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Mine Seismic Activity and Chaotic Time Series Analysis

Author: JiangJiaoLian
Tutor: TangLiZhong
School: Central South University
Course: Safety Technology and Engineering
Keywords: Seismic activity Chaotic time series Phase Space Reconstruction Lyapunov exponent RBF Neural Network
CLC: P315
Type: Master's thesis
Year: 2011
Downloads: 68
Quote: 0
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Abstract


Application microseismic technology Dongguashan copper mine monitoring of seismic activity, people are concerned about the pluton whether the earthquake activity, and even the phenomenon may lead to pressure position, time and degree of instability, if predict specific future time of seismic activity circumstances, come to change the basic law of the seismic activity, the lives of the miners and mine safety production has a very important significance. This paper uses quantitative seismology and statistically the energy - seismic moment features, frequency - magnitude of the laws of the statistical analysis; then using phase space reconstruction of chaotic time series theory of mine seismic activity time series attractor recovery from attractor found the original system of law restored; Finally, use the RBF neural network modeling and prediction of mine earthquake intensity, achieved the ideal result. The main research results are as follows: (1) Dongguashan copper seismic activity schedule analysis and parametric statistics: according to the instance to investigate the distribution law of mine earthquake; discussion the melon Copper seismic activity frequency - magnitude, energy - seismic moment distribution law, found that both the existence of two distribution patterns; (2) mining seismic activity time sequence of phase space reconstruction study. Essence of Chaos brief, were used to determine the two important parameters for reconstructing phase space autocorrelation method and saturation correlation dimension method: delay time and embedding dimension. The calculation results show that the seismic moment and seismic energy time delay basically at 2-3, embedding dimension values ??are 6-8 dimensional. Two-dimensional reconstructed trajectories revealed a bimodal distribution mode, three-dimensional reconstruction of trajectories \Lyapunov exponent, correlation dimension chaotic system features two important amount of time series Chaos Characteristics of quantitative discriminant judgment results showed that the seismic activity time series Dongguashan copper really belongs chaotic time series; (4) to study the mining seismic activity the forecast time. Mine earthquake activity calculated using the maximum Lyapunov exponent forecasting time; (5) establish the RBF neural network model for predicting chaotic time series, forecasting results show that to remove some rare cases, the predicted results are consistent with the actual situation.

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CLC: > Astronomy,Earth Sciences > Geophysics > Earth ( rock circles ) physics ( geophysics ) > Seismology
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