Optimization And Control Of Mine Ventilation System Based On PSO Algorithm

Most of the current coal mines in China are deep underground,which is the reason that it has to be mined underground,so it is necessary to establish a safe and reliable coal mine ventilation system for underground mining.Coal mine ventilation system is one of the key factors of coal mine safety and an important part of coal mine enterprises'energy consumption.The stable,safe and efficient operation of coal mine ventilation system is of great significance to coal mine safety production,energy conservation,emission and cost reduction.Firstly,the importance of coal mine ventilation system in coal mine safety production,and the significance of its optimized regulation to coal mine safety,energy conservation,emission reduction and management level improvement were analyzed in this dissertation.The method of main fan switchover with air-flow stabilization underground was presented.The equivalent model of the side of main fan of the ventilation system and the optimal control model of the main fan switchover with air-flow stabilization were established.Based on graph theory,the optimization and regulation model of complex ventilation network to reduce energy consumption for air-flow on-demand were built,and in the manner of hybrid regulation and control by regulating pressure and resistance,the regulating and controlling method of hybrid complex ventilation network with multi-objective optimization,which are construction investment cost,energy consumption and profit loss,were put forward,and the model of multi-objective optimization and regulation to hybrid complex ventilation network were built..Secondly,the improved particle swarm optimization(PSO)algorithm was proposed to optimize and control the complex ventilation system in view of the fact that the traditional algorithm cannot satisfy the requirements of large-scale,multi-variable,multi-constraint,multi-peak,nonlinear and non-convex complex problems such as complex ventilation network.Imitating the hierarchical structure of the integrated system and biological behavior of heterogeneity,a new type particle swarm optimization with extended hierarchical heterogeneous(EH~2PSO)was proposed,in which the hierarchical structure,the particle heterogeneous behaviors are employed and"refining""exploring"factors are adopted to extend particle exploring ability,the hierarchical structure is used to enhance the capacity of sharing information between particles,and particle heterogeneous behavior selection from the behavior pool including five types PSO algorithm,such an standard PSO(SPSO)and others,based on the population congestion and early stagnation detecting.The performance of EH~2PSO algorithm was tested and compared by benchmark functions,and the superiority of the algorithm was proved.Thirdly,based on the established model of main fan switchover with air-flow stabilization,the Fuzzy-PID and Constraint Planning control strategy and EH~2PSO algorithm of main fan switchover with air-flow stabilization underground was proposed and the Fuzzy reasoning rules of air-flow were established.The influence of air-door angle adjusting step length interval on air-flow variation underground was studied.The results showed that the air-flow stabilizing and reversing method of coal mine main fan controlled by EH~2PSO algorithm can keep the variation of air-flow underground to a minimum(less than 0.8%).The optimal control system of main fan switchover with air-flow stabilization underground was developed and proved to be stable by practical application.In addition,based on the algorithm adaptation idea of the informed solution guiding particles to converge rapidly to the global optimal solution,the corner solution was introduced into the population of SMPSO algorithm to form the Corner-SMPSO.To the corner solutions of the optimization problem,a method of transforming multi-objective into bi-objective optimization was presented,and the method of solving corner solution and its effectiveness were discussed for different Pareto frontier types,The corner solution solving method of multi-objective problem with bi-objective SMPSO was developed.Based on the DLZT series of benchmark functions,a comparative study was conducted on the Corner-SMPSO algorithm with or without corner solutions and when it is introduced.It was proved that the performance of the multi-objective search algorithm after the introduction of corner solution is greatly improved in convergence speed and solution accuracy,and there is no obvious effect on the performance of the algorithm when using the different corner solution introduction time.Finally,an optimization method of complex coal mine ventilation network based on EH~2PSO algorithm was proposed to reduce its energy consumption.With using other three types PSO algorithm,such as Clerc's Constricted PSO,the comparative study on the optimal regulation of four types algorithm including EH~2PSO was conducted,whose results show that the optimization and regulation of complex coal mine ventilation network with EH~2PSO algorithm obtains the best performance of algorithm convergence and solution accuracy.With EH~2PSO algorithm,the optimization and regulation of hybrid complex ventilation network with multi-fan can make the lowest power consumption.A multi-objective optimization and regulation method for hybrid complex ventilation network based on the Corner-SMPSO algorithm was proposed.Considering the ventilation energy consumption,construction investment cost and profit loss of production stoppage due to ventilation network renovation,taking the domestic hybrid complex ventilation network with multi-fan as an example,the Corner-SMPSO algorithm is used to carry out multi-objective optimization of the hybrid complex ventilation network,which provides decision-making basis for the operation and management of coal mine ventilation network.The experimental results provide a set of multi-objective optimal solutions for decision making of coal mining enterprises.This dissertation has 50 figures,31 tables and 147 references.