KEYWORDS: Mining, Clouds, Signal processing, Safety, Power supplies, Data acquisition, Product safety, Telecommunications, Solar processes, Network landslides
With the deepening of the depth of open-pit mining, the country's open-pit mining gradually into the deep depression mining stage, the number of high and steep rock slopes increased, landslide accidents frequently occur. Landslide accident has become a major hidden danger in open-pit mine safety production. Microseismic monitoring technology has been widely recognized by the industry as an effective slope monitoring and early warning means covering the whole mine. In this paper, a wireless microseismic monitoring scheme is formed through wireless bridge technology and solar power supply technology, which is successfully implemented in an open-pit mine slope monitoring. The data processing and analysis results are uploaded to the cloud service platform in real time. The wireless microseismic monitoring system based on cloud service platform runs stably, successfully solving the problem of long-term stable operation of the open-pit slope monitoring system and ensuring the safety of mine production.
KEYWORDS: Sensors, Mining, Error control coding, Clouds, Error analysis, Safety, Network architectures, Land mines, Design and modelling, Data processing
With the increasing depth of open pit mining in our country, a large number of high and steep slope is produced, slope stability problem has become increasingly prominent, landslide accident has become a major hidden danger in surface mining safety production. As an effective slope monitoring and early warning method covering the whole mine, microseismic monitoring technology has been widely used. In this paper, the location accuracy of the source of microseismic monitoring on open-pit slope is quantitatively evaluated through the research of the slope location error control method. The effectiveness of the slope microseismic location error control method is verified through the fixed point blasting inside the network, which provides effective guidance for the microseismic data processing, so as to improve the location accuracy of slope microseismic. Rock fracture source location results are sent to the microseismic monitoring cloud service platform in real time. In order to improve the accuracy of rock mass stability analysis, so as to ensure mining safety.
At present, the mine microseismic monitoring system mostly adopts the mean velocity model and absolute positioning method, and the source positioning error is large, which seriously affects the later processing interpretation and risk assessment, it is difficult to meet the refined management requirements of deep mining ground pressure risk. In response to this situation, the velocity partition model is established, which makes the velocity model more fit with the velocity structure characteristics of the complex rock mass in the microseismic monitoring area underground mine (mine roadway, cavity, ore body, surrounding rock mass, etc.), so as to improve the picking accuracy of microseismic wave arrival time. Finally, the mine site data is used to carry out the IMS micro-seismic monitoring system positioning results and the source location results in this paper benchmarking. The results show that the relocation results obtained by the micro-seismic location of velocity partition based on the 3D stations underground mines are more reliable and more accurately match the high-risk areas during mining.
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