Skip to main content
SpringerLink
Log in

Structural Health Monitoring Based on Artificial Intelligence Algorithm and Acoustic Emission Analysis

  • Conference paper
  • First Online:
European Workshop on Structural Health Monitoring (EWSHM 2020)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 128))

Included in the following conference series:

Abstract

In the online approach for Structural Health Monitoring (SHM) particular relevance can be assumed in the Artificial Intelligence algorithms. In fact, the real time structure condition evaluation must be performed by the fast analysis of the data provided by several sensors and devices. Among the SHM techniques the most attractive are based on the analysis of the Acoustic emission. In particular, in the paper are considered the acoustic emission naturally generated by the building material under stress. This signal is used in the paper to evaluate the input features for the Machine learning. The features of the acoustic emission signal used in the training of the machine learning techniques are based on the Gutenberg–Richter law, which expresses the relationship between magnitude and total number of earthquake events in a defined region and time interval.

In the design of the automatic classifier of structural critical event the selection of the machine learning technique is performed by comparing with tests the performance of the: (i) Support Vector Machine (SVM), (ii) k Neighbor Classifier and (iii) Adaptive Boosting. The experimental tests performed by compression tests carried out on cubic concrete specimens permit to achieve the best performance as concerning the overall classification accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lacidogna, G., Accornero, F., Corrado, M., Carpinteri, A.: Crushing and fracture energies in concrete specimens monitored by Acoustic Emission. In: Proceedings of the 8th International Conference on Fracture Mechanics of Concrete and Concrete Structures, FraMCoS 2013, pp 1726–1736 (2013)

    Google Scholar 

  2. Rao, M.V.M.S., Prasanna Lakshmi, K.J.: Analysis of b-value and improved b-value of acoustic emissions accompanying rock fracture. Curr. Sci. 89, 1577–1582 (2005)

    Google Scholar 

  3. Grosse, C., Reinhardt, H., Dahm, T.: Localization and classification of fracture types in concrete with quantitative acoustic emission measurement techniques. NDT E Int. 30, 223–230 (1997)

    Article  Google Scholar 

  4. Zitto, M.E., Piotrkowski, R., Gallego, A., Sagasta, F., Benavent-Climent, A.: Damage assessed by wavelet scale bands and b-value in dynamical tests of a reinforced concrete slab monitored with acoustic emission. Mech. Syst. Signal Process. 60, 75–89 (2015)

    Article  Google Scholar 

  5. Goszczyńska, B., Świt, G., Trąmpczyński, W.: Application of the IADP acoustic emission method to automatic control of traffic on reinforced concrete bridges to ensure their safe operation. Arch. Civ. Mech. Eng. 16, 867–875 (2016)

    Article  Google Scholar 

  6. Shah, S.G., Chandra Kishen, J.M.: Use of acoustic emissions in flexural fatigue crack growth studies on concrete. Eng. Fract. Mech. 87, 36–47 (2012)

    Article  Google Scholar 

  7. Siracusano, G., Lamonaca, F., Tomasello, R., Garescì, F., La Corte, A., Carnì, D.L., Carpentieri, M., Grimaldi, D., Finocchio, G.: A framework for the damage evaluation of acoustic emission signals through Hilbert–Huang transform. Mech. Syst. Signal Process. 75, 109–122 (2016)

    Google Scholar 

  8. Grosse, C.U., Ohtsu, M.: Acoustic Emission Testing. Basic for Research—Applications in Civil Engineering. Springer, Leipzig (2008)

    Google Scholar 

  9. Aggelis, D.G.: Classification of cracking mode in concrete by acoustic emission parameters. Mech. Res. Commun. 38, 153–157 (2011)

    Article  Google Scholar 

  10. Carpinteri, A., Lacidogna, G., Corrado, M., Di Battista, E.: Cracking and crackling in concrete-like materials: a dynamic energy balance. Eng. Fract. Mech. 155, 130–144 (2016)

    Article  Google Scholar 

  11. Lamonaca, F., Carnì, D.L., Carrozzini, A., Grimaldi, D., Olivito, R.S.: Multi-triggering and signal extraction for acoustic emissions monitoring. In: 2014 IEEE International Workshop on Metrology for Aerospace, MetroAeroSpace 2014 – Proceedings, pp 383–387 (2014)

    Google Scholar 

  12. Kashif Ur Rehman, S., Ibrahim, Z., Memon, S.A., Jameel, M.: Nondestructive test methods for concrete bridges: a review. Constr. Build. Mater. 107, 58–86 (2016)

    Article  Google Scholar 

  13. Yapar, O., Basu, P.K., Volgyesi, P., Ledeczi, A.: Structural health monitoring of bridges with piezoelectric AE sensors. Eng. Fail. Anal. 56, 150–169 (2015)

    Article  Google Scholar 

  14. Huguet, S., Godin, N., Gaertner, R., Salmon, L., Villard, D.: Use of acoustic emission to identify damage modes in glass fibre reinforced polyester. Compos. Sci Technol. 62, 1433–1444 (2002)

    Article  Google Scholar 

  15. Fursa, T.V., Utsyn, G.E., Korzenok, I.N., Petrov, M.V., Reutov, Y.A.: Using electric response to mechanical impact for evaluating the durability of the GFRP-concrete bond during the freeze-thaw process. Compos. Part B Eng. 90, 392–398 (2016)

    Article  Google Scholar 

  16. Njuhovic, E., Bräu, M., Wolff-Fabris, F., Starzynski, K., Altstädt, V.: Identification of interface failure mechanisms of metallized glass fibre reinforced composites using acoustic emission analysis. Compos. Part B Eng. 66, 443–452 (2014)

