Optimization methods of cutting depth in mining Co-rich crusts

Xuan-yun Qin , Ji-hong Guan , Bo Ren , Ying-yong Bu

Journal of Central South University ›› 2007, Vol. 14 ›› Issue (4) : 595 -599.

PDF
Journal of Central South University ›› 2007, Vol. 14 ›› Issue (4) : 595 -599. DOI: 10.1007/s11771-007-0114-0
Article

Optimization methods of cutting depth in mining Co-rich crusts

Author information +
History +
PDF

Abstract

For optimizing the cutting depth of spiral drum type cutting head, the relations among collecting ratio, interfusing ratio of mullock and cutting depth of the mining cobalt-rich crusts in ocean were discussed. Furthermore, the multi-extremum problem about cutting depth was analyzed in mining at a certain interfusing ratio of mullock. Through introducing genetic algorithm (GA), the cutting depth-control problem when the collecting ratio is maximized by controlling the interfusing ratio of mullock was solved with global-optimization-search algorithms. Then optimization theory for cutting depth in mining cobalt-rich crusts by GA, and computer programming were given to realize the algorithm. The computation result of actual data proves the validity of this method.

Keywords

Co-rich crust / collecting ratio / interfusing ratio of mullock / gene algorithm

Cite this article

Download citation ▾
Xuan-yun Qin, Ji-hong Guan, Bo Ren, Ying-yong Bu. Optimization methods of cutting depth in mining Co-rich crusts. Journal of Central South University, 2007, 14(4): 595-599 DOI:10.1007/s11771-007-0114-0

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

HeG.-w., LiangD.-h., SongC.-b., et al.. Determining the distribution boundary of cobalt-rich crusts of guyot by synchronous application of sub-bottom profiling and deep-Sea video recording[J]. Earth Science—Journal of China University of Geosciences, 2005, 30(4): 509-512

[2]

ShenY.-j., ZhongX., HeZ.-q.. Present status of investigation and development of ocean cobalt crust resources[J]. Mining and Metallurgical Engineering, 1999, 19(2): 11-13

[3]

MOON Jai-woon, et al. Current state and future prospect of Korean activities on the seafloor sulfides and cobalt-rich crusts[C]// International Symposium on New Deep Seabed Mineral Resources Development Policy. Ansan, Korea, 2004.

[4]

YamazakiT., SharmaR.. Morphological features of Co-rich mangance deposites and their relation to seabed slopes[J]. Marine Georesources & Geotechonology, 2000, 18(1): 43-76

[5]

GlasbyG. P.. Deep seabed mining: Past failures and future prospects[J]. Marine Georesources and Geotechnology, 2002, 20(2): 161-176

[6]

WuG.-h., MaW.-l., LiuJ.-h., et al.. A method for finding the ore block of Co-rich crusts on seamounts[J]. Journal of Maring Sciences, 2005, 23(4): 15-19

[7]

LiuY.Theoretic and experimental research of method for applying twist-roller to cut and collect deep-sea cobalt crust[D], 2002, Changsha, School of Mechanical and Electrical Engineering, Central South University

[8]

LuoC.-l., HuJ.-p., LiuW.. Device and methods of mining cobalt crust[J]. Journal of Central South University of Technology: Natural Science, 2002, 33(6): 617-620

[9]

XiaY.-m., BuY.-y., TangP.-h., et al.. Modeling and simulation of crushing process of spiral ming head[J]. Journal of Central South University of Technology, 2006, 13(2): 171-174

[10]

QinX.-y., BuY.-y., XiaY.-m., et al.. The reconstructing of the tiny terrain based on fractal theory[J]. Journal of National University of Defense Technology, 2003, 25(5): 44-47

[11]

RenP.. Genetic algorithm(an overview)[J]. Journal of Engineering Mathematics, 1999, 16(1): 18-19

[12]

WuG.-h., WenY., LeM.-f.. Genetic algorithm and its application in structure optimization[J]. Chinese Journal of Applied Mechanics, 1996, 13(2): 93-98

[13]

ZhangX.-j., DaiG.-z., XuN.-p.. Genetic algorithms—A new optimization and search algorithms[J]. Control Theory and Applications, 1995, 12(3): 265-273

[14]

YunQ.-x., HuangG.-q., WangZ.-q.Genetic Algorithm and Genetic Programming[M], 1997, Beijing, Metallurgical Industry Press: 4

AI Summary AI Mindmap
PDF

109

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/