Research On Coal Mine Personnel Positioning System Based On Visible Light

Coal mine resources are related to Chinese social construction and private life,while our coal resources are mostly distributed in the underground.Therefore,the safe production of coal and the establishment of safe underground coal mine positioning system have aroused a great national attention.Compared with existing positioning technologies such as WiFi,Bluetooth,radio frequency identification,visible light communication positioning system has the advantages of rich spectrum resources,low cost,anti-electromagnetic interference,high communication security and strong compatibility.Based on this situation,we establish a coal mine underground positioning system for complex and variable coal mine environment based on visible light communication.The main work of this thesis are as follows:In view of the two-dimensional positioning of visible light in coal mine,we use Monte Carlo algorithm to analyze the multipath reflection in underground coal mine and propose to select the optimal receiving angle of view to reduce the received interference power.We use the Kalman filter algorithm to optimize the received power and analyze the visible light communication model under tilt.After that,we use the improved centroid weighting algorithm to simulate the two-dimensional positioning of the coal mine.The simulation results shows that the maximum error of two-dimensional positioning is reduced from 7.3cm before the optimization to 2.6cm,and the average positioning error is reduced from 4.6cm before the optimization to 2.03 cm.At the same time,it is verified that the layout pattern of the LED array has a great influence on the positioning accuracy and optical power distribution.In view of the problem of uneven illumination and power distribution in the coal mine.We propose a layout mode to divide the large LED array into small LED arrays and distribute them evenly on the emission plane.By studying the influence of the distance between the arrays and the half power angle on the system performance,we use the genetic algorithm to optimize the system parameters.And aiming at the disadvantage of traditional genetic algorithm,we improve the selection process,crossover and mutation operations.And compared with the existing methods of optimizing the uniformity of received power,the proposed method has better optimization effect.The simulation results show that the received power variance of thereceiving plane is reduced from 3.02 before the optimization to 1.16 and the range of illumination intensity from 374 ~ 862 lx is improved to 417 ~ 765 lx.In view of the problem of poor positioning performance and long time consumption in the existing visible light three-dimensional positioning system,we propose a three-dimensional visible light localization system based on improved immune particle swarm optimization algorithm.By improving the weighting factors and learning factors in the particle swarm algorithm,the immune algorithm is integrated.The simulation results show that the average positioning error of the indoor three-dimensional positioning system based on the improved immune particle swarm optimization algorithm is 3cm,and the positioning time is 2s.Compared with the existing three-dimensional positioning system,the positioning accuracy and convergence speed are significantly improved.