A model for defects hazard degree assessing based of the acoustic emission invariants

Aeronautical and Space-Rocket Engineering

DOI: 10.34759/vst-2022-4-94-103


Samuilov A. O.

Zhukovsky Air Force Engineering Academy, 3, Planetnaya str., Moscow, 125190, Russia

e-mail: branco09@mail.ru


The article presents a model for assessing the presence and hazard degree of defects based on acoustic emission invariants. The analysis of acoustic emission criteria of destruction is presented from the viewpoint of their application possibility while diagnosing power elements of aircraft structures in real time to determine the degree of deformation and the hazard of structure defects. As of now, a number of the destruction criteria of the controlled object (CO) material has been developed, based on the various approaches to the acoustic-emission (AE) information processingn and analyzing. However, there is no criterion allowing diagnosing the cracks being developed with high probability. This is being associated with the CO material inhomogeneity and the presence of the residual stresses. Under these conditions, to increase fidelity of the acoustic-emission method of non-destructive control and defining the degree of the defects hazard, it is rational to develop and employ destruction criteria based on statistic invariant dependencies that characterize pulse flows of the acoustic emission. The article presents the results of studying the acoustic emission parameters relationship with the early stages of destruction specifics of a layered composite, as well as iron and aluminum alloys employed in the design of power elements of the aircraft airframe. The studies on destruction of the standard cylindrical samples from the 40 steel and flat samples from D16 duralumin were conducted for experimental test of the drawn inferences validity. These types of samples selection is stipulated by the wide-spread occurrence of steels, having the yield point, and aluminum based allows in the power elements of the structures. High acoustic activity at the yield point, i.e. avalanche-like density increase of the mobile dislocations, is intrinsic to these types of materials. The developed approach provides the possibility of assessment in the process of control of dynamics and degree of change of the emission informative parameters, characterizing the degree of the pre-destructive state of the structure. Assessment with the relations being presented allows evaluating both initial and «rarefied» acoustic-emission flows of any order and does not depend on the loadings pre-history, shapes and sizes of the structures, which allows perpetrating constant and periodic acoustic-emission control.


acoustic-emission diagnostics, fracture criterion, invariant, crack resistance, acoustic processes


  1. Builo S.I. Kontrol’. Diagnostika, 2000, no. 10, pp. 10–15.
  2. Popov A.V., Komlev A.B., Samuilov A.O., Zakusilov P.V. V mire nerazrushayushchego kontrolya, 2021, vol. 24, no. 2(92), pp. 50–52. DOI: 10.12737/1609-3178-2021-52-54
  3. Popov A.V., Voloshina V.Yu., Sirenko I.L. et al. Patent RU 2659575 C1, 03.07.2018.
  4. Popov A.V., Samuilov A.O., Voloshina V.Yu. Vestnik UGATU, 2021, vol. 25, no. 3(93), pp. 50–55. DOI: 10.54708/19926502_2021_2539350
  5. Popov A.V., Samuilov A.O., Voloshina V.Yu., Zakusilov P.V. Inzhener i promyshlennik, 2021,
    no. 3—4(51-52), pp. 14–17.
  6. Popov A.V., Samuilov A.O., Nedoseikin A.D., Cherepanov I.S. Vestnik RGATU, 2021, no. 4 (59),
    pp. 98-105.
  7. Kondranin E.A., Popov A.V. Patent RU 2 367 942 C1, 20.09.2009.
  8. Popov A.V., Kondranin E.A. Kontrol’. Diagnostika, 2008, no. 7, pp. 45–47.
  9. Troitskii V.A., Borovikov A.S., Rad’ko V.P. et al. Spravochnik po oborudovaniyu dlya defektoskopii svarnykh shvov (Handbook of weld joints flaw detection equipment), Kiev, Tekhnika, 1987, 126 p.
  10. Rytov S.M. Vvedenie v statisticheskuyu radiofiziku. Chast’ 1. Sluchainye protsessy (Introduction to statistical radio physics. Part 1. Random processes), Moscow, Nauka, 1976, 496 p.
  11. Grosse C.U., Ohtsu M. (eds.) Acoustic Emission Testing. Springer Science & Business Media, 2008, 416 p.
  12. Ciampa F., Meo M. A new algorithm for acoustic emission localization and flexural group velocity determination in anisotropic structures. Composites Part A: Applied Science and Manufacturing, 2010,
    vol. 41, no. 12, pp. 1777–1786. DOI: 10.1016/j.compositesa.2010.08.013
  13. Dunegan H.L., Tatro C.A. Acoustic Emission Effects During Mechanical Deformation. Techniques of Metals Research, 1971, vol. 5, no. 2, pp. 12 — 32.
  14. Dunegan H.L., Harris D.O., Tatro C.A. Fracture Analysis by Use of Acoustic Emission. Engineering Fracture Mechanics, 1968, vol. 1, no. 1, pp. 105-110, IN23-IN24, 111-122. DOI: 10.1016/0013-7944(68)90018-0
  15. Earle P.S., Shearer P.M. Characterization of global seismograms using an automatic—picking algorithm. Bulletin of the Seismological Society of America (BSSA), 1994, vol. 84, no. 2, pp. 366–376.
  16. Eaton M.J., Pullin R., Holford K.M. Acoustic emission source location in composite material susing Delta T mapping. Composites Part A: Applied Science and Manufacturing, 2012, vol. 43, no. 6, pp. 856–863. DOI: 10.1016/j.compositesa.2012.01.023
  17. Hamstad M.A., O‘Gallagher A., Gary J. A wavelet transform applied to acoustic emission signals. Part 1: Source identification. Journal of Acoustic Emission, 2002, vol. 20, pp. 39–82.
  18. Hu B., OuYang H., Wu Y. et al. Numerical prediction of the interaction noise radiated from an axial fan. Applied Acoustics, 2013, vol. 74, no. 4, pp. 544–552. DOI: 10.1016/j.apacoust.2012.09.009
  19. Wang J., Teng T.-L. Artificial neural network—based seismic detector. Bulletin of the Seismological Society of America (BSSA), 1995, vol. 85, no, 1, pp. 308–319. DOI: 10.1785/BSSA0850010308
  20. Jiao J., He C., Wu B. et al. Wang Application of wavelet transform on modal acoustic emission source location in thin plates with one sensor. International Journal of Pressure Vessels and Piping, 2004, vol. 81, no. 5, pp. 427–431. DOI: 10.1016/j.ijpvp.2004.03.009
  21. Maskaykin V. A., Makhrov V. P. Thermal conductivity research of the aircraft heat-insulating skin under flight conditions. Aerospace MAI Journal, 2021, vol. 28, no. 4, pp. 118-130. DOI: 10.34759/vst-2021-4-118-130
  22. Bokhoeva L.A., Baldanov A.B., Chermoshentseva A.S. Optimal structure of multi-layer wing console of unmanned aerial vehidle with experimental validation. Aerospace MAI Journal, 2020, vol. 27, no. 1, pp. 65-75. DOI: 10.34759/vst-2020-1-65-75
  23. Tudupova A.N., Strizhius V.E., Bobrovich A.V. Computational and experimental evaluation of fatigue life characteristics of the transport category aircraft composite wing panels. Aerospace MAI Journal, 2020, vol. 27, no. 4, pp. 21-29. DOI: 10.34759/vst-2020-4-21-29

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