基于粒子-蚁群混合算法的截割头形状优化设计

Optimization design of cutting head shape based on Particle-Ant Colony Hybrid algorithm

针对EBH-150型横轴式掘进机截割头在截割过程中遇到的载荷波动问题,采用粒子-蚁群混合算法对现有抛物线形截割头进行优化设计。利用Matlab数值模拟软件,对截齿的排列参数进行多目标优化,以期减少载荷波动并提升掘进机的工作稳定性。优化结果显示,截割头的截线间距经过调整后,从外向内逐渐减小,使得单个截齿受力更为均匀。横向载荷波动降低了约62%,其他方向的载荷波动也显著降低,均超过50%。这些改进有效提高了掘进机横摆进刀的稳定性,并有助于延长截割头的使用寿命。尽管优化后的截割头在某些方向上的载荷均值有所增加,但载荷峰值降低,避免了单个截齿的过载现象。总体而言,优化设计取得了理想的效果,但仍需通过实际应用进行验证。本研究为掘进机截割头的优化设计提供了一种有效的算法支持,对于提高掘进机的工作效率和安全性能具有重要意义。

In addressing the issue of load fluctuations encountered by the cutting head of the EBH-150 type horizontal axis tunneling machine during the excavation process,this study employed a hybrid Particle-Ant Colony Optimization algorithm to refine the design of the existing parabolic-shaped cutting head,By utilizing the numerical simulation software Matlab,a multi-objective optimization of the arrangement parameters of the cutter teeth was conducted,aiming to diminish load fluctuations and enhance the operational stability of the tunneling machine,The optimization outcomes revealed that the spacing of the cutting lines was adjusted to gradually decrease from the exterior towards the interior,resulting in a more uniform distribution of force on each cutter tooth,There was a 62%reduction in lateral load fluctuations,and significant reductions in load fluctuations in other directions as well,all exceeding 50%,These enhancements effectively improved the stability of the machine's lateral cutting entry and contributed to extending the lifespan of the cutting head,Although there was an increase in the average load in certain directions following the optimization,the peak load values decreased,preventing the overload phenomenon of individual cutter teeth,Overall,the optimization design achieved desirable results,yet its efficacy still requires validation through practical application,This research provides effective algorithmic support for the optimization design of tunneling machine cutting heads and holds significant implications for improving the work efficiency and safety performance of tunneling machines.