摘要
为了提高采煤效率,降低采煤装置的损耗,构建了采煤机牵引速度和滚筒高度智能协调控制系统,采用BP神经网络和RS理论的模式算法,对采煤机的运行状态进行计算,根据专家知识库,辨别采煤机故障原因;采用模糊逻辑—专家知识库(FL-EKB)来选择控制指令的优先,设计了该系统的智能协调控制流程,并进行了工业试验分析,搭建了完善的试验平台。研究表明,煤矿采煤机可以按照目标路径高效、平稳地运行,能够准确判断出采煤机异常的原因,发出协调控制命令。研究为自动化综采工作面的建立提供了技术支持。
In order to improve the efficiency of coal mining and reduce the loss of coal mining equipment,the intelligent coordinated control system of haulage speed and drum height of shearer was constructed.The mode algorithm of BP neural network and RS theory was used to calculate the running state of shearer.According to the expert knowledge base,the fault causes of the shearer were identified.The fuzzy logic expert knowledge base(FL-EKB) was used to select the control command.The intelligent coordinated control flow of the system was designed,and the industrial test analysis was carried out,and a perfect test platform was built.The research showed that the coal mining machine can run efficiently and stably according to the target path,and can accurately determine the cause of abnormal shearer and issue coordinated control command.The research provided technical support for the establishment of automatic fully-mechanized mining face.
作者
雍建军
Yong Jianjun(Mechanical and Electrical Management Department of Ningxia Coal Industry Company,China Energy Group,Yinchuan 750000,China)
出处
《能源与环保》
2020年第7期159-162,共4页
CHINA ENERGY AND ENVIRONMENTAL PROTECTION
关键词
采煤机
牵引速度
滚筒高度
协调控制
运行状态
shearer
traction speed
drum height
coordinated control
operating status
