Skip to main content

Signal-Based AE Analysis

  • Chapter
  • First Online:
Acoustic Emission Testing

Abstract

Signal-based AE techniques use the entire transient waveform resulting from an AE event. As such, more information is available allowing for improved interpretation of fracture processes in a material or structure. Two signal-based approaches are presented and discussed in this chapter: Waveform analysis and quantitative analysis. The former has received increasing attention due to the recent developments and wide availability of machine learning algorithms. The latter is a classic approach that has its origin in seismology. The main approach associated with quantitative analysis is moment tensor inversion (MTI). While MTI requires accurate 3D source localization from an extensive network of sensors, waveform analysis can theoretically be performed with a single sensor. A comparison between signal- and parameter-based AE analyses is presented first. Subsequently, the measurement process is explained and its main influences on the recorded signals are discussed. Finally, waveform analysis and quantitative analysis approaches are described in detail, along with application examples from the literature.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
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

  • Aki K, Richards PG (1980) Quantitative seismology. Freeman, San Francisco

    Google Scholar 

  • Anastasopoulos A (2005) Pattern recognition techniques for acoustic emission based on condition assessment of unfired pressure vessels. J Acoust Emiss 23:318–330

    Google Scholar 

  • Andersen LM (2001) A relative moment tensor inversion technique applied to seismicity induced by mining. PhD thesis, University of the Witwatersrand, Johannesburg, p 230

    Google Scholar 

  • ASTM E610 (1982) Standard definitions of terms relating to acoustic emission. ASTM, pp 579–581

    Google Scholar 

  • Balázs GL, Grosse CU, Koch R, Reinhardt HW (1993) Acoustic emission monitoring on steel-concrete interaction. Otto Graf J 4:56–90

    Google Scholar 

  • Bar-Cohen Y, Xue T, Lih SS (1996) Polymer piezoelectric transducers for ultrasonic NDE. NDTnet 1(9):7

    Google Scholar 

  • Barker JS, Langston CA (1982) Moment tensor inversion of complex earthquakes. Geophys J Int 46(3):341–371

    Google Scholar 

  • Berger H (ed) (1977) Nondestructive testing standards—a review. Gaithersburg, ASTM, Philadelphia

    Google Scholar 

  • Buland R (1976) The mechanics of locating earthquakes. Bull Seismol Soc Am 66(1):173–187

    Google Scholar 

  • Carter GC, Ferrie JF (1979) A coherence and cross spectral estimation program. IEEE Press, pp 1–2.3

    Google Scholar 

  • CEN European Standard (2009) EN 1330-9—nondestructive testing—terminology—Part 9: Terms used in acoustic emission analysis. Comité Européan de Normalisation CEN. (1330-9) Rel. 2000-3, pp 1–23

    Google Scholar 

  • Dahm T (1996) Relative moment tensor inversion based on ray theory: theory and synthetic tests. Geophys J Int 124:245–257

    Article  Google Scholar 

  • Daubechies I (1996) Where do wavelets come from?—a personal point of view. Proc IEEE 84(4):510–513

    Article  Google Scholar 

  • DGZfP (1991) Merkblatt SE-3 – Richtlinie zur Charakterisierung des Schallemissionsprüfgerätes im Labor. Deutsche Gesellschaft für Zerstörungsfreie Prüfung. Recommendation SE-3

    Google Scholar 

  • Dziewonski AM, Woodhouse JH (1981) An experiment in systematic study of global seismicity: centroid-moment tensor solutions for 201 moderate and large earthquakes of 1981. J Geophys Res 88(B4):3247–3271

    Google Scholar 

  • Ebrahimkhanlou A, Salamone S (2018) Single-sensor acoustic emission source localization in plate-like structures using deep learning. Aerospace 5(2):50

    Article  Google Scholar 

  • Emamian V, Kaveh M, Tewfik AH, Shi Z, Jacobs LJ, Jarzynski J (2003) Robust clustering of acoustic emission signals using neural networks and signal subspace projections. EURASIP J Adv Signal Process 276–286

