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Towards fatigue failure prediction via acoustic emission analysis

Shimon Bettan1, Eilon Faran1,*, Ronen Talmon2, and Doron Shilo1

  • *Contact author: eilonfa@ technion.ac.il
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Phys. Rev. Materials 10, 023802 – Published 23 February, 2026

DOI: https://doi.org/10.1103/t948-9sjk

Abstract

This study presents and tests several approaches for predicting fatigue failure in metals using acoustic emission data analysis. We demonstrate that conventional single-valued AE features (event rate, amplitude, power-law exponents) fail to correlate with fatigue damage progression in selective laser melted additively manufactured AlSi10Mg specimens. Instead, we develop two complementary methods based on spectral density analysis of complete acoustic emission waveforms: (1) a physics-based approach that identifies fatigue-related events through their enhanced excitation of an axial resonant mode, and (2) a data-driven method using dimensionality reduction combined with statistical metrics. Both methods demonstrate the ability to predict approaching failure, with the data-driven approach showing superior consistency. Furthermore, both methods are unsupervised, require no extensive training datasets, and are grounded in physical principles, suggesting potential applicability across different materials and geometries. These findings offer promising pathways for nondestructive fatigue monitoring.

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References (48)

  1. W. Cui, X. Huang, and F. Wang, Description of Fatigue Loading, in Unified Fatigue Life Prediction Method for Marine Structures edited by W. Cui, X. Huang, F. Wang (Springer, Berlin, Heidelberg, 2014), pp. 173–208.
  2. K. K. Chawla, Fatigue and creep, in Composite Materials, edited by K.K. Chawla (Springer, New York, NY, 1998), pp. 404–435.
  3. T. Moan and K. M. Engesvik, Discussion of “Fatigue reliability: Introduction” by The Committee on Fatigue and Fracture Reliability of the Committee on Structural Safety and Reliability of the Structural Division, J. Struct. Eng. 110 (1982).
  4. H. Javidrad, B. Koc, H. Bayraktar, U. Simsek, and K. Gunaydin, Fatigue performance of metal additive manufacturing: A comprehensive overview, Virtual Phys. Prototyp. 19, e2302556 (2024).
  5. A. Yadollahi and N. Shamsaei, Additive manufacturing of fatigue resistant materials: Challenges and opportunities, Int. J. Fatigue 98, 14 (2017).
  6. S. Sankararaman, Y. Ling, and S. Mahadevan, Uncertainty quantification and model validation of fatigue crack growth prediction, Eng. Fract. Mech. 78, 1487 (2011).
  7. C. R. Farrar and K. Worden, An introduction to structural health monitoring, Philos. Trans. Math. Phys. Eng. Sci. 365, 303 (2007).
  8. S. Hassani and U. Dackermann, A systematic review of advanced sensor technologies for non-destructive testing and structural health monitoring, Sensors 23, 2204 (2023).
  9. B. Glisic, Concise historic overview of strain sensors used in the monitoring of civil structures: The first one hundred years, Sensors 22, 2397 (2022).
  10. Z. Yang, H. Yang, T. Tian, D. Deng, M. Hu, J. Ma, D. Gao, J. Zhang, S. Ma, L. Yang, H. Xu, and Z. Wu, A review on guided-ultrasonic-wave-based structural health monitoring: From fundamental theory to machine learning techniques, Ultrasonics 133, 107014 (2023).
  11. S. C. Olisa, M. A. Khan, and A. Starr, Review of current guided wave ultrasonic testing (GWUT) limitations and future directions, Sensors 21, 811 (2021).
  12. G. F. Nataf, P. O. Castillo-Villa, J. Baró, X. Illa, E. Vives, A. Planes, and E. K. H. Salje, Avalanches in compressed porous SiO2-based materials, Phys. Rev. E 90, 022405 (2014).
  13. J. P. Sethna, K. A. Dahmen, and C. R. Myers, Crackling noise, Nature (London) 410, 242 (2001).
  14. E. K. H. Salje and K. A. Dahmen, Crackling noise in disordered materials, Annu. Rev. Condens. Matter Phys. 5, 233 (2014).
  15. S. Zapperi, A. Vespignani, and H. E. Stanley, Plasticity and avalanche behaviour in microfracturing phenomena, Nature (London) 388, 658 (1997).
  16. R. Maaß, M. Wraith, J. T. Uhl, J. R. Greer, and K. A. Dahmen, Slip statistics of dislocation avalanches under different loading modes, Phys. Rev. E 91, 042403 (2015).
  17. N. Friedman, A. T. Jennings, G. Tsekenis, J.-Y. Kim, M. Tao, J. T. Uhl, J. R. Greer, and K. A. Dahmen, Statistics of dislocation slip avalanches in nanosized single crystals show tuned critical behavior predicted by a simple mean field model, Phys. Rev. Lett. 109, 095507 (2012).
  18. T. M. Roberts and M. Talebzadeh, Acoustic emission monitoring of fatigue crack propagation, J. Constr. Steel Res. 59, 695 (2003).
  19. D. Bonamy, Dynamics of cracks in disordered materials, Comptes Rendus Phys. 18, 297 (2017).
  20. W. Zhao, Z. Wang, Z. Song, P. G. Ranjith, H. Zhang, and T. Wang, Experimental exploration of damage propagation in rocks using acoustic emission, Bull. Eng. Geol. Environ. 80, 6065 (2021).
