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.

[1]  TengFei Bao,et al.  Detection of subcritical crack propagation for concrete dams , 2009 .

[2]  Li Chun-Gui,et al.  A method for distinguishing dynamical species in chaotic time series , 2003 .

[3]  P. Grassberger,et al.  Measuring the Strangeness of Strange Attractors , 1983 .

[4]  D. Gribkov,et al.  Learning dynamics from nonstationary time series: analysis of electroencephalograms. , 2000, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[5]  Lakshmi Vara Prasad Pondugala Stochastic J-integral and realiability of composite laminates based on a computational methodology combining experimental investigation, stochastic finite element analysis and maximum entropy method , 2000 .

[6]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Manish Sarkar,et al.  Characterization of medical time series using fuzzy similarity-based fractal dimensions , 2003, Artif. Intell. Medicine.

[8]  Kantz Quantifying the closeness of fractal measures. , 1994, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[9]  H. Stanley,et al.  Scale invariance in the nonstationarity of human heart rate. , 2000, Physical review letters.

[10]  F. Takens Detecting strange attractors in turbulence , 1981 .

[11]  Robert Savit,et al.  Stationarity and nonstationarity in time series analysis , 1996 .

[12]  E. Jaynes On the rationale of maximum-entropy methods , 1982, Proceedings of the IEEE.

[13]  Li Ji,et al.  Review on hidden trouble detection and health diagnosis of hydraulic concrete structures , 2007 .