    Google Scholar 

  • Enoki M, Kishi T (1988) Theory and analysis of deformation moment tensor due to microcracking. Int J Fract 38:295–310

    Google Scholar 

  • Farrar C, Worden K (2012) Structural health monitoring: a machine learning perspective. Wiley

    Google Scholar 

  • Feignier B, Young RP (1992) Moment tensor inversion of induced microseismic events: evidence of non-shear failures in the –4 < M < –2 moment magnitude range. Geophys Res Lett 19(14):1503–1506

    Article  Google Scholar 

  • Finck F, Yamanouchi M, Reinhardt HW, Christian CU (2003) Evaluation of mode I failure of concrete in a splitting test using acoustic emission technique. Int J Fract 124:139–152

    Article  Google Scholar 

  • Fukunaga Y, Kishi T (1986) Progress in acoustic emission III. In: Yamaguchi K et al (eds). Japanese Society for Non-Destructive Inspection, Tokyo, pp 722–731

    Google Scholar 

  • Geiger L (1910) Herdbestimmung bei Erdbeben aus den Ankunftszeiten. Nachrichten von der Königlichen Gesellschaft der Wissenschaften zu Göttingen 4:331–349

    MATH  Google Scholar 

  • Gilbert F (1973) A Discussion on the measurement and interpretation of changes of strain in the Earth - Derivation of source parameters from low-frequency spectra. Philosophical Transactions of the Royal Society of London. Ser A Math Phys Sci 274:369–371. http://doi.org/10.1098/rsta.1973.0065

  • Glaser SD, Weiss GG, Johnson LR (1998) Body waves recorded inside an elastic half-space by an embedded, wideband velocity sensor. J Acoust Soc Am 104(3):1404–1412

    Article  Google Scholar 

  • Gollob S (2017) Source localization of acoustic emissions using multi-segment paths based on a heterogeneous velocity model in structural concrete. PhD Dissertation ETH Zurich No. 24146

    Google Scholar 

  • Grosse CU (1996) Quantitative zerstörungsfreie Prüfung von Baustoffen mittels Schallemissionsanalyse und Ultraschall. PhD Thesis, University of Stuttgart, Germany, 168 pages

    Google Scholar 

  • Grosse CU (2000) WinPecker - Programm zur vollautomatischen dreidimensionalen Lokalisierung von Schallemissionsquellen. DGZfP Report 72:191–204

    Google Scholar 

  • Grosse CU (2021) Einführung in die Zerstörungsfreie Prüfung. Springer Publ

    Google Scholar 

  • Grosse CU, Reinhardt HW (1999) Schallemissionsquellen automatisch lokalisieren. Materialprüfung 41:342–346

    Google Scholar 

  • Grosse CU, Schumacher T (2013) Anwendungen der Schallemissionsanalyse an Betonbauwerken. Bautechnik 90(11):721–731

    Article  Google Scholar 

  • Grosse CU, Weiler B, Reinhardt HW (1997a) Relative moment tensor inversion applied to concrete fracture tests. J Acoust Emiss 14(3–4):64–87

    Google Scholar 

  • Grosse CU, Reinhardt HW, Dahm T (1997b) Localization and classification of fracture types in concrete with quantitative acoustic emission measurement techniques. NDT&E Int 30:223–230

    Article  Google Scholar 

  • Grosse CU, Finck F, Kurz J, Reinhardt HW (2004) Improvements of the acoustic emission technique using wavelet algorithms, coherence functions and automatic data analysis techniques. Constr Build Mater 18(3):203–213

    Article  Google Scholar 

  • Hafiz A, Schumacher T (2018) Monitoring of stresses in concrete using ultrasonic coda wave comparison technique. J Nondestr Eval 37:73

