| With the mining depth increasing,high ground stress and high temperature are becoming the main factors to affect the stability of rock. In present the acoustic emission technology has been an important role in the ground pressure monitoring. It can provide a basis for solving practical engineering problems to study the temperature impact on the rock instability damage. In this thesis, the AE serials of granite on natural drying, water temperature of 50 degrees and 100 degrees were investigated by uniaxial compression test to get the mechanical parameters of rock deterioration process, the AE characteristics and acoustic emission signals, with frequency characteristics being analyzed using Fourier transform and wavelet packet. Combined with wavelet packet and fractal theory, the correspondence between acoustic emission signal box dimension and frequency was obtained. In the end the pattern of granite’s acoustic emission signals in different temperature was recognized by fuzzy neural networks. The main research achievements are as follows:1. The AE serials of different temperature of granite were investigated by uniaxial compression test, the rock failure process, the stress- strain curve, deformation characteristics and the characteristics of acoustic emission parameter are analyzed. Different water sample were experienced four stages that pressure airtight, elastic deformation and plastic deformation and destruction instability, such as maximum stress value and ringing count rate in 50 c water temperature, the natural drying of next time, 100- degree water temperature is minimal.2. The frequency range of rock acoustic emission signal is obtained by Fourier transform. Peak frequency of the acoustic emission signal that 50 water temperature, 100 degrees temperature granite specimen are mainly concentrated on about 100 KHZ, frequency distributing in the range of 80-120 KHZ range. Peak frequency of granite specimen under natural dry is concentrated on about 45 KHZ, frequency range being around 20 ~ 60 KHZ.3. Through wavelet packet decomposition of acoustic emission signal on whole process of rock burst, the coefficient of wavelet packet energy spectrum and extract the frequency distribution and energy distribution was analyzed. The main energy of acoustic emission signals of three water temperature under the condition are distributed in sub-band i1, i2, i3, i2, i7 and i8, the energy distribution of the range of frequency varying with the load time and temperature.4. Combined with the fractal theory to different water temperature granite, the acoustic emission signal wavelet packet and the signal multi-scale fractal box dimension were studied. Natural dry wife signal frequency range fractal box dimension at around 1.4, 50 degrees when the water temperature signal frequency range had the fractal box dimension at around 1.6, when the water temperature is 100 degrees, wife signal frequency range fractal box dimension at around 1.6, sub-band signal wavelet packet decomposition of the fractal box dimension and its frequency characteristic and the energy distribution with consistency, can quantitatively reflect the characteristics of acoustic emission signals.5. Selecting the vector involving different temperature granite characteristic parameters of acoustic emission, peak frequency, wavelet packet energy spectrum coefficient and wavelet fractal box dimension, pattern recognition was done by the fuzzy neural network. Water temperature of 100 degrees, natural drying granite acoustic emission signal recognition rate above 90%, 50 degrees temperature acoustic emission signal recognition rate is 75%. |
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