摘要
分析国内电牵引采煤机调速过程中存在的问题,提出以变频调速为主,多信息数据融合为辅的最优调速控制算法。采煤机各部件的相互耦合会对调速过程产生不同的影响,通过采集各部件运行状态数据,提出以BP神经网络作为数据融合算法的多信息处理技术,处理后的信息输出作为不同工况下控制采煤机调速的最优化参数。
Based on the analysis of the problems existing in the speed control process of domestic electric haulage shearer,an optimal speed control algorithm is proposed,which is mainly based on frequency conversion and supplemented by multi-information data fusion.The coupling of each part of the shearer has different influence on the speed regulation process.By collecting the running state data of each part,the multi-information processing technology with BP neural network as the data fusion algorithm was proposed,and the processed information output was the optimal parameter to control the speed regulation of the shearer under different working conditions.
作者
李彬
黄克军
韩磊
李涛
LI Bin;HUANG Ke-jun;HAN Lei;LI Tao(Shaanxi Coal Chemical Industry Technology Research Institute Co.,Ltd.,Xi’an 710065,China;National and Local United Engineering Research Center of Green Safe and Efficient Coal Mining,Xi’an 710065,China;Research Center of Coal Green Mining Engineering in Coal Industry,Xi’an 710065,China)
出处
《陕西煤炭》
2020年第S01期105-108,共4页
Shaanxi Coal
关键词
电牵引采煤机
变频调速
数据融合
BP神经网络
electrical haulage shearer
frequency control
data fuse
BP neural network