    Article  Google Scholar 

  • Hamstad MA (1994) An examination of piezoelectric polymers as wideband acoustic emission displacement sensors. Progress in AE VII, Japanese Society for NDI, pp 79–86

    Google Scholar 

  • Hamstad MA (1997) Improved signal-to-noise wideband acoustic/ultrasonic contact displacement sensors for wood and polymers. Wood Fiber Sci 29(3):239–248

    Google Scholar 

  • Hamstad MA (2001) An illustrated overview of the use and value of a wavelet transformation to acoustic emission technology. NIST Report, Boulder

    Google Scholar 

  • Hamstad MA, Fortunko CM (1995) Development of practical wideband high-fidelity acoustic emission sensors. In: Proceedings of SPIE, conference on NDE of aging infrastructure, vol 2456, pp 281–288

    Google Scholar 

  • Harley JB, Sparkman D (2019) Machine learning and NDE: past, present, and future. AIP Conf. Proc. 2102:090001-1–090001-10. https://doi.org/10.1063/1.5099819

  • Hatano H, Mori E (1976) Acoustic-emission transducer and its absolute calibration. J Acoust Soc Am 59(2):344–349

    Article  Google Scholar 

  • Hildyard MW, Milev A, Linzer LM, Roberts MKC, Jager AJ, Spottiswoode SM (2005) PLATMINE 3.7: assess the hazard posed by dynamic failure of pillars in the back areas of platinum mines. PLATMINE final project report

    Google Scholar 

  • Hsu NN, Breckenridge FR (1981) Characterization and calibration of acoustic emission sensors. Mater Eval 39(1):60–68

    Google Scholar 

  • Hykes DL, Hedrick WR, Starchman DE (1992) Ultrasound physics and instrumentation. Mosby-Year Book, 2nd ed

    Google Scholar 

  • Jost ML, Hermann R (1989) A student’s guide to and review of moment tensors. Seismol Res Lett 60(2):37–57

    Article  Google Scholar 

  • Kalafat S, Sause MGR (2015) Acoustic emission source localization by artificial neural networks. Struct Health Monit 14(6):633–647

    Article  Google Scholar 

  • Kaphle M (2012) Analysis of acoustic emission data for accurate damage assessment for structural health monitoring applications. PhD dissertation, Queensland University of Technology

    Google Scholar 

  • Kino GS (1987) Acoustic waves: devices, imaging, and analog signal processing. Prentice Hall

    Google Scholar 

  • Köppel S (2002) Schallemissionsanalyse zur Untersuchung von Stahlbetontragwerken. PhD Thesis ETH No. 14490, Swiss Federal Institute of Technology (ETH) Zürich, Switzerland

    Google Scholar 

  • Krautkrämer J, Krautkrämer H (1986) Werkstoffprüfung mit Ultraschall. Springer, Berlin

    Book  Google Scholar 

  • Kurz JH, Finck F, Grosse CU, Reinhardt HW (2004) Similarity matrices as a new feature for acoustic emission analysis in concrete. DGZfP-Proceedings BB 90-CD, pp 769–775

    Google Scholar 

  • Landis EN (1993) A quantitative acoustic emission investigation of microfractures in cement based materials. Thesis, Northwestern University, Evanston, USA

    Google Scholar 

  • Landis EN, Shah SP (1995) Frequency-dependent stress wave attenuation in cement-based materials. J Eng Mech 121(6):737–743

    Article  Google Scholar 

  • Landis EN, Ouyang C, Shah SP (1992) Automated determination of first P-wave arrival and acoustic emission source location. J Acoust Emiss 10(1–2):S97–S103

    Google Scholar 

  • Lawson CH, Hanson RJ (1974) Solving least squares problems. Prentice-Hall, Engelwood Cliffs, New Jersey

    MATH  Google Scholar 

  • Linzer LM (2005) Manuel Rocha Medal recipient: a relative moment tensor inversion technique applied to seismicity induced by mining. J Rock Mech Rock Eng 38(2):81–104

