difference in physical and chemical properties of dissimilar materials, the formed weld during laser welding is different from that of the same material welding. The geometric morphology of the formed weld is an important factor affecting the welded joints performance. Therefore, an identification method of weld seam characteristic parameters is proposed in this paper for evaluating the welding quality by image segmentation in the laser welding of low carbon steel (Q235) and stainless steel (316L). The region of interest of the weld metallograph from experimental observation is defined, converted into grayscale image and then denoised by filter. The weld is segmented by the seeded region growing method with initial seed automatic selection. The weld seam characteristic parameters including the weld area, left weld width, right weld width, and weld penetration in the laser welding of dissimilar materials are identified based on the segmented image. The obtained results are validated by the experimental measurements of weld and good agreement between them has been found. The identified weld seam characteristic parameters are adopted for assessing weld fusion status, depth-to-width ratio, and symmetry quantitatively. The results indicate that the proposed method is reasonable and feasible for the weld quality evaluation to improve the laser welding quality of dissimilar materials in practical production.
REFERENCES
1.
Z.
Sun
and J. C.
Ion
, “Laser welding of dissimilar metal combinations
,” J. Mater. Sci.
30
, 4205
–4214
(1995
). 2.
J.
Huang
, W.
Shi
, Y.
Xie
, Z.
Liang
, and J.
Zhan
, “Analysis of laser micro welding of copper-aluminum dissimilar metals and its mechanism
,” J. Appl. Math. Phys.
07
, 3192
–3200
(2019
). 3.
T.
Murakami
, K.
Nakata
, H.
Tong
, and M.
Ushio
, “Dissimilar metal joining of aluminum to steel by MIG arc brazing using flux cored wire
,” ISIJ Int.
43
, 1596
–1602
(2003
). 4.
M. S.
Khorrami
, M. A.
Mostafaei
, H.
Pouraliakbar
, and A. H.
Kokabi
, “Study on microstructure and mechanical characteristics of low-carbon steel and ferritic stainless steel joints
,” Mater. Sci. Eng., A
608
, 35
–45
(2014
). 5.
M.
Jafarzadegan
, A.
Abdollah-Zadeh
, A. H.
Feng
, T.
Saeid
, J.
Shen
, and H.
Assadi
, “Microstructure and mechanical properties of a dissimilar friction stir weld between austenitic stainless steel and low carbon steel
,” J. Mater. Sci. Technol.
29
, 367
–372
(2013
). 6.
W.
Wu
, S.
Hu
, and J.
Shen
, “Microstructure, mechanical properties and corrosion behavior of laser welded dissimilar joints between ferritic stainless steel and carbon steel
,” Mater. Des.
65
, 855
–861
(2015
). 7.
M. J.
Torkamany
, J.
Sabbaghzadeh
, and M. J.
Hamedi
, “Effect of laser welding mode on the microstructure and mechanical performance of dissimilar laser spot welds between low carbon and austenitic stainless steels
,” Mater. Des.
34
, 666
–672
(2012
). 8.
S.
Li
, G.
Chen
, S.
Katayama
, and Y.
Zhang
, “Relationship between spatter formation and dynamic molten pool during high-power deep-penetration laser welding
,” Appl. Surf. Sci.
303
, 481
–488
(2014
). 9.
S.
Li
, G.
Chen
, and C.
Zhou
, “Effects of welding parameters on weld geometry during high-power laser welding of thick plate
,” Int. J. Adv. Manuf. Technol.
79
, 177
–182
(2015
). 10.
M. M. A.
Khan
, L.
Romoli
, R.
Ishak
, M.
Fiaschi
, G.
Dini
, and M. D.
Sanctis
, “Experimental investigation on seam geometry, microstructure evolution and microhardness profile of laser welded martensitic stainless steels
,” Opt. Laser Technol.
44
, 1611
–1619
(2012
). 11.
S.
Liu
, G.
Mi
, F.
Yan
, C.
Wang
, and P.
Jiang
, “Correlation of high power laser welding parameters with real weld geometry and microstructure
,” Opt. Laser Technol.
94
, 59
–67
(2017
). 12.
Y.
Ai
, X.
Liu
, Y.
Huang
, and L.
Yu
, “The analysis of asymmetry characteristics during the fiber laser welding of dissimilar materials by numerical simulation
,” Int. J. Adv. Manuf. Technol.
119
, 3293
–3301
(2022
). 13.
M. A.
Attar
, M.
Ghoreishi
, and Z. M.
Beiranvand
, “Prediction of weld geometry, temperature contour and strain distribution in disk laser welding of dissimilar joining between copper & 304 stainless steel
,” Optik
219
, 165288
(2020
). 14.
D.
Xu
, Z.
Jiang
, L.
Wang
, and M.
Tan
, “Features extraction for structured light image of welding seam with arc and splash disturbance
,” in ICARCV 2004 8th Control, Automation, Robotics and Vision Conference
, Kunming, China, 6–9 December 2004, (IEEE, Piscataway, NJ, 2004
), Vol. 3, pp. 1559
–1563
.15.
Y.
Huang
, X.
Hua
, F.
Li
, C.
Shen
, G.
