基于PSO-GACA的采煤机螺旋滚筒参数优化设计

为了改善滚筒采煤机的装煤性能、增加采煤机的块煤率、提高其产煤经济效益,以叶片外缘直径、内、外螺旋升角、滚筒转速和采煤机牵引速度为设计变量,选择装煤生产率最大和吨煤售价最高作为目标函数,建立了各种几何约束及性能约束,采用粒子群算法和蚁群算法的混合算法(PSO-GACA算法)对螺旋滚筒的参数进行优化设计。结果表明,在保证滚筒不发生堵塞、抛煤距离合理等条件下,优化后的采煤机装煤生产率提高14.5%,块煤率增加13.2%,吨煤售价可提高0.75%。

Parameter optimization design of screw drum for drum shearer based on PSO-GACA algorithm

In order to improve coal loading performance,increasing the lump rate of a drum shearer and enhancing its coal production economic benefits,parameters of the outer edge diameter of the blade,inside and outside spiral rising angles,drum rotating speeds and dragging velocity were used as design variables,the largest coal loading productivity and coal price highest were chosen as optimal objective and various geometric constraint and performance constraint were set for optimization design of a screw drum of a shear.Particle swarm optimization algorithm and ant colony algorithm hybrid optimization(PSO-GACA algorithm) were used to solve this optimization design.The optimized results indicate that the productivity of loading coal can be increase by 14.5%,the lump coal rate increases by 13.2%,coal price can be enhanced by 0.75% when the screw drum is not jammed and the casting distance of lump coal is reasonable.