    Article  Google Scholar 

  • Linzer L (2012) Moment tensor inversion toolbox version 8.0. User’s guide

    Google Scholar 

  • Linzer L, Mhamdi L, Schumacher T (2015) Application of a moment tensor inversion code developed for mining-induced seismicity to fracture monitoring of civil engineering materials. J Appl Geophys 112:256–267

    Article  Google Scholar 

  • Lockner AD, Byerlee JD, Kuksenko V, Ponomarev A, Sidrin A (1993) Quasi-static fault growth and shear fracture energy in granite. Nature 350:39–42

    Article  Google Scholar 

  • Lu Y, Oruklu E, Saniie J (2008) Application of Hilbert-Huang transform for ultrasonic nondestructive evaluation. pp. 1499–1502. https://doi.org/10.1109/ULTSYM.2008.0365

  • Lyamshev ML, Stanullo J, Busse G (1995) Thermoacoustic vibrometry. Materialprüfung 37:1–2

    Google Scholar 

  • McLaskey GC, Glaser SD (2012) Acoustic emission sensor calibration for absolute source measurements. J Nondestruct Eval 31:157–168. https://doi.org/10.1007/s10921-012-0131-2

  • McGarr A (1992) Moment tensors of ten Witwatersrand mine tremors. Pure Appl Geophys 139:781–800

    Article  Google Scholar 

  • Mhamdi L (2015) Seismology-based approaches for the quantitative acoustic emission monitoring of concrete structures. PhD dissertation, University of Delaware, Newark, DE

    Google Scholar 

  • Miller RK, McIntire P (eds) (1987) Acoustic emission testing. Nondestructive testing handbook, vol 5, 2nd ed. American Society for Nondestructive Testing

    Google Scholar 

  • Nair A, Cai CS, Kong X (2019) Acoustic emission pattern recognition in CFRP retrofitted RC beams for failure mode identification. Compos B Eng 161:691–701

    Article  Google Scholar 

  • Napier JAL, Spottiswoode SM, Sellers E, Hildyard MW, Linzer LM (2005) SIMRAC 02-03-01: new criteria for rock mass stability and control using integration of seismicity and numerical modeling. SIMRAC Final Project Report, Department of Minerals and Energy, South Africa

    Google Scholar 

  • Niederleithinger E, Wolf J, Mielentz F, Wiggenhauser H, Pirskawetz S (2015) Embedded ultrasonic transducers for active and passive concrete monitoring. Sensors 15(5):9756–9772

    Article  Google Scholar 

  • Ohtsu M (1991) Simplified moment tensor analysis and unified decomposition of acoustic emission source: application to in-situ hydrofracturing test. J Geophys Res Solid Earth 96(B4):6211–6221

    Article  Google Scholar 

  • Oncescu MC (1986) Relative seismic moment tensor determination for Vrancea intermediate depth earthquakes. Pure Appl Geophys 124:931–940

    Article  Google Scholar 

  • Oncescu L, Grosse CU (1998) HYPOAE—a program for the localization of hypocenters of acoustic emissions. Computer program, Rev. 2.1

    Google Scholar 

  • Patton H (1980) Reference point equalization method for determining the source and path of surface waves. J Geophys Res Solid Earth 85(B2):821–848

    Article  Google Scholar 

  • Pazdera L, Smutny J (2001) Using non-traditional tool—discrete wavelet transformation to analysis of acoustic emission signal. In: Acoustic Emission AE2001, International conference on Internet, March–September 2001, Brno, Czech Republic

    Google Scholar 

  • Proctor TM (1982) Some details on the NBS conical transducer. J Acoust Emiss 1(3):173–178

    Google Scholar 

  • Proctor TM (1986) More recent improvements on the NBS conical transducer. J Acoust Emiss 5(4):134–142

    Google Scholar 

  • Rikitake T, Sato R, Hagiwara Y (1987) Applied mathematics for earth scientists. Mathematical approaches to geophysics. Kluwer Academic Pub, Dordrecht

