Research On Mine Water Inrush Monitoring System Based On Laser Induced Fluorescence

With the increasing depth of coal mining,coal production will encounter all kinds of security and disaster.A sudden influx of groundwater of mine water inrush phenomenon that is generally ferocious,often floods the tunnel in a short period of time,brings harm to mine production and causes casualties and serious economic losses.Now,water disaster has become one of the most important risks that threaten the life and property safety of the coal mine.In the face of serious water hazards,we urgently need for prevention and control of water early warning disaster,In view of this situation,this paper uses the combination of geochemical exploration and monitoring,and puts forward the mine water inrush monitoring system based on laser induced fluorescence technology.The system uses the technology of laser-induced fluorescence spectra,obtaining fluorescence intensity of real-time measurement of mine water source and luminous flux variation of the wavelength of the emitted light.We can identify the composition and content of identification of material elements.By pH and conductivity,water inflow and water parameters real-time monitoring,according to the parameters of water supplemented by conventional chemical mutation,we can determine water source.Using RBF neural network(radial basis function neural network)to carry on the discrimination model establishes the comprehensive coal mine water inrush source discrimination model.The system has been successfully applied to coal mine,Datong Coal Mine 8306 working face 8401.After installation has been running for 10 months,the data acquisition system acquires sensor information,we realize remote real-time monitoring of mine working face water quality information,using data communication substation by fiber network transmission to the computer on the ground.The test results show that the system is reasonable in design,stable in operation and high in precision of measurement data.The packet loss rate is 0.93%and the relative error of PH and conductivity is between 0.42%and 0.52%.For a long time,the monitoring has shown that 8306 and 8401 PH in the goaf water stably at around 6.5,the conductivity stably at 2105 about s/cm,oxygen 2%,the spectral characteristics of stability.By the RBF neural network model,we can determine the goaf water,and find no obvious external water intrusion.This system firstly uses online multiple parameter water quality sensor,designing a set of mine water quality monitoring system based on CAN network.The system by the sensor nodes collects spectral characteristics,pH value and conductivity,dissolved oxygen concentration and other parameters.The use of bus technology data by the network gateway will transmit the information to the computer on the ground,realizing remote real-time monitoring of coal mine working face the water quality information,and applying the system of Datong Coal Mine Group operation in good effect.This system is significant of water inrush warning of major online,providing decision-making basis for the prediction of mine water inrush disaster.It has important scientific significance for the mine disaster prevention and safety production of coal mine based on the theory and methods of research.