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针对刨煤机载荷波动率、刨削比能耗及生产能力问题,根据刨煤机刨削参数和刨头结构参数,并借助改进粒子群算法对刨煤机多目标进行优化设计。优化结果表明:刨煤机载荷波动率降低了20%、刨削比能耗降低了9.8%,生产能力升高了2.5%,极大地优化了上行刨削深度、下行刨削深度、上行刨速、下行刨速、刨刀数量和刨刀间距,有效地提高了刨煤机的整机工作性能。对比不同的优化算法,采用改进粒子群算法优化的刨煤机的综合性能优于其他算法。
According to the plow load fluctuation rate, the energy consumption ratio and the production capacity of the plow, the plow optimization model is designed according to the plow parameters and the plow structural parameters of plow and the improved particle swarm optimization algorithm. The results show that the plow load fluctuation rate is reduced by 20%, the cutting energy consumption is reduced by 9.8% and the production capacity is increased by 2.5%, which greatly optimizes the effect of the upstream planing depth, the downstream planing depth, the upstream planing speed , The downstream planing speed, the number of planing knives and planer spacing, effectively improve the plow machine work performance. Comparing different optimization algorithms, the overall performance of plows optimized with improved particle swarm optimization is superior to other algorithms.