    Article  Google Scholar 

  17. Sano, O., Terada, M., Ehara, S.: A study on the time-dependent microfracturing and strength of Oshima granite. Tectonophysics 84, 343–362 (1982)

    Article  Google Scholar 

  18. Lamonaca, F., Carrozzini, A., Grimaldi, D., Olivito, R.S.: Acoustic emission monitoring of damage concrete structures by multi-triggered acquisition system. In: IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2012), pp 1630–1634 (2012)

    Google Scholar 

  19. Ghiassi, B., Verstrynge, E., Lourenço, P.B., Oliveira, D.V.: Application of acoustic emission technique for bond characterization in FRP-masonry systems. Trans Tech Publications Ltd., pp. 534–541 (2015)

    Google Scholar 

  20. Vidya Sagar, R., Raghu Prasad, B.K.: Damage limit states of reinforced concrete beams subjected to incremental cyclic loading using relaxation ratio analysis of AE parameters. Constr. Build. Mater. 35, 139–148 (2012)

    Article  Google Scholar 

  21. Verstrynge, E., Van Balen, K., Wevers, M., Ghiassi, B., Oliveira, D.V.: Detection and localization of debonding damage in composite-masonry strengthening systems with the acoustic emission technique. In: 6th International Conference on Emerging Technologies in Non-Destructive Testing, pp. 511–517. CRC Press/Balkema (2015)

    Google Scholar 

  22. Carni, D.L., Scuro, C., Lamonaca, F., Olivito, R.S., Grimaldi, D.: Damage analysis of concrete structures by means of B-value technique. Int. J. Comput. 16, 82–88 (2017)

    Google Scholar 

  23. Angrisani, L., Bonavolontà, F., Liccardo, A., Schiano Lo Moriello, R., Ferrigno, L., Laracca, M., Miele, G.: Multi-channel simultaneous data acquisition through a compressive sampling-based approach. Meas. J. Int. Meas. Confed. 52, 156–172 (2014)

    Article  Google Scholar 

  24. Carnì, D.L., Scuro, C., Lamonaca, F., Olivito, R.S., Grimaldi, D.: Damage analysis of concrete structures by means of acoustic emissions technique. Compos. Part B Eng. 115, 79–86 (2017)

    Article  Google Scholar 

  25. Gutenberg, B., Richter, C.F.: Magnitude and energy of earthquakes. Nature 176, 795 (1955)

    Article  Google Scholar 

  26. Sengur, A.: Multiclass least-squares support vector machines for analog modulation classification. Expert Syst. Appl. 36, 6681–6685 (2009)

    Article  Google Scholar 

  27. Kannan, R., Ravi, S.: Second-order statistical approach for digital modulation scheme classification in cognitive radio using support vector machine and K-Nearest neighbor classifier. J. Comput. Sci. 9, 235 (2013)

    Article  Google Scholar 

  28. Rodríguez-Pérez, Q., Zúñiga, F.R.: Båth’s law and its relation to the tectonic environment: a case study for earthquakes in Mexico. Tectonophysics 687, 66–77 (2016)

    Article  Google Scholar 

  29. Schölkopf, B., Smola, A.J.: A short introduction to learning with kernels (2003)

    Google Scholar 

  30. Schölkopf, B.: An Introduction to Support Vector Machines (2003)

    Google Scholar 

  31. Alanazi, H.O., Abdullah, A.H., Qureshi, K.N.: A critical review for developing accurate and dynamic predictive models using machine learning methods in medicine and health care. J. Med. Syst. 41, 1–10 (2017)

    Article  Google Scholar 

  32. Schapire, R.E.: Explaining adaboost (2013)

    Google Scholar 

  33. Mohammadi, R., Najfabadi, M.A., Saeedifar, M., Yousefi, J., Minak, G.: Correlation of acoustic emission with finite element predicted damages in open-hole tensile laminated composites. Compos. Part B: Eng. 108, 427–435 (2017)

    Google Scholar 

  34. BS EN 12390-3:2009 Testing hardened concrete. Compressive strength of test specimens (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physics, University of Calabria, 87036, Rende, CS, Italy

    Carmelo Scuro

  2. Department of Civil Engineering, University of Calabria, 87036, Rende, CS, Italy

    Renato Sante Olivito

  3. Department of Engineering, University of Sannio, 82100, Benevento, BN, Italy

    Francesco Lamonaca

  4. Department of Informatics, Modelling, Electronics and System Engineering, University of Calabria, 87036, Rende, CS, Italy

    Domenico Luca Carnì

Authors
  1. Carmelo Scuro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Renato Sante Olivito
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francesco Lamonaca
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Domenico Luca Carnì
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carmelo Scuro .

Editor information

Editors and Affiliations

  1. Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA, USA

    Piervincenzo Rizzo

  2. Department of Engineering, UniversitĂ  degli Studi di Palermo, Palermo, Italy

    Alberto Milazzo

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Scuro, C., Olivito, R.S., Lamonaca, F., Carnì, D.L. (2021). Structural Health Monitoring Based on Artificial Intelligence Algorithm and Acoustic Emission Analysis. In: Rizzo, P., Milazzo, A. (eds) European Workshop on Structural Health Monitoring. EWSHM 2020. Lecture Notes in Civil Engineering, vol 128. Springer, Cham. https://doi.org/10.1007/978-3-030-64908-1_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-64908-1_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-64907-4

  • Online ISBN: 978-3-030-64908-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation