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为优化掘进机铲板参数,建立了装载能力、铲掘力与铲板参数之间的数学模型;确立了装载能力、铲掘力的灰色权重;采用粒子群优化算法,对铲板参数进行了多目标优化;对多目标的处理提出了采用理想点法与灰色权重相结合的方法,并对优化前后铲板进行了仿真分析和对比,表明铲板优化后取得了良好的优化结果。为掘进机铲板的设计提供一定的理论依据和参考价值,为工程中处理多目标优化问题提供一定的借鉴。
In order to optimize the parameters of roadheader shovel, the mathematic model between loading capacity, shoveling force and shovelboard parameters was established. The gray weight of loading capacity and shoveling force was established. The parameters of shovelboard were optimized by particle swarm optimization Multi-objective optimization. The multi-objective processing method is proposed by using the combination of the ideal point method and the gray weight. The simulation analysis and comparison of the optimized front and rear shovels show that the optimized optimization results of the shovel board are obtained. It provides some theoretical basis and reference value for the design of heading machine’s shovel board, and provides some reference for dealing with multi-objective optimization problems in engineering.