Research On Monitoring And Data Processing Of Non-coal Mine Mountain Pressure Disaster By Wireless Sensor Network

With the rapid development of China’s economy,the demand for non-coal resources is increasing day by day.High intensity mining leads to frequent ground pressure disasters and accidents,which brings huge economic losses and a large number of casualties to our country.In order to ensure the safe mining of non-coal mine resources,it is urgent to monitor the non-coal mine mountain pressure disaster in real time.At present,non-coal mine underground mainly adopts wired monitoring.This method not only takes time and labor to deploy,but also has problems such as inconvenient maintenance,poor reliability and poor robustness.Wireless sensor network(WSN)has the advantages of self-organization,small volume and low cost,which is very suitable for non coal mine underground environment.WSN is applied to the monitoring of underground non-coal mountain pressure disaster,and three key technologies of wireless sensor network node location,data transmission and data fusion are studied by theoretical analysis and simulation.(1)WSN location algorithm based on improved bird swarm optimization.Firstly,several anchor nodes closest to the node are used to limit the area,and then the random inertia weight is used to improve the foraging behavior of the bird swarm algorithm.The method of selecting the best individual is used to replace the random selection method in the original algorithm to improve the warning behavior of the bird swarm algorithm.Finally,the improved bird swarm algorithm is used to search and solve in the limited area to complete the node location.Simulation results show that the algorithm has high positioning accuracy and strong error resistance.(2)Non-uniform clustering routing and transport protocol based on dynamic competitive radius.Firstly,the threshold formula of the LEACH protocol is improved by using the distance and energy factors.Secondly,the successor energy consumption factor and the predecessor energy consumption factor are introduced into the calculation of the competition radius.Finally,the remaining energy of nodes is used to simplify the next round of cluster head election and reduce the network energy overhead.The simulation analysis shows that the energy consumption of the network is more balanced and the survival time of the network is longer.(3)WSN data fusion algorithm based on fireworks optimized neural network.Firstly,the Tent chaotic graph is used in the firework algorithm to improve the initial position distribution of the firework population,so that the initial firework distribution is more uniform.Then,the weight matrix,threshold matrix and other parameters of the BP neural network are optimized by the improved firework algorithm for data fusion.The simulation results show that,compared with other algorithms,this algorithm improves the accuracy of data fusion,reduces network energy consumption,and prolongs network life cycle.