Abstract
A novel porosity detection technique from the voltage and current transients is introduced in this paper. An online weld monitoring that detects the porosity at an earlier stage is much demanding in the industry due to their adverse effects on structural integrity. In this research work, control chart and probability density distribution have been employed as tools to detect arc instability and weld porosity. The results showed that the pattern of probability density distribution changes for the defect and defect-free welds significantly. The mean and standard deviation control charts plotted with voltage clearly distinguished the quality of the weld based on sample points spread within or outside the control limits. For minute internal porosities, the sample points at the corresponding region in the standard deviation control chart were outside the limits whereas it is well within the control limits in the mean control chart. Inspector can predict the presence and near location of porosity using these tools by simple mathematical calculations easily and instantly. The results proved that the developed approach is successful and promising for the weld inspection.
Similar content being viewed by others
References
Kaçar R, Kökemli K (2005) Effect of controlled atmosphere on the mig-mag arc weldment properties. Mater Des 26(6):508–516. https://doi.org/10.1016/j.matdes.2004.07.027
Bai Y, Gao HM, Wu L, Ma ZH, Cao N (2010) Influence of plasma-MIG welding parameters on aluminum weld porosity by orthogonal test. Trans Nonferrous Metals Soc China (English Ed.) 20:1392–1396. https://doi.org/10.1016/S1003-6326(09)60310-1
Campana G, Ascari A, Fortunato A, Tani G (2009) Hybrid laser-MIG welding of aluminum alloys: the influence of shielding gases. Appl Surf Sci 255(10):5588–5590. https://doi.org/10.1016/j.apsusc.2008.07.169
Murugan N, Parmar R (1994) Effects of MIG process parameters on the geometry of the bead in the automatic surfacing of stainless steel. J Mater Process Technol 41(4):381–398. https://doi.org/10.1016/0924-0136(94)90003-5
Mourad AHI, Khourshid A, Sharef T (2012) Gas tungsten arc and laser beam welding processes effects on duplex stainless steel 2205 properties. Mater Sci Eng A 549:105–113. https://doi.org/10.1016/j.msea.2012.04.012
Bouzid AH, Mourad AHI, El Domiaty A (2015) Impact of material behaviour modeling on the residual contact pressure in hydraulically expanded tube-to-tubesheet joints. In: Proc. ICPVT-14, Shanghai, China, pp. 1–10
Bouzid AH, Mourad AHI, El Domiaty A (2016) Influence of Bauschinger effect on the residual contact pressure of hydraulically expanded tube-to-tubesheet joints. Int J Press Vessel Pip 146:1–10. https://doi.org/10.1016/j.ijpvp.2016.07.002.
Praveen P, Kang MJ, Yarlagadda KDVP (2006) Characterization of dynamic behaviour of short circuit in pulsed gas metal arc welding of aluminum. J Achiev Mater Manuf Eng 14:75–82
Norrish J, Cuiuri D (2014) The controlled short circuit GMAW process: a tutorial. J Manuf Process 16(1):86–92. https://doi.org/10.1016/j.jmapro.2013.08.006
Rehfeldt D, Polte T (1999) Three systems for process monitoring, process analysis and quality determination in arc welding. In: Int. Conf. Join. Mater., Denmark, pp. 277–283
Rehfeldt D, Rehfeldt MD (2015) Statistical evaluation of GMAW process disturbances with signature analysis through ANALYSATOR HANNOVER. J Chem Pharm Sci (2015):274–279
Wu CS, Polte T, Rehfeldt D (2001) A fuzzy logic system for process monitoring and quality evaluation in GMAW. Weld J 80(2):33s–38s
Sumesh A, Rameshkumar K, Raja A, Mohandas K, Santhakumari A, Shyambabu R (2017) Establishing correlation between current and voltage signatures of the arc and weld defects in GMAW process. Arab J Sci Eng 42(11):4649–4665. https://doi.org/10.1007/s13369-017-2609-9
Wei E, Farson D, Richardson R, Ludewig H (2001) Detection of weld surface porosity by statistical analysis of arc current in gas metal arc welding. J Manuf Process 3(1):50–59. https://doi.org/10.1016/S1526-6125(01)70033-3
Wu CS, Gao JQ, Hu JK (2007) Real-time sensing and monitoring in robotic gas metal arc welding. Meas Sci Technol 18(1):303–310. https://doi.org/10.1088/0957-0233/18/1/037
Luksa K, Rymarski Z (2006) Collection of arc welding process data. J Achiev Mater Manuf Eng 17:377–380
Wu CS, Polte T, Rehfeldt D (2000) Gas metal arc welding process monitoring and quality evaluation using neural networks. Sci Technol Weld Join 5(5):324–328. https://doi.org/10.1179/136217100101538380
Wu CS, Hu QX, Sun JS, Polte T, Rehfeldt D (2004) Intelligent monitoring and recognition of the short-circuiting gas-metal arc welding process. Proc Inst Mech Eng B J Eng Manuf 218(9):1145–1151. https://doi.org/10.1243/0954405041897121
Sumesh A, Rameshkumar K, Mohandas K, Babu RS (2015) Use of machine learning algorithms for weld quality monitoring using acoustic signature. Procedia Comput Sci 50:316–322. https://doi.org/10.1016/j.procs.2015.04.042
Sumesh A, Thekkuden DT, Nair BB, Rameshkumar K, Mohandas K (2015) Acoustic signature based weld quality monitoring for SMAW process using data mining algorithms. Appl Mech Mater 813–814:1104–1113. https://doi.org/10.4028/www.scientific.net/AMM.813-814.1104
Wu D, Chen H, He Y, Song S, Lin T, Chen S (2016) A prediction model for keyhole geometry and acoustic signatures during variable polarity plasma arc welding based on extreme learning machine. Sens Rev 36(3):257–266. https://doi.org/10.1108/SR-01-2016-0009
Zhiyong L, Bao W, Jingbin D (2009) Detection of GTA welding quality and disturbance factors with spectral signal of arc light. J Mater Process Technol 209(10):4867–4873. https://doi.org/10.1016/j.jmatprotec.2009.01.010
Alfaro SCA, Mendonça D d S, Matos MS (2006) Emission spectrometry evaluation in arc welding monitoring system. J Mater Process Technol 179(1-3):219–224. https://doi.org/10.1016/j.jmatprotec.2006.03.088
Rehfeldt D, Schmitz T (1997) Process monitoring and quality assurance for electric welding. Weld Surf Rev 8:187–199
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Thekkuden, D.T., Santhakumari, A., Sumesh, A. et al. Instant detection of porosity in gas metal arc welding by using probability density distribution and control chart. Int J Adv Manuf Technol 95, 4583–4606 (2018). https://doi.org/10.1007/s00170-017-1484-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-017-1484-6