Behavior of Rock Acoustic Emission Based on Chaotic Theory

Abstract: Recently AE technology widely used is one of the effective means of the safety monitoring to geotechnical engineering. However some problems are met when AE technique is applied to monitoring and forecasting. The reason is that rock system is a highly nonlinear complex system during a dynamic and irreversible evolution, and the characteristics of rock damage are not fully understood. In order to predict the mechanical behavior of rock, the rock nonlinear static and dynamic systems should be established by using nonlinear sciences, which are suitable for describing the characteristics of rock mechanics and engineering. Chaos is suitable for researching non-linear mathematics and mechanics, which is also one of the fundamental characteristics of non-linear system. There is a large number of non-stable dispersion of data and non-uniform data in rock system, such as displacement, AE series, seismic data and other records of time series, which reveal failure mechanism of rock by using chaos.The main points in this thesis are summarized as follows:①Uniaxial compression damage tests and Acoustic emission test of Calcareous mudstone, sandstone, fine sandstone, Korea sandstone are carried with AG-I Full-digitally Servo-controlled testing machine and PCI-2 emissions equipment. Acoustic emission events time series, AE energy time series, displacement (strain) and stress time series are recorded in the process of rock test. On the basis of the theory of nonlinear kinetic principle, nonlinear dynamics model of rock failure process are discussed.②Acoustic emission events time series is treated by using the wavelet noise reduction method. The chaotic characteristics are determined after the noise reduction. Comparing between the noise reduction data and the original data is done. The effect of noise on the chaotic characteristics was studied.③AE time series embedding dimension and the delay time are calculated from the recorded acoustic emission time series. Delay time was chosen by using mutual information method. Embedding dimension was obtained by using Cao method and saturation correlation dimension law.④Chaotic characteristics, i.e. fractal dimension and Lyapunov exponents (mainly the largest Lyapunov exponents), were given out. Fractal dimension from different definitions and estimates have different results, the correlation dimension is the most commonly used estimate of fractal dimension. The G-P saturation correlation dimension method is applied to compute the correlation dimension. The small data set method is applied to calculate the largest Lyapunov exponents of the time series. The chaotic feature of the rock AE time series is determined from the qualitative and quantitative aspects. The qualitative method is PCA (Principal Components Analysis) method, and the quantitative analysis methods are based on saturated correlation dimension law and the largest Lyapunov exponents method.⑤The application of characteristics of the rock failure AE signal and the AE basic parameters to analyze the rock damage are discussed. The fractal model of acoustic emission time series is established based on the chaos fractal theory. By means of the changes of fractal dimension and the AE characteristics of rock damage during the various stages of rock damage, the criterion of rock damage is found…
Key words: Acoustic emission; Wavelet de-noising; Nonlinear dynamics; Chaos; Rock failure criterion

This entry was posted in Master Thesis. Bookmark the permalink.