Acoustic emission source localization by artificial neural networks

Structural Health Monitoring

Volumn 14, Issue 6, 2015, Pages 633-647

  Kalafat, Sinan ^a   Sause, Markus G R ^a  

^a UNIVERSITY OF AUGSBURG   (Germany)

Author keywords

Acoustic emission; carbon fiber composite; composite material; localization; neural network; polymer matrix composites; pressure vessel; source location; type III carbon fiber reinforced polymer pressure vessel

Indexed keywords

ACOUSTIC EMISSION TESTING; ACOUSTIC EMISSIONS; CARBON FIBER REINFORCED PLASTICS; COMPOSITE MATERIALS; POLYMER MATRIX COMPOSITES; PRESSURE VESSELS; REINFORCEMENT;

ACOUSTIC EMISSION SOURCES; CARBON FIBER COMPOSITE; CARBON FIBER REINFORCED POLYMER; LOCALIZATION; LOCALIZATION ACCURACY; NETWORK-BASED APPROACH; SOURCE LOCATION; TRAINED NEURAL NETWORKS;

NEURAL NETWORKS;

EID: 84948771885     PISSN: 14759217     EISSN: 17413168     Source Type: Journal    
DOI: 10.1177/1475921715607408     Document Type: Article

References (31)

1. F.L.MatthewsR.D.Rawlings. Composite materials: engineering and science. Cambridge: Woodhead Publishing, Ltd, 1999.
2. J.BohseG.W.MairP.Novak. Acoustic emission testing of high-pressure composite cylinders. In: R.PullinK.M.HolfordS.L.Evans. (eds) Advanced materials research. Berlin, 2006, pp. 267–272. Switzerland: Trans Tech Publication.
3. M.Sause. Identification of failure mechanisms in hybrid materials utilizing pattern recognition techniques applied to acoustic emission signals. Augsburg: University of Augsburg, 2010.
4. A.R.BunsellA.Thionnet. Life prediction for carbon fibre filament wound composite structures. Philos Mag2010; 90: 4129–4146.
5. M.G.R.SauseT.MüllerA.Horoschenkoff. Quantification of failure mechanisms in mode-I loading of fiber reinforced plastics utilizing acoustic emission analysis. Compos Sci Technol2012; 72: 167–174.
6. C.U.GrosseM.Ohtsu. Acoustic emission testing. 1st ed.Berlin, Heidelberg: Springer-Verlag, 2008.
7. D.Aljets. Acoustic emission source location in composite aircraft structures using modal analysis. South Wales: University of Glamorgan, 2011.
8. M.A.Hamstad. A waveform-based study of AE wave propagation by use of eight wide-band sensors on a composite pressure vessel. In: Proceedings of the 30th European conference on acoustic emission testing, Granada, 12–15 September 2012, pp. 12–15. Granada: EWGAE.
9. M.A.HamstadM.G.R.Sause. Acoustic emission signals versus propagation direction for hybrid composite layup with large stiffness differences versus direction. In: Proceedings of the 31st conference of the European Working Group on Acoustic Emission, Dresden, 3–5 September 2014, pp. 1–8. Dresden: EWGAE.
10. H.-Y.Chou. Damage analysis of composite pressure vessels using acoustic emission monitoring. Melbourne, VIC, Australia: RMIT University, 2012.
11. K.Ono. Research and applications of AE on advanced composites. In: Proceedings of the 30th European conference on acoustic emission testing, Granada, 12–15 September 2012, p. 44. Granada: EWGAE.
12. M.BlahacekM.ChladaZ.Prevorovský. Acoustic emission source location based on signal features. In: R.PullinK.M.HolfordS.L.Evans. (eds) Advanced materials research. Prague, 2006, pp. 77–82. Switzerland: Trans Tech Publication.
13. J.J.ScholeyP.D.WilcoxM.R.Wisnom. A generic technique for acoustic emission source location. J Acoust Emiss2009; 27: 291–298.
14. M.ChladaP.ZdenekM.Blahacek. Neural network AE source location apart from structure size and material. In: Proceedings of the European Working Group on Acoustic Emission, Vienna, 8–10 September 2010, pp. 359–366. Vienna: EWGAE.
15. T.KunduH.NakataniN.Takeda. Acoustic source localization in anisotropic plates. Ultrasonics2012; 52: 740–746.
16. T.Kundu. Acoustic source localization. Ultrasonics2014; 54: 25–38.
17. G.PiątkowskiZ.Waszczyszyn. Identification problems of recurrent cascade neural network application in predicting an additional mass location. Comput Assist Mech Eng Sci2011; 18: 217–228.
18. S.Kalafat. Lokalisierung von Schallemissionsquellen mit künstlichen neuronalen Netzwerken in Faserverbundwerkstoffen. Augsburg: University of Augsburg, 2013.
19. S.KalafatM.G.R.Sause. Localization of acoustic emission sources in fiber composites using artificial neural networks. In: Proceedings of the 31st conference of the European Working Group on Acoustic Emission, Dresden, 3–5 September 2014. Dresden: EWGAE.
20. J.A.NelderR.Mead. A simplex method for function minimization. Comput J1965; 7: 308–313.
21. J.H.KurzC.U.GrosseH.W.Reinhardt. Strategies for reliable automatic onset time picking of acoustic emissions and of ultrasound signals in concrete. Ultrasonics2005; 43: 538–546.
22. B.Hosten. Heterogeneous structure of modes and Kramers–Kronig relationship in anisotropic viscoelastic materials. J Acoust Soc Am1998; 104: 1382.
23. H.Lamb. On waves in an elastic plate. P Roy Soc Lond A Mat1917; 93: 114–128.
24. M.G.R.SauseS.Horn. Quantification of the uncertainty of pattern recognition approaches applied to acoustic emission signals. J Nondestruct Eval2013; 32: 242–255.
25. C.M.Bishop. Neural networks for pattern recognition. 1st ed. Birmingham: Oxford University Press, Inc., 1995.
26. S.S.Haykin. Neural networks: a comprehensive foundation. 2nd ed.Barrie, ON, Canada: Prentice Hall, 1999.
27. M.G.R.Sause. Investigation of pencil-lead breaks as acoustic emission sources. J Acoust Emiss2011; 29: 184–196.
28. M.G.R.SauseM.A.HamstadS.Horn. Finite element modeling of lamb wave propagation in anisotropic hybrid materials. Compos Part B: Eng2013; 53: 249–257.
29. K.TodaK.Motegi. Propagation characteristics of leaky Lamb waves in a liquid-loaded double-layered substrate consisting of a thin piezoelectric ceramic plate and a thin glass plate. J Acoust Soc Am1999; 105: 3290–3294.
30. M.Calomfirescu. Lamb waves for structural health monitoring in viscoelastic composite materials. Bremen: Logos Verlag Berlin GmbH, 2008.
31. F.L.Bookstein. Principal warps: thin-plate splines and the decomposition of deformations. IEEE T Pattern Anal1989; 11: 567–585.