Abstract
Detection of severe defects such as porosity underneath the weld bead during the welding process is vital during installation of a gas pipeline network because such defects might lead to fatigue crack. In this study, the work associated with detection of porosity through analysis of the acquired arc sound is presented. Air-borne acoustic signal was acquired during the metal inert gas welding process on API 5L X70 gas pipeline steel. Then, the acquired signal was analyzed using Hilbert Huang transform (HHT), which uses empirical mode decomposition for the purpose of filtering unrelated-to-damage signal components, and Hilbert spectral analysis to obtain the energy-frequency-distance plot. Results showed a significant energy amplitude pattern at the region where both surface- and subsurface-pores existed. Thus, the application of HHT analysis to the acquired arc sound signal has significantly assisted in identifying hidden information that is related to the existence of defects. This finding would enhance the development of an online welding defect detection system during the welding process.
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Aljaroudi A, Khan F, Akinturk A, Haddara M, Thodi P (2015) Risk assessment of offshore crude oil pipeline failure. J Loss Prev Process Ind 37:101–109. doi:10.1016/j.jlp.2015.07.004
Asl HM, Vatani A (2013) Numerical analysis of the burn-through at in-service welding of 316 stainless steel pipeline. Int J Press Vessel Pip 105–106:49–59. doi:10.1016/j.ijpvp.2013.03.002
Jha AK, Manwatkar SK, Narayanan PR, Pant B, Sharma SC, George KM (2013) Failure analysis of a high strength low alloy 0.15C–1.25Cr–1Mo–0.25V steel pressure vessel. Case Stud Eng Fail Anal 1(4):265–272. doi:10.1016/j.csefa.2013.09.004
Hval M, Lamvik T (2015) Parameters affecting the weld defect acceptance criteria of clad submarine pipelines installed by S-lay or reel-lay. Eng Fail Anal 58:394–406. doi:10.1016/j.engfailanal.2015.07.003
Carlson M, Johnson JA, Kunerth DC (1992) Control of GMAW: detection of discontinuities in the weld pool. NDT E Int 25: 44
Ulbrich D, Kowalczyk J, Jósko M, Selech J (2015) The analysis of spot welding joints of steel sheets with closed profile by ultrasonic method. Case Stud Nondestruct Test Eval 4:8–14. doi:10.1016/j.csndt.2015.09.002
Bentley PG, Dawson DG, Prine DW (1982) An evaluation of acoustic emission for the detection of defects produced during fusion welding of mild and stainless steels. NDT Int 15(5):243–249. doi:10.1016/0308-9126(82)90033-5
Yu J, Ziehl P, Matta F, Pollock A (2013) Acoustic emission detection of fatigue damage in cruciform welded joints. J Constr Steel Res 86:85–91. doi:10.1016/j.jcsr.2013.03.017
Valavanis I, Kosmopoulos D (2010) Multiclass defect detection and classification in weld radiographic images using geometric and texture features. Expert Syst Appl 37(12):7606–7614. doi:10.1016/j.eswa.2010.04.082
Alaknanda, Anand RS, Kumar P (2006) Flaw detection in radiographic weld images using morphological approach. NDT & E Int 39(1):29–33. doi:10.1016/j.ndteint.2005.05.005
Vilar R, Zapata J, Ruiz R (2009) An automatic system of classification of weld defects in radiographic images. NDT & E Int 42(5):467–476. doi:10.1016/j.ndteint.2009.02.004
Kasban H, Zahran O, Arafa H, El-Kordy M, Elaraby SMS, Abd El-Samie FE (2011) Welding defect detection from radiography images with a cepstral approach. NDT & E Int 44(2):226–231. doi:10.1016/j.ndteint.2010.10.005
Yu H, Xu Y, Song J, Pu J, Zhao X, Yao G (2015) On-line monitor of hydrogen porosity based on arc spectral information in Al–Mg alloy pulsed gas tungsten arc welding. Opt Laser Technol 70:30–38. doi:10.1016/j.optlastec.2015.01.010
Zhang Z, Kannatey-Asibu E Jr, Chen S, Huang Y, Xu Y (2015) Online defect detection of Al alloy in arc welding based on feature extraction of arc spectroscopy signal. Int J Adv Manuf Technol 79:2067–2077. doi:10.1007/s00170-015-6966-9
Wang Y, Zhao P (2001) Noncontact acoustic analysis monitoring of plasma arc welding. Int J Press Vessel Pip 78(1):43–47. doi:10.1016/S0308-0161(00)00085-5
Huang W, Kovacevic R (2009) Feasibility study of using acoustic signals for online monitoring of the depth of weld in the laser welding of high-strength steels. Proc Inst Mech Eng B J Eng Manuf 2009(223):343–361
Saad E, Wang H, Kovacevic R (2006) Classification of molten pool modes in variable polarity plasma arc welding based on acoustic signature. J Mater Process Technol 174(1–3):127–136. doi:10.1016/j.jmatprotec.2005.03.020
Grad L, Grum J, Polajnar I, Marko Slabe J (2004) Feasibility study of acoustic signals for on-line monitoring in short circuit gas metal arc welding. Int J Mach Tools Manuf 44(5):555–561. doi:10.1016/j.ijmachtools.2003.10.016
Wang Y, Chen Q, Sun Z, Sun J (2001) Relationship between sound signal and weld pool status in plasma arc welding. Trans Nonferrous Metals Soc Chin 11(01):54–57
You DY, Gao XD, Katayama S (2014) Review of laser welding monitoring. Sci Technol Weld Join 19 (3):181–201. doi:10.1179/1362171813Y.0000000180
Huang W, Kovacevic R (2011) A neural network and multiple regression method for the characterization of the depth of weld penetration in laser welding based on acoustic signatures. J Intell Manuf 22(2):131–143. doi:10.1007/s10845-009-0267-9
Luo Z, Liu W, Wang Z, Ao S (2015) Monitoring of laser welding using source localization and tracking processing by microphone array. Int J Adv Manuf Technol 1–8. doi:10.1007/s00170-015-8095-x
Huang NE, Shen Z, Long SR, Wu ML, Shih HH, Zheng Q, Yen NC, Tung CC, Liu HH (1998) The empirical mode decomposition end Hilbert spectrum for nonlinear and nonstationary time series analysis. Proc Roy Soc London A 454(1998):903–995
Messler RW Jr (2004) Principle of welding: process, physics, chemistry and metallurgy. Wiley VCH Verlag GmbH & Co., Singapore
Xiao YH, Ouden GD (1993) Weld pool oscillation during GTA welding of mild steel. Weld J (Miami) 72
Subramaniam S, White DR (2001) Effect of shield gas composition on surface tension of steel droplet in a gas-metal-arc welding arc. Metall Mater Trans B 32(2001):313–318
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Yusof, M.F.M., Kamaruzaman, M.A., Ishak, M. et al. Porosity detection by analyzing arc sound signal acquired during the welding process of gas pipeline steel. Int J Adv Manuf Technol 89, 3661–3670 (2017). https://doi.org/10.1007/s00170-016-9343-4
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DOI: https://doi.org/10.1007/s00170-016-9343-4