基于粒子群算法的采煤机单向示范刀采样轨迹规划

Based on Particle Swarm Optimization Planning of Shearer Sampling Trajectory of Single Demonstration Cutter

考虑到采煤工艺和工作面的设备适应能力的限制,为提高单向示范刀采样轨迹与记忆截割轨迹的吻合度,探讨单向截割信息转换为双向截割信息的条件,建立基于粒子群算法截割轨迹规划数学模型,通过粒子群算法对截割参数进行规划,给出采煤机顶板记忆截割轨迹,利用Matlab软件对滚筒超调截割岩石或过低留顶煤的单向示范刀采样轨迹进行规划。

Taking into account mining technology and adaptability limitations of working face equipment, to improve the goodness of fit of trajectory of single demonstration cutter sampling and memory-cutting, discussed conditions of single demonstration cutter information converted to bidirectional demonstration cutter information, a cutting trajectory planning mathematical model which based on particle swarm algorithm is established, and then planning cutting parameters by particle swarm optimization, given memory-cutting trajectory of roof, use Matlab software to planning single demonstration cutter sampling trajectory of drum over adjustment cutting rock or low stationary coal roof.