摘要
为避免采煤机电机过载损伤,使其持续可靠高效运行,提出一种基于多目标优化的采煤机截割最优运动学参数匹配控制策略,根据采煤机滚筒的生产率和块煤率等性能指标建立数学模型,构建总的目标函数,采用模拟退火的粒子群算法对其进行寻优,通过构建最优运动学参数匹配模块,仿真分析采煤机截割-牵引协同控制系统。结果表明,与传统采煤机控制方法相比,系统能随着实时工况的变化较好地跟踪最优牵引电机转速和滚筒转速,采煤机生产率降低了3.2%,但块煤率提高了138.5%,截割比能耗总体降低了30.8%,装煤率提高了40%,采煤机的综合性能指标达到最优。
This paper proposes a control strategy of matching optimal kinematics parameter for shearer cutting based on multi-objective optimization to avoid overload damage of the shearer,and make it run continuously,reliably and efficiently.According to the performance indicators including productivity rate and lump coal rate of the shearer drum,the study consists of developing a mathematical model and the overall objective function;optimizing it by using the particle swarm optimization algorithm based on simulated annealing;and simulating and analyzing shearer cutting and pulling cooperative control system by constructing a optimal kinematic parameter matching module.The results show that compared with traditional shearer control method,this system can fit the optimal traction motor speed and drum speed better with the change of real-time working conditions.Although the shearer productivity is reduced by 3.2%,the comprehensive performance index of the shearer reaches the best with the increase of lump coal rate by 138.5%,the decrease of specific energy consumption of cutting by 30.8%,and the increase of coal loading rate by 40%.
作者
郭殿林
岳博
Guo Dianlin;Yue Bo(School of Electrical&Control Engineering,Heilongjiang University of Science&Technology,Harbin 150022,China)
出处
《黑龙江科技大学学报》
CAS
2024年第1期98-105,共8页
Journal of Heilongjiang University of Science And Technology
基金
黑龙江省省属高等学校基本科研业务费项目(2022-KYYWF-0550)。
关键词
采煤机
参数匹配控制策略
模拟退火的粒子群算法
多目标优化
shearer
parameter matching control policy
particle swarm optimization for simulated annealing
multi-objective optimization