基于改进粒子群算法的采煤工作面顺槽顶板支护参数优化研究OA

Aiming at the poor adaptability and low support efficiency of the traditional design method for roof support parameters of gateways in coal mining faces under complex geological conditions,an optimization method for support parameters based on the improved particle swarm optimization algorithm was proposed in this paper.First,mechanical parameters and failure criteria of roof strata were determined through the analysis of engineering geology and mechanical characteristics,which provided a theoretical foundation for optimization.Second,key decision variables such as bolt length and spacing as well as their value ranges were defined.Finally,a comprehensive optimization function was established with roof subsidence,support resistance and material cost as the objectives,and the multi-objective problem was converted into a weighted single-objective problem.On this basis,the standard particle swarm optimization algorithm was modified by introducing dynamic inertia weight and adaptive mutation operator.The global search ability and the capability to escape from local optima were enhanced,and the efficient optimization of support parameters was therefore realized.The gateway of No.23225 Face in Yili Xinkuang Mine was taken as an example for application analysis.The results showed that the support resistance efficiency index of the optimized scheme was increased by 70.8％,the roof subsidence was reduced obviously,and the stability fitness was closer to 1.The effectiveness and engineering applicability of the proposed method in improving support performance and economic benefits were verified.This study provided a scientific reference for the gateway support design under complex geological conditions.