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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.
The energy consumption of cobalt-rich crusts collected at 6km underwater is an outstanding problem.The design variables are the walking speed of the collecting head, the cutting speed of the drum, the cutting depth and the cutting distance of the picks, and the minimum cutting energy consumption As the goal, the optimization design model of the working parameters of the collecting head is established.Design fuzzy controller is embedded into the genetic algorithm to control the automatic adjustment of the crossover rate and mutation rate, the fuzzy genetic algorithm is used to optimize the model to get the optimal cutting depth, The cutting distance, the traveling speed of the mining vehicle, the cutting speed of the collecting head and the minimum power were 3.0993cm, 5.5979cm, 0.2889m / s, 0.3535m / s and 149.6229kW, respectively. The pool test showed that the optimization results were satisfactory. 2, reference 8.