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Disaster Monitoring and Warning in Mining Process of Multi-disasters Underground Mine

Author: CuiXiuJing
Tutor: DengHongWei
School: Central South University
Course: Safety Technology and Engineering
Keywords: Underground mine with multi-disasters Disastersmonitoring and early-warning system Monitoring and controlling Disaster prediction and forecast Model optimization
Type: Master's thesis
Year: 2012
Downloads: 189
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Focused on underground mine with multi-disasters, the paper discussed its category and characteristics, analyzed the disasters, the rules of disaster development and their procedures as well as the derivative chains. Based on the monitoring technology of disasters and early warning theory, combining with some engineering cases, established the disasters monitoring and early-warning system which is appropriate for mine with multi-disasters. The main contents and results are as follows:(1)The definition of underground mine of multi-disasters was elaborated. Moreover, the characteristics and the inoculation mechanism of disasters, as well as its deribative relationships that were under the condition of disturbance, were analyzed in this kind of underground mine.(2) Depending on the characteristics of disasters and derivative chains of disasters, the overall framework of the system of disasters monitoring and early-warning being appropriate for mine with multi-disasters were stuctured. The monitoring objects of comprehensive monitoring system of disasters were determined based on fuzzy multi-attribute decision making method. Based on the overall framework, the comprehensive system of disasters monitoring adopting Zigbee technology and wireless sensor network were built in a mine with multi-disasters.(3) The other monitoring system of ground pressure were built in underground artificial structure of some mine with multi-disasters, on the basis of characteristics of the reconstructed mining environment and the overall framework of the system of disasters monitoring and early-warning. The BP neural network&GM(1,1) model combination forecasting model for displacement prediction of underground artificial structure and predicting model for stress of underground artificial structure based on BP neural network were constructed in Matlab and EasyNN-plus. By using the random global search and optimization function of genetic algorithm, to optimize the BP neural network&GM(1,1) model combination forecasting model in Matlab, which improved the prediction performance of combination forecasting model. (4) In accordance with the numerical simulation parameters of underground artificial structure, the early warning deadline of early warning indexes, the prediction method of ground pressure, and the alarming model of ground pressure were devised. The disasters monitoring and early-warning system can early warning the ground pressure of underground artificial structure, which demonstrated the reliability of the system.

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CLC: > Industrial Technology > Mining Engineering > Mine the pressure and support > Rock pressure and rock movement
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