【摘要】 在6km水下采集富钴结壳,其能耗是一个突出的问题.以采集头的行走速度、滚筒切割速度、切削深度及截齿的截线距为设计变量,以采集头最小切削能耗为目标,建立了采集头工作参数优化设计模型.设计模糊控制器嵌入到遗传算法中控制交叉率、变异率的自动调整,利用模糊遗传算法对模型进行优化,得到最优切削深度、截齿的截线距、采矿车行走速度、采集头切割速度及最小功率分别为3.0993cm、5.5979cm、0.2889m/s、0.3535m/s和149.6229kW.水池试验证明优化结果令人满意.图6,表2,参8.更多还原

【Abstract】 Energy consumption is an important problem when cobalt-rich crusts are mined under 6 000 meters seabed.Using cutting depth,distance of picks,feeding speed and rotation speed of mining head as design variants,aiming at minimum cutting energy consumption,a process parameters optimizing model of mining head was established.Fuzzy controllers were embedded to the genetic algorithms to control the crossover probability and the mutation probability.The fuzzy genetic algorithms(FGA) were used to solve the optimization model.The optimal results are as follows: cutting depth,distance of cutting teeth,marching speed,rotation speed and cutting power are 3.099 3 cm、5.597 9 cm、0.288 9 m/s、0.353 5 m/s and 149.622 9 kW respectively.The experiments which were completed under a water pool of 8 m depth indicate that the optimized result is satisfactory,and the optimized results provide theoretical reference for selecting work parameters of mining head.6figs.,2tabs.,8refs.更多还原