IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v26y2005i2p481-494.html
   My bibliography  Save this article

Characterization of failure mechanism in composite materials through fractal analysis of acoustic emission signals

Author

Listed:
  • Silva, F.E.
  • Gonçalves, L.L.
  • Fereira, D.B.B.
  • Rebello, J.M.A.

Abstract

In this paper it is presented a detailed numerical investigation of acoustic emission signals obtained from test samples of fibreglass reinforced polymeric matrix composites, when subjected to tensile and flexural tests. Various fractal indices, characteristic of the signals emitted at the different structural failures of the test samples and which satisfy non-stationary distributions, have been determined. From the results obtained for these indices, related to the Hurst analysis, detrended fluctuation analysis, minimal cover analysis and to the boxcounting dimension analysis, it has been shown they can discriminate the different failure mechanisms and, therefore, they constitute their signature.

Suggested Citation

  • Silva, F.E. & Gonçalves, L.L. & Fereira, D.B.B. & Rebello, J.M.A., 2005. "Characterization of failure mechanism in composite materials through fractal analysis of acoustic emission signals," Chaos, Solitons & Fractals, Elsevier, vol. 26(2), pages 481-494.
  • Handle: RePEc:eee:chsofr:v:26:y:2005:i:2:p:481-494
    DOI: 10.1016/j.chaos.2004.12.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077905001001
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2004.12.042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dubovikov, M.M & Starchenko, N.V & Dubovikov, M.S, 2004. "Dimension of the minimal cover and fractal analysis of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 591-608.
    2. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salmasi, Mehrdad & Modarres-Hashemi, M., 2009. "Design and analysis of fractal detector for high resolution radars," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2133-2145.
    2. Xu, Na & Shang, Pengjian & Kamae, Santi, 2009. "Minimizing the effect of exponential trends in detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 311-316.
    3. Bueno-Orovio, Alfonso & Pérez-García, Víctor M., 2007. "Enhanced box and prism assisted algorithms for computing the correlation dimension," Chaos, Solitons & Fractals, Elsevier, vol. 34(2), pages 509-518.
    4. Serinaldi, Francesco, 2010. "Use and misuse of some Hurst parameter estimators applied to stationary and non-stationary financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2770-2781.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juraj Čurpek, 2019. "Time Evolution of Hurst Exponent: Czech Wholesale Electricity Market Study," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2019(3), pages 25-44.
    2. Yuanyuan Zhang & Stephen Chan & Jeffrey Chu & Hana Sulieman, 2020. "On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market," JRFM, MDPI, vol. 13(1), pages 1-14, January.
    3. Fernandez Viviana, 2011. "Alternative Estimators of Long-Range Dependence," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(2), pages 1-37, March.
    4. Serletis, Apostolos & Rosenberg, Aryeh Adam, 2009. "Mean reversion in the US stock market," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 2007-2015.
    5. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    6. Didenko Alexander & Dubovikov Mikhail & Poutko Boris, 2015. "Forecasting coherent volatility breakouts," Вестник Финансового университета, CyberLeninka;Федеральное государственное образовательное бюджетное учреждение высшего профессионального образования «Финансовый университет при Правительстве Российской Федерации» (Финансовый университет), issue 1 (85), pages 30-36.
    7. A. Gómez-Águila & J. E. Trinidad-Segovia & M. A. Sánchez-Granero, 2022. "Improvement in Hurst exponent estimation and its application to financial markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
    8. He, Shanshan & Wang, Yudong, 2017. "Revisiting the multifractality in stock returns and its modeling implications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 11-20.
    9. Bariviera, A.F. & Guercio, M. Belén & Martinez, Lisana B., 2012. "A comparative analysis of the informational efficiency of the fixed income market in seven European countries," Economics Letters, Elsevier, vol. 116(3), pages 426-428.
    10. Sukpitak, Jessada & Hengpunya, Varagorn, 2016. "The influence of trading volume on market efficiency: The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 259-265.
    11. Charfeddine, Lanouar & Khediri, Karim Ben & Aye, Goodness C. & Gupta, Rangan, 2018. "Time-varying efficiency of developed and emerging bond markets: Evidence from long-spans of historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 632-647.
    12. Miao Yu & Dong Liu & Jean Dieu Bazimenyera, 2013. "Diagnostic Complexity of Regional Groundwater Resources System Based on time series fractal dimension and Artificial Fish Swarm Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 1897-1911, May.
    13. Santos, E.C.O. & Guedes, E.F. & Zebende, G.F. & da Silva Filho, A.M., 2022. "Autocorrelation of wind speed: A sliding window approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    14. Alvarez-Ramirez, J. & Rodriguez, E. & Ibarra-Valdez, C., 2020. "Medium-term cycles in the dynamics of the Dow Jones Index for the period 1985–2019," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 546(C).
    15. Jamshid Ardalankia & Mohammad Osoolian & Emmanuel Haven & G. Reza Jafari, 2019. "Scaling Features of Price-Volume Cross-Correlation," Papers 1903.01744, arXiv.org, revised Aug 2020.
    16. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda & Dirk Helbing, 2013. "Are Random Trading Strategies More Successful than Technical Ones?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    17. Kiran Sharma & Parul Khurana, 2021. "Growth and dynamics of Econophysics: a bibliometric and network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4417-4436, May.
    18. Brandi, Giuseppe & Di Matteo, T., 2022. "Multiscaling and rough volatility: An empirical investigation," International Review of Financial Analysis, Elsevier, vol. 84(C).
    19. Vinodh Madhavan & Rakesh Arrawatia, 2016. "Relative Efficiency of G8 Sovereign Credit Default Swaps and Bond Scrips: An Adaptive Market Hypothesis Perspective," Studies in Microeconomics, , vol. 4(2), pages 127-150, December.
    20. Zheng, Shiyuan & Lan, Xiangang, 2016. "Multifractal analysis of spot rates in tanker markets and their comparisons with crude oil markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 547-559.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:26:y:2005:i:2:p:481-494. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.