Optimization Of Ventilation On-Demand In Mines Based On Niche Particle Swarm Optimization Algorithm

Mine ventilation is an important process of coal mining,the basic guarantee of mine safety production,and the decisive factor to ensure the normal operation of the mine.Therefore,it is very important to realize the scientific and efficient ventilation system to adjust the air volume of the main mine ventilation site.In this thesis,the adjustable range of wind resistance is determined based on the sensitivity wind regulation theory and the air volume constraint.The demand wind regulation of simple air network is adjusted using the fitting curve method.The concept of second-order air network sensitivity is proposed to quantitatively analyze the mutual disturbance relationship of multi-branch joint regulation process.The optimization of regulation branch combination is realized by using the Taylor expansion theory of air volume change.Based on the niche idea,a particle swarm optimization algorithm based on neighbor mobility strategy was proposed,and an optimization model of complex ventilation network was established.The effectiveness of the algorithm is verified by the actual wind network model of a coal mine.The specific content of this thesis is as follows:In order to ensure the high efficiency in the process of branch wind resistance adjustment,the adjustment of branch wind resistance must be in the sensitive area of wind regulation.Therefore determining the adjustable range of branch wind resistance is the premise of efficient wind regulation.Based on the analysis of the influence of the attenuation rate of the branch resistance sensitivity and the air volume constraint on the adjustable range of the wind resistance,combined with the favorable factors of the two,the method of determining the adjustable range of the branch resistance is proposed,and its shortcomings in the selection of multi-branch adjusting branch and regulating quantity scheme are analyzed,which leads to the follow-up research content.In previous air volume regulation models,only branch sensitivity was considered in the selection of regulation branches,but there was a lack of comprehensive analysis of the adjustable range of wind resistance and the two factors influencing each other.In this thesis,the concept of second order sensitivity is proposed to quantitatively characterize the mutual disturbance in the process of multi-branch joint regulation.Based on the sensitivity of branch selection,adjustable range and the interaction between branches,a new optimization method of adjusting branch combination based on the Taylor expansion approximation of air volume variation was proposed.This method takes more comprehensive factors into consideration when selecting the regulation branch combination in complex ventilation network and has less time complexity.Based on the sensitivity theory,the concept of fan power sensitivity was proposed to represent the influence of wind network branch resistance changes on fan power.Taking fan power consumption as the optimization objective,a particle swarm optimization algorithm（CNMM）based on the concept of niche mobility strategy is proposed,which can provide multiple optimization schemes of wind resistance regulation for mine technicians to choose in the feasible area of wind resistance regulation.Finally,after comprehensive analysis of the time complexity and optimization effect of each adjustment optimization scheme of fitting curve method,feasible solution comparison method and niche particle swarm optimization algorithm,the wind resistance adjustment optimization model of complex ventilation network was established.According to the three air demand conditions of 7303 working face in a coal mine,the combination of single branch,double branch and three branch efficient regulation branches under different air demand conditions is selected,and the adjustable range of wind resistance is determined.When the air volume of 7303 working face needs to be adjusted to?q_137fixed∈[2.0877,2.1]m³/s,the optimal adjustment scheme of branch{615}is obtained by fitting curve method based on the property of fan power sensitivity.When air volume?q_137fixed∈[2.1,3.09]m3/s,using CNMM algorithm to get branch combination{149,615}three kinds of fan power better adjustment scheme,when air volume?q_137fixed∈[3.1,3.9]m3/s,CNMM algorithm is used to obtain four optimal fan power adjustment schemes of branch combination{149,406,615}.Through verification,the adjustment schemes can meet the air adjustment requirements of 7303 working surface,and ensure that the air volume of all branches can meet the air volume constraints.The effectiveness of the regulation scheme is verified.The thesis has 53 images,27 tables,and 75 references.