论文部分内容阅读
为了降低刨煤机刨削比能耗、刨链损伤、刨刀磨损及提高日生产量,选择上行刨削深度、下行刨削深度、上行刨速、下行刨速、刨链预紧力为设计参数,采用改进NSGA-Ⅱ(Non-dominated sorting Genetic Algorithms)算法对刨煤机进行了多目标优化设计。优化结果表明:刨煤机比能耗降低了16.7%,刨刀磨损量降低了17.1%,刨链损伤降低了13.6%,日生产能力提高13.9%,大幅优化了刨煤机刨削参数及运行参数,有效提高了刨煤机的整机工作性能,为刨煤机的设计及改进提供了理论依据。
In order to reduce the plow planing than the energy consumption, planing chain damage, planing wear and improve daily production, select the amount of upward planing depth, down planing depth, upward planing speed, down planing speed, planing chain preload for the design parameters , The multi-objective optimization design of the plow was carried out with the improved Non-dominated sorting Genetic Algorithms (NSGA-Ⅱ) algorithm. The results show that the specific energy consumption of the plow is reduced by 16.7%, the wear loss of the plow is reduced by 17.1%, the damage of the chain saw is reduced by 13.6% and the daily productivity is increased by 13.9%. The planing parameters and operating parameters , Which effectively improves the working performance of the plow and provides a theoretical basis for the design and improvement of the plow.