Abstract
In this study, a low-cost infrared sensing system based on the analysis of the surface temperature distribution is proposed for monitoring the perturbations occurring during the aluminum alloy metal inert gas (MIG) welding process. A galvanometer scanner is employed in this real-time infrared sensing system to continually reflect the infrared energy to the point infrared sensor. By controlling the scanning mirror of the galvanometer scanner rotating in a high speed, the infrared energy at different points of the welding seam and the heat-affected zone on the surface of the plate will be continually captured by the point infrared sensor. Different conditions (changes in the welding speed, welding current, and joint gap width) of the welding process have been simulated to perturb the welding process. Three representative geometric defects such as undercut, humping, and lack of fusion were produced to validate our infrared sensing system. Experimental results showed that the sensing system is useful for monitoring perturbations that arise during the welding process and identifying welding defects.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Çam G, İpekoğlu G (2016) Recent developments in joining of aluminum alloys. Int J Adv Manuf Technol. doi:10.1007/s00170-016-9861-0
Santos MC Jr, Machado AR, Sales WF, Barrozo MAS, Ezugwu EO (2016) Machining of aluminum alloys: a review. Int J Adv Manuf Technol. doi: 10.1007/s00170-016-8431-9
Trimm M (2003) An overview of nondestructive evaluation methods. J Fail Anal Prev 3(3):17–31
Lakshmi MRV, Mondal AK, Jadhav CK, Dutta BVR, Sreedhar S (2013) Overview of NDT methods applied on an aero engine turbine rotor blade. Insight Non Destr Test Cond Monit 55(9):482–486. doi:10.1784/insi.2012.55.9.482
Lhémery A, Calmon P, Lecœur-Taїbi I, Raillon R, Paradis L (2000) Modeling tools for ultrasonic inspection of welds. NDT E Int 33(7):499–513. doi:10.1016/S0963-8695(00)00021-9
Ditchburn RJ, Burke SK, Scala CM (1996) NDT of welds: state of the art. NDT E Int 29(96):111–117. doi:10.1016/0963-8695(96)00010-2
Easterling K (1992) Introduction to the physical metallurgy of welding. Butterworth Heinemann, Great Britain
Kou S (2003) Welding metallurgy. Wiley, New Jersey
Gao X, Liu Y, Lan C, Xiao Z, Chen X (2016) Laser-induced infrared characteristic analysis for evaluating joint deviation during austenitic stainless steel laser welding. Int J Adv Manuf Technol 88(5):1877–1888. doi: 10.1007/s00170-016-8892-x
Alfaro SCA, Vargas JAR, Carvalho GCD, Souza GGD (2015) Characterization of “humping” in the GTA welding process using infrared images. J Mater Process Technol 223:216–224. doi:10.1016/j.jmatprotec.2015.03.052
Vasudevan M, Chandrasekhar MN, Maduraimuthu MV, Bhaduri AK, Raj B (2013) Real-time monitoring of weld pool during GTAW using infrared thermography and analysis of infrared thermal images. Weld World 55(7–8):83–89
Doumanidis CC, Hardt DE (1991) Multivariable adaptive control of thermal properties during welding. J Dyn Syst Meas Control Trans ASME 113(1):82–92
Chandrasekhar N, Vasudevan M, Bhaduri AK, Jayakumar T (2015) Intelligent modeling for estimating weld bead width and depth of penetration from infra-red thermal images of the weld pool. J Intell Manuf 26(1):1–13. doi:10.1007/s10845-013-0762-x
Menaka M, Vasudevan M, Venkatraman B, Raj B (2005) Estimating bead width and depth of penetration during welding by infrared thermal imaging. Insight Non Destr Test Cond Monit 47(47):564–568. doi:10.1784/insi.2005.47.9.564
Ghanty P, Vasudevan M, Mukherjee DP, Pal NR, Chandrasekhar N, Maduraimuthu V, Bhaduri AK, Barat P, Raj B (2008) Artificial neural network approach for estimating weld bead width and depth of penetration from infrared thermal image of weld pool. Sci Technol Weld Join 60(2):395–401. doi:10.1179/174329308X300118
Fan H, Ravala NK, Iii HCW, Chin BA (2003) Low-cost infrared sensing system for monitoring the welding process in the presence of plate inclination angle. J Mater Process Technol 140(1–3):668–675. doi:10.1016/S0924-0136(03)00836-7
Iii HCW, Kottilingam S, Zee RH, Chin BA (2001) Infrared sensing techniques for penetration depth control of the submerged arc welding process. J Mater Process Technol 113(1–3):228–233. doi:10.1016/S0924-0136(01)00587-8
Ling KH, Fuh YK, Kuo TC, Sheng XT (2015) Effect of welding sequence of a multi-pass temper bead in gas-shielded flux-cored arc welding process: hardness, microstructure, and impact toughness analysis. Int J Adv Manuf Technol 81(5):1–14. doi:10.1007/s00170-015-7277-x
Wu S, Gao H, Zhang Z (2015) A preliminary test of a novel molten metal filler welding process. Int J Adv Manuf Technol 80(1):647–655. doi:10.1007/s00170-015-7017-2
Pal K, Bhattacharya S, Pal SK (2010) Multisensor-based monitoring of weld deposition and plate distortion for various torch angles in pulsed MIG welding. Int J Adv Manuf Technol 50(5):543–556. doi:10.1007/s00170-010-2523-8
Al-Habaibeh A, Parkin R (2003) An autonomous low-cost infrared system for the on-line monitoring of manufacturing processes using novelty detection. Int J Adv Manuf Technol 22(3):249–258. doi:10.1007/s00170-002-1467-z
Myhr OR, Kluken AO, Klokkehaug S, Fjaer HG, Grong O (1998) Modeling of microstructure evolution, residual stresses and distortions in 6082-t6 aluminum weldments. Weld J 77(7)
Missori S, Pezzuti E (2010) Microstructural and mechanical characteristics of welded joints in type 6082-t6 aluminium alloy. Weld Int 11(11):468–474. doi:10.1080/09507119709451996
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yu, P., Xu, G., Gu, X. et al. A low-cost infrared sensing system for monitoring the MIG welding process. Int J Adv Manuf Technol 92, 4031–4038 (2017). https://doi.org/10.1007/s00170-017-0515-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-017-0515-7