Optimal control of cobalt crust seabedmining parameters based on simulated annealing genetic algorithm  

作　　者：夏毅敏 张刚强 聂四军 卜英勇 张振华 

机构地区：[1]School of Mechanical and Electrical Engineering,Central South University [2]Guangxi Liugong Machinery Co.Ltd

出　　处：《Journal of Central South University》2011年第3期650-657,共8页中南大学学报（英文版）

基　　金：Project(50875265) supported by the National Natural Science Foundation of China;Project(20080440992) supported by the Postdoctoral Science Foundation of China;Project(2009SK3159) supported by the Technology Support Plan of Hunan Province,China

摘　　要：Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.Under the condition of the designated collection ratio and the interfused ratio of mullock,to ensure the least energy consumption,the parameters of collecting head (the feed speed,the axes height of collecting head,and the rotate speed) are chosen as the optimized parameters.According to the force on the cutting pick,the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head,the optimized design model of collecting head is built.Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 cm,then making use of the improved simulated annealing genetic algorithm (SAGA),the corresponding optimized result can be obtained.At the same time,in order to speed up the controlling of collecting head,the optimization results are analyzed using the regression analysis method,and the conclusion of the second parameter of the seabed microtopography is drawn.

关 键 词：cobalt crust mining parameter specific energy consumption simulated annealing genetic algorithm 

分 类 号：O232[理学—运筹学与控制论] TP18[理学—数学]