悬臂式掘进机断面成型轨迹多目标优化方法研究

断面成型是掘进过程的重要工序,传统的断面轨迹仅以轨迹最短为目标,且一旦确定不再改变,制约掘进机器人的发展。为此,本文针对常见及复杂构造断面,提出了悬臂式掘进机断面成型轨迹多目标优化方法。首先,以效能和安全为目标,建立了截割轨迹多目标优化模型,考虑实际截割工况,确定了模型中决策变量、目标函数以及约束条件;其次,为进一步提高优化解的收敛性及分布性,提出了基于知识库精简的多目标粒子群算法(FDMOPSO算法);最后,基于FDMOPSO算法对截割轨迹多目标优化模型进行求解。经仿真验证,算法的收敛性提高了约90%、分布性提高了约40%,且对于不同形状、大小的复杂构造巷道断面都可以规划得到截割轨迹解集,并以效率、安全和截割平滑性为依据,最终决策得出最优轨迹。优化之后的截割轨迹,既能提高截割效率,同时可以做到避免夹矸,增加了截割的安全性。

A multi-objective optimization method for cantileverroadheader section forming trajectory

Section forming is an important process in the tunneling process. Traditional section trajectory only aims at the shortesttrajectory and it will not change once determined, which restricts the development of tunneling robots. For this reason, this paperproposes a multi-objective optimization method for the cutting trajectory of the cantilever roadheader for common and complex structuralsections. Firstly, taking efficiency and safety as the goal, a multi-objective optimization model of the cutting trajectory is established.Considering the actual cutting conditions, the decision variables, objective functions and constraints in the model are determined.Secondly, in order to further improve the convergence and distribution of the optimized solution, a multi-objective particle swarmoptimization based on fitness distance to simplify knowledge base ( FDMOPSO) is proposed. Finally, the multi-objective optimizationmodel of the cutting trajectory is solved based on the FDMOPSO algorithm. Simulation results show that the convergence and distributionof the algorithm are improved by about 90% and 40% , respectively. It also verified that the cutting trajectory solution set can be plannedfor complex structure roadway sections of different shapes and sizes. Based on efficiency, safety and cutting smoothness, the optimaltrajectory can be finally determined. The optimized cutting trajectory not only improves the cutting efficiency, but also avoids dirt bandtrapping and increases the safety of cutting.