  21. E. K. H. Salje, D. E. Soto-Parra, A. Planes, E. Vives, M. Reinecker, and W. Schranz, Failure mechanism in porous materials under compression: Crackling noise in mesoporous SiO2, Philos. Mag. Lett. 91, 554 (2011).
  22. D. Ozevin and S. Kessler, The dependence of acoustic emission behavior on prior fatigue loading history, Front. Built Environ. 8, 1 (2022).
  23. J. Cui, X. Qu, C. Lv, and J. Du, Linking Acoustic emission signals to fatigue crack growth in metallic Materials: A new approach for structural health monitoring, Appl. Acoust. 235, 110689 (2025).
  24. F. Dong, Y. Li, and B. Li, Acoustic emission-driven fatigue damage evolution equation and life prediction of composite laminates, Int. J. Fatigue 198, 109012 (2025).
  25. M. Seleznev, A. Weidner, and H. Biermann, Detection of early fatigue damage during ultrasonic fatigue testing of steel by acoustic emission monitoring, Int. J. Fatigue 185, 108367 (2024).
  26. J. Baró, Á. Corral, X. Illa, A. Planes, E. K. H. Salje, W. Schranz, D. E. Soto-Parra, and E. Vives, Statistical similarity between the compression of a porous material and earthquakes, Phys. Rev. Lett. 110, 088702 (2013).
  27. G. Galanopoulos, D. Milanoski, N. Eleftheroglou, A. Broer, D. Zarouchas, and T. Loutas, Acoustic emission-based remaining useful life prognosis of aeronautical structures subjected to compressive fatigue loading, Eng. Struct. 290, 116391 (2023).
  28. J. Li, X. Cao, R. Chen, C. Zhao, Y. Li, and X. Huang, Prediction of remaining fatigue life of metal specimens using data-driven method based on acoustic emission signal, Appl. Acoust. 211, 109571 (2023).
  29. J. Huang, Z. Zhang, B. Zheng, R. Qin, G. Wen, W. Cheng, and X. Chen, Acoustic emission technology-based multifractal and unsupervised clustering on crack damage monitoring for low-carbon steel, Measurement 217, 113042 (2023).
  30. M. Mohammad, A. Tajuddin, S. Abdullah, N. Jamaluddin, and B. I. S. Murat, Fatigue damage monitoring using un-supervised clustering method of acoustic emission signal on SAE 1045 steel, Int. J. Automot. Mech. Eng. 13, 3584 (2016).
  31. O. M. Stankevych and D. P. Rebot, Methods of artificial intelligence for acoustic emission diagnostics of fracture stages (a review), Mater. Sci. 60, 255 (2024).
  32. S. Gholizadeh, Z. Leman, and B. T. H. T. Baharudin, State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission, Ultrasonics 132, 106998 (2023).
  33. E. Bronstein, E. Faran, R. Talmon, and D. Shilo, Data-driven analysis of acoustic emission signals for the distinction of deformation mechanisms, Phys. Rev. Mater. 9, 073804 (2025).
  34. S. Bettan, E. Bronstein, H. Seiner, P. Sedlak, M. Koller, D. Shilo, and E. Faran, Linking acoustic emission signals to deformation mechanisms in magnesium, Phys. Rev. Mater. 9, 103805 (2025).
  35. E. Bronstein, E. Faran, R. Talmon, and D. Shilo, Uncovering avalanche sources via acceleration measurements, Nat. Commun. 15, 7474 (2024).
  36. N. E. Uzan, R. Shneck, O. Yeheskel, and N. Frage, Fatigue of AlSi10Mg specimens fabricated by additive manufacturing selective laser melting (AM-SLM), Mater. Sci. Eng. A 704, 229 (2017).
  37. Standard Test Method for Strain-Controlled Fatigue Testing, https://store.astm.org/e0606_e0606m-21.html.
  38. S. Deschanel, W. Ben Rhouma, and J. Weiss, Acoustic emission multiplets as early warnings of fatigue failure in metallic materials, Sci. Rep. 7, 13680 (2017).
  39. F. Yamashita, E. Fukuyama, S. Xu, H. Kawakata, K. Mizoguchi, and S. Takizawa, Two end-member earthquake preparations illuminated by foreshock activity on a meter-scale laboratory fault, Nat. Commun. 12, 4302 (2021).
  40. K. Z. Nanjo and A. Yoshida, Changes in the b value in and around the focal areas of the M6.9 and M6.8 earthquakes off the coast of Miyagi prefecture, Japan, in 2021, Earth Planets Space 73, 176 (2021).
  41. Y. Y. Kagan, Seismic moment distribution revisited: I. Statistical results: Seismic moment distribution: I, Geophys. J. Int. 148, 520 (2002).
  42. H. Bauke, Parameter estimation for power-law distributions by maximum likelihood methods, Eur. Phys. J. B 58, 167 (2007).
  43. K. F. Graff, Wave Motion in Elastic Solids (Dover Publications, New York, 1991).
  44. L. McInnes, J. Healy, and J. Melville, UMAP: Uniform Manifold approximation and projection for dimension reduction, arXiv:1802.03426.
  45. Z. I. Botev, J. F. Grotowski, and D. P. Kroese, Kernel density estimation via diffusion, Ann. Stat. 38, 2916 (2010).
  46. B. W. Silverman, Density Estimation for Statistics and Data Analysis, 1st ed. (Routledge, New York, 2018).
  47. A. Gretton, K. M. Borgwardt, M. J. Rasch, B. Schölkopf, and A. Smola, A kernel two-sample test, J. Mach. Learn Res. 13, 723 (2012).
  48. E. Faran, Data sets for article: Towards fatigue failure prediction via acoustic emission analysis [Data set]. Zenodo (2025), https://doi.org/10.5281/zenodo.17150452.

Outline

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Phys. Rev. Materials 10, 023802– Published 23 February, 2026
  • Received 18 September 2025
  • Revised 9 December 2025
  • Accepted 28 January 2026
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