Russian Journal of Nondestructive Testing

, Volume 53, Issue 2, pp 96–103 | Cite as

Analysis of errors in location of flaws in multipass welds using different clustering methods

  • L. N. Stepanova
  • S. I. Kabanov
  • I. S. Ramazanov
  • K. V. Kanifadin
Acoustic Methods
  • 20 Downloads

Abstract

Titanium and duralumin inserts were introduced into a weld to imitate welding flaws in St3 steel samples. Analysis of the accuracy of locating the introduced flaws with different clustering methods (by digitized shape, main informative parameters, the rise rate of leading-edge envelope) has shown that these methods involve considerable time expenditures. The developed dynamic clustering has been combined with the clustering by main informative parameters and allowed in situ location of flaws during welding, while the weld has not been completed yet.

Keywords

welding insert flaw acoustic emission error cluster dynamic clustering 

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References

  1. 1.
    Gomera, V.P., Smirnov, A.D., Nefed’ev, E.Yu., et al., In situ acoustic-emission detection of cracks in welded joints, Kontrol’. Diagn., 2016, no. 7, pp. 25–32.CrossRefGoogle Scholar
  2. 2.
    Stepanova, L.N., Ramazanov, I.S., and Kanifadin, K.V, Dynamic clustering by a set of parameters of acousticemission signals, Kontrol’. Diagn., 2012, no. 10, pp. 12–16.Google Scholar
  3. 3.
    Calabrese, L., Campanella, G., and Proverbio, E, Use of cluster analysis of acoustic emission signals in evaluating damage severity in concrete structures, J. Acoust. Emiss., 2010, vol. 28, pp. 129–141.Google Scholar
  4. 4.
    Gumenyuk, V.A. and Nesmashnyi, E.V, Optimizing the algorithm of acoustic-emission location of flaws in circular seams of welded constructions, Kontrol’. Diagn., 2007, no. 9, pp. 34–42.Google Scholar
  5. 5.
    Mohsen Ghofrani, Hamid, Shahabi, and Farhad, Kolahan., Evaluate and control the weld quality, using acoustic data and artificial neural network modeling, Indian J. Sci. Res, 2014, vol. 1, no. 2, pp. 482–486.Google Scholar
  6. 6.
    Stepanova, L.N., Ramazanov, I.S., and Kireenko, V.V, The development of a defect-rejection procedure for multiple-pass welding by the distribution of the principal parameters of acoustic-emission signals, Russ. J. Nondestr. testing, 2014, vol. 50, no. 11, pp. 667–678.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2017

Authors and Affiliations

  • L. N. Stepanova
    • 1
  • S. I. Kabanov
    • 1
  • I. S. Ramazanov
    • 1
  • K. V. Kanifadin
    • 2
  1. 1.Siberian Aeronautical Research Institute named after S. A. ChaplyginNovosibirskRussia
  2. 2.Siberian Transport UniversityNovosibirskRussia

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