    Google Scholar 

  • Rippengill S, Worden K, Holford KM, Pullin R (2003) Automatic classification of acoustic emission patterns. Strain 39:31–41

    Article  Google Scholar 

  • Sachse W, Kim KY (1987) Quantitative acoustic emission and failure mechanics of composite materials. Ultrasonics 25(4):195–203

    Article  Google Scholar 

  • Salamon MDG, Wiebols GA (1974) Digital location of seismic events by an underground network of seismometers using the arrival times of compressional waves. Rock Mech 6:141–166

    Article  Google Scholar 

  • Sause MGR, Gribov A, Unwin AR, Horn S (2012) Pattern recognition approach to identify natural clusters of acoustic emission signals. Pattern Recogn Lett 33:17–23

    Article  Google Scholar 

  • Schechinger B (2005) Schallemissionsanalyse zur Überwachung der Schädigung von Stahlbeton. Diss., Technische Wissenschaften, Eidgenössische Technische Hochschule ETH Zürich, Nr. 16250. https://doi.org/10.3929/ethz-a-005067935

  • Scruby CB (1985) Quantitative acoustic emission techniques. Nondestr Test 8:141–210

    Google Scholar 

  • Šílený J, Panza GF, Campus P (1992) Waveform inversion for point source moment retrieval with variable hypocentral depth and structural model. Geophys J Int 109(2):259–274

    Article  Google Scholar 

  • Simmons JA (1991) Deconvolution of acoustic emission and other casual time series. J Res Nat Inst Stand Technol 96(3):345–369

    Article  MATH  Google Scholar 

  • Stein S, Wysession M (2003) An introduction to seismology, earthquakes and earth structure. Blackwell Publishing. http://levee.wustl.edu/seismology/book/

  • Strelitz RA (1980) The fate of the downgoing slab: a study of the moment tensors from body waves of complex deep-focus earthquakes. Phys Earth Planet Inter 21(2–3):83–96

    Article  Google Scholar 

  • To AC, Glaser SD (2005) Full waveform inversion of a 3-D source inside an artificial rock. J Sound Vib 285(4–5):835–857

    Article  Google Scholar 

  • Udias A, Baumann D (1969) A computer program for focal mechanism determination combining P and S wave data. Bull Seismol Soc Am 59(2):503–519

    Google Scholar 

  • Vallen H, Forker J (2001) Optimierung der Analyse von Daten der Schallemissionsprüfung eines vorgeschädigten Objekts während dem Bersttest. 13. Kolloquium Schallemission, DGZfP Berichtsband 78, pp 11–21

    Google Scholar 

  • Virieux J, Asnaashari A, Brossier R, Metivier L, Ribodetti A, Zhou W (2017) An introduction to full waveform inversion. Encyclopedia of exploration geophysics SEG

    Google Scholar 

  • Weiler B, Grosse CU (1995) Calibration of ultrasonic transducers—a comparative study of different methods. Otto Graf J 6:153–167

    Google Scholar 

  • Wood BRA, Harris RW (1982) An evaluation of the breaking pencil lead calibration technique. Jap. Soc. NDI. Progress in acoustic emission VI, Tokyo, pp 423–439

    Google Scholar 

  • Zang A, Wagner FC, Stanchits S, Dresen G, Andresen R, Haidekker MA (1998) Source analysis of acoustic emissions in granite cores under symmetric and asymmetric compressive load. Geophys J Int 135(3):1113–1130

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Schumacher .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Schumacher, T., Linzer, L., Grosse, C.U. (2022). Signal-Based AE Analysis. In: Grosse, C.U., Ohtsu, M., Aggelis, D.G., Shiotani, T. (eds) Acoustic Emission Testing. Springer Tracts in Civil Engineering . Springer, Cham. https://doi.org/10.1007/978-3-030-67936-1_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-67936-1_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67935-4

  • Online ISBN: 978-3-030-67936-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics