大洋富钴结壳实时开采切削深度优化分级模型研究

Study on multilevel model of optimized cut depth in real-time mining of ocean cobalt-rich crusts

根据统计分形理论对大量实验测得的微地形数字高程数据进行了分维空间、无标度区和分形维数等分析和计算,并求出了各自的地形特征数据,同时建立了单个微地形在控制废石混入率时富钴结壳开采的最优切削深度的遗传寻优算法。在此基础上,利用实验所得各种分形特征数据及微地形的自相似性、各向异性及分形布朗函数,通过计算机自动生成了大量仿真微地形,并求出了各相应仿真微地形的地形特征数值和在控制废石混入率时富钴结壳开采的最优切削深度,再通过对此大样本的统计回归分析,建立了大洋富钴结壳实时开采切削深度的优化分级模型。该模型经实验数据的验证,其结果达到了满意的要求。

On the basis of statistical fractal theory, we analyze and compute the dimension space, scale ranges and fractal dimensions of a large number of tiny-terrain digital-elevation-model （DEM） data which are got from experiments, and get their terrain-characteristlc data. At the same time, we build the Genetic Algorithm （GA） for searching for optimized cut depth in the mining of cobah-rich crusts of single tiny terrain when the waste in-ore rate is under control. Moreover, with the help of various experimental fractal-characteristic data, the self-similarlty, direction-dissimilarity of the tiny terrain and Fractal-Brownian-Movement （FBM） Function, we use the computer to generate automatically a large number of imitated tiny-terrains, get their terrain-characteristic values and optimize the cut depth in the mining of cobah-rich crusts when the waste in-ore rate is under control. And through statistical analyses of large samples, a multilevel model of the optimized cut depth in the realtime mining of ocean cobalt-rich crusts is constructed. The computation of actual data proves the validity of this model.