Abstract
The danger of downhole work is mainly due to the chemical toxic gases and flammable gases NO2, CO, SO2, H2S, CH4, CO2, etc. When the concentration reaches a certain value, it will produce very great harm. With the continuous development of sensor technology and communication technology, it is necessary to monitor the relevant geographic features below the ground. Because of the complex environmental parameters of the coal mine roadway and the interference caused by various electrical equipment, the transmission of mine electromagnetic signals will be affected, resulting in low positioning accuracy. However, the underground chemical gas leakage leads to the life of underground workers which cannot be guaranteed, so it is necessary to effectively monitor the concentration of chemical gas components in underground mines. In this paper, a moth flame algorithm based on optimized inertia weights is proposed. By continuously improving the local inertia weights, the global optimum is determined by using the change of inertia weights in the iterative process of the algorithm. By testing the convergence and optimal value of several algorithms under common test functions, IMFO can obtain the global optimal solution. Finally, the concentrations of chemical gases NO2, CO, SO2, H2S, CH4, and CO2 are monitored by setting specific areas to see if they reach the early warning values. Then, 16 coordinates in the region are used to predict the above method, and the IMFO algorithm can achieve the best prediction effect.
Highlights
Because the mining operation of coal resources is below the ground and has high harmfulness, there are still hundreds of people who pay their lives due to coal mining every year, and major accidents often occur
Due to the complex environmental parameters of the coal mine roadway and the interference caused by various electrical equipment, the transmission of mine electromagnetic signals will be affected, resulting in low positioning accuracy [1]
Whether the massive data generated under the above technical background can accurately measure the specific position has become a hot spot in the research of the positioning algorithm
Summary
Because the mining operation of coal resources is below the ground and has high harmfulness, there are still hundreds of people who pay their lives due to coal mining every year, and major accidents often occur. On the other hand, based on the theoretical model of wireless transmission signals, the weighted average value of the attenuation index of signal transmission paths is obtained periodically and optimized in combination with the genetic algorithm This method is an intelligent swarm algorithm, a hot issue studied [5]. Aiming at the problem of low matching positioning accuracy such as MSD and MAD [9], the MPMD matching algorithm based on the feature vector product is used to improve positioning accuracy, and the results are better in error and pit noise. Literature [12] is aimed at the problems of unstable WLAN information and low positioning accuracy in narrow space; it is proposed to fuse GPS and WLAN data information, sample the integrated data, and realize particle weight by combining the Kalman filter and map. The performance of the improved IMFO algorithm is compared with those of other algorithms
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