Science China Technological Sciences

, Volume 54, Issue 7, pp 1930–1939

Abnormality diagnosis of cracks in the concrete dam based on dynamical structure mutation



A method of the fuzzy cross-correlation factor exponent in dynamics is researched and proposed to diagnose abnormality of cracks in the concrete dam. Moreover, the Logistic time series changing from period-doubling bifurcation to chaos is tested first using this method. Results indicate that it can distinguish inherent dynamics of time series and can detect mutations. Considering that cracks in the concrete dam constitute an open, dissipative and complex nonlinear dynamical system, a typical crack on the downstream face of a concrete gravity arch dam is analyzed with the proposed method. Two distinct mutations are discovered to indicate that the abnormality diagnosis of cracks in the concrete dam is achieved dynamically through this method. Furthermore, because it can be directly utilized in the measured crack opening displacement series to complete abnormality diagnosis, it has a good prospect for practical applications.


dynamical structure mutation cracks in the concrete dam method of the fuzzy cross-correlation factor exponent in dynamics abnormality diagnosis of cracks 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Xu H Z. Nonlinear analysis model for safety monitoring of large dam dynamic system (in Chinese). PhD Thesis. Nanjing: Hohai University, 2001Google Scholar
  2. 2.
    Bao T F. Chaotic characteristics, analysis theories and methods of cracks in concrete dams (in Chinese). PhD Thesis. Nanjing: Hohai University, 2004Google Scholar
  3. 3.
    Gribkov D, Gribkova V. Learning dynamics from nonstationary time series: Analysis of Electroencephalograms. Phys Rev E, 2000, 61(6): 6538–6545CrossRefGoogle Scholar
  4. 4.
    Wu Z R. Safety Monitoring Theory and Its Application of Hydraulic Structures (in Chinese). Beijing: Higher Education Press, 2003Google Scholar
  5. 5.
    Wu Z R, Li J, Gu C S, et al. Review on hidden trouble detection and health diagnosis of hydraulic concrete structures. Sci China Ser E-Tech Sci, 2007, 50(Suppl 1): 34–50CrossRefGoogle Scholar
  6. 6.
    Li X H. Evolution rule and abnormality diagnosis of crack of important hydraulic concrete structure (in Chinese). PhD Thesis. Nanjing: Hohai University, 2003Google Scholar
  7. 7.
    Cong P J. Research on analysis model of concrete dam crack based on entropy theory (in Chinese). PhD Thesis. Nanjing: Hohai University, 2007Google Scholar
  8. 8.
    Bao T F, Yu H. Detection of subcritical crack propagation for concrete dams. Sci China Ser E-Tech Sci, 2009, 52(12): 3654–3660MATHCrossRefGoogle Scholar
  9. 9.
    Grassberger P, Procaccia I. Measuring the strangeness of strange attractors. Phys D: Nonlinear Phenomena, 1983, 9(1–2): 189–208MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Takens F. Detecting Strange Attractors in Turbulence. Berlin: Springer, 1981. 366–381Google Scholar
  11. 11.
    Mallat S. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans on PAMI, 1989, 11(7): 674–693MATHCrossRefGoogle Scholar
  12. 12.
    Manuca R, Savit R. Stationarity and nonstationarity in time series analysis. Phys D, 1996, 99: 134–161MATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Li C G, Pei L Q. A method for distinguishing dynamical species in chaotic time series (in Chinese). Acta Physica Sinica, 2003, 52(9): 2114–2120Google Scholar
  14. 14.
    Kantz H. Quantifying the closeness of fractal measures. Phys Rev E, 1994, 49(6): 5091–5097CrossRefGoogle Scholar
  15. 15.
    Manish S, Leong T Y. Characterization of medical time series using fuzzy similarity-based fractal dimensions. Artif Intell Med, 2003, 27: 201–222CrossRefGoogle Scholar
  16. 16.
    Jaynes E T. On the rationale of maximum entropy methods. Proc of IEEE, 1982, 70(9): 939–952CrossRefGoogle Scholar
  17. 17.
    Lakshmi V P P. Stochastic J-integral and reliability of composite laminates based on a computational methodology combining experimental investigation, stochastic finite element analysis and maximum entropy method. PhD Thesis. Canada: Concordia University, 2000Google Scholar
  18. 18.
    Bernaola-Galvan P, Ivanov P C, Amaral L A N, et al. Scale invariance in the nonstationarity of human heart rate. Phys Rev Lett, 2001, 87(16): 168105(1–4)CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
  2. 2.National Engineering Research Center of Water Resources Efficient Utilization and Engineering SafetyNanjingChina
  3. 3.College of Water Conservancy and Hydropower EngineeringHohai UniversityNanjingChina

Personalised recommendations