基于量子遗传算法的液压支架喷雾效率的参数优化设计  

Parameter optimization design on spray efficiency of hydraulic support based on quantum genetic algorithm

作　　者：张强[1] 李宏峰[1] 

机构地区：[1]辽宁工程技术大学机械工程学院,辽宁阜新123000

出　　处：《中国安全生产科学技术》2014年第12期51-55,共5页Journal of Safety Science and Technology

基　　金：国家863项目(2013AA06A412);国家科技支撑计划项目(2013BAH12F01);工业装备结构分析国家重点实验室开放基金项目(GZ1107);辽宁省教育厅科研项目计划资助项目(L20110520)

摘　　要：为了提高综采工作面液压支架喷雾的降尘效率,通过分析影响支架喷雾降尘效率的因素,以支架喷雾效率最高为优化目标,利用量子遗传算法对喷嘴到产尘点距离,雾化角度,喷雾压力,喷嘴个数,喷嘴直径多参数进行优化。结果表明:液压支架的采煤机移动喷雾降尘效率增加了13.06%,液压支架上的移架/放煤喷雾降尘效率增加了13.33%。此研究对于支架喷雾降尘系统的设计,参数的合理选取有一定的参考价值。In order to improve the efficiency of reducing dust by spray of hydraulic support in fully mechanized working face, through the analysis on the factors influencing the efficiency of reducing dust by spray of support, with the maximum spray efficiency of hydraulic support as optimization goal, multiple parameters were optimized by quantum genetic algorithm, including the distance from nozzle to the place forming dust,spray angle,spray pres-sure,the number of nozzle and nozzle diameter etc.The results showed that the efficiency of reducing dust by mo-bile spray of hydraulic support on coal mining machine increased by 13.06%, and the efficiency of reducing dust by support moving/discharging coal spray of hydraulic support increased by 13 .33%.It provides some reference value for designing the spray reducing dust system on support and selecting reasonably parameters.

关 键 词：液压支架 降尘效率 优化 多目标 量子遗传算法 

分 类 号：X936[环境科学与工程—安全科学]