Mou
, and B.
Tang
, “Spatter feature analysis in laser welding based on motion tracking method
,” J. Manuf. Process.
55
, 220
–229
(2020
). 16.
O.
Zahran
, H.
Kasban
, M.
El-Kordy
, and F. E. A.
El-Samie
, “Automatic weld defect identification from radiographic images
,” NDT E Int.
57
, 26
–35
(2013
). 17.
R.
Miao
, Y.
Gao
, L.
Ge
, Z.
Jiang
, and J.
Zhang
, “Online defect recognition of narrow overlap weld based on two-stage recognition model combining continuous wavelet transform and convolutional neural network
,” Comput. Ind.
112
, 103115
(2019
). 18.
R.
Miao
, Z.
Shan
, Q.
Zhou
, Y.
Wu
, L.
Ge
, J.
Zhang
, and H.
Hu
, “Real-time defect identification of narrow overlap welds and application based on convolutional neural networks
,” J. Manuf. Syst.
62
, 800
–810
(2022
). 19.
V. R.
Rathod
and R. S.
Anand
, “A comparative study of different segmentation techniques for detection of flaws in NDE weld images
,” J. Nondestruct. Eval.
31
, 1
–16
(2012
). 20.
J.
Fang
and K.
Wang
, “Weld pool image segmentation of hump formation based on fuzzy C-means and Chan-Vese model
,” J. Mater. Eng. Performance
28
, 4467
–4476
(2019
). 21.
M.
Landowski
, A.
Świerczyńska
, G.
Rogalski
, and D.
Fydrych
, “Autogenous fiber laser welding of 316L austenitic and 2304 lean duplex stainless steels
,” Materials
13
, 2930
(2020
). 22.
H.
Wang
, K.
Wang
, W.
Wang
, L.
Huang
, P.
Peng
, and H.
Yu
, “Microstructure and mechanical properties of dissimilar friction stir welded type 304 austenitic stainless steel to Q235 low carbon steel
,” Mater. Charact.
155
, 109803
(2019
). 23.
Y.
Ai
, X.
Shao
, P.
Jiang
, P.
Li
, Y.
Liu
, and W.
Liu
, “Welded joints integrity analysis and optimization for fiber laser welding of dissimilar materials
,” Opt. Lasers Eng.
86
, 62
–74
(2016
). 24.
R. P.
Singh
and M. K.
Agrawal
, “Effect of welding current on the dimensions of bead in tungsten inert gas welding process
,” Mater. Today: Proc.
45
, 3235
–3239
(2021
). 25.
X.
Zhan
, J.
Zhou
, W.
Sun
, J.
Chen
, and Y.
Wei
, “Effect of external applied steady magnetic field on the morphology of laser welding joint of 4-mm 2024 aluminum alloy
,” Appl. Phys. A
123
, 106
(2017
).26.
Y.
Ai
, P.
Jiang
, X.
Shao
, C.
Wang
, P.
Li
, G.
Mi
, Y.
Liu
, and W.
Liu
, “A defect-responsive optimization method for the fiber laser butt welding of dissimilar materials
,” Mater. Des.
90
, 669
–681 (2016
).27.
J.
Zeng
, G.
Cao
, Y.
Peng
, and S.
Huang
, “A weld joint type identification method for visual sensor based on image features and SVM
,” Sensors
20
, 471
(2020
). 28.
J. B.
Santos
, D.
Celorico
, J.
Varandas
, and J.
Dias
, “The importance of the pre-processing on the echocardiographic images for the left ventricular contour extraction
,” Eur. J. Acardio-Thorac. Surg.
18
, 458
–465
(2000
).29.
30.
W.
Khan
, “Image segmentation techniques: A survey
,” J. Image Graphics
1
, 166
–170
(2013
). 31.
J.
Fan
, D. K. Y.
Yau
, A. K.
Elmagarmid
, and W. G.
Aref
, “Automatic image segmentation by integrating color-edge extraction and seeded region growing
,” IEEE Trans. Image Process.
10
, 1454
–1466
(2001
). 32.
M. M. S. J.
Preetha
, P. L.
Suresh
, and M. J.
Bosco
, “Image segmentation using seeded region growing
,” in 2012 International Conference on Computing, Electronics and Electrical Technologies
, Nagercoil, India, 21–22 March 2012 (IEEE, Piscataway, NJ, 2012
), pp. 576
–583
.33.
N.
Ikonomatakis
, K. N.
Plataniotis
, M.
Zervakis
, and A. N.
Venetsanopoulos
, “Region growing and region merging image segmentation
,” in Proceedings of 13th International Conference on Digital Signal Processing, Santorini, Greece, 2–4 July 1997
(IEEE, Piscataway, NJ, 1997), Vol. 1, pp. 299–302.34.
M.
Mostafa
, J.
Laifi
, M.
Ashari
, and Z. A.
Alrowaili
, “MATLAB image treatment of copper-steel laser welding
,” Adv. Mater. Sci. Eng.
2020, 8914841
(2020
). © 2022 Author(s). Published under an exclusive license by Laser Institute of America.
2022
Author(s)
You do not currently have access to this content.
