摘要
将采煤机滚筒截割振动特性作为煤岩识别的标识之一,利用自适应模糊神经网络推理系统(ANFIS)将采煤机的工作状态信息进行融合,建立了多信息融合的煤岩识别模型,并利用模拟实验中采集的数据完成煤岩分界识别的实验研究,结果表明利用该方法实现采煤机的煤岩识别是可行的,并为实现采煤机姿态的自动控制提供依据。
The vibration character of shearer has been used as one of the signals in the coal-rock interface recognition in the study. The multi-information of working conditions of the shear-er have been fused by the Adaptive Neural-Fuzzy Inference System （ANFIS）.Based on this theo-ry,a coal and rock identification model is adopted to perform the study of the coal-rock interface recognition with the previous experimental data. The result showed that it is a feasible method to realize coal-rock interface recognition and also is the base of the study of shearer＆#39;s running posture auto-control.
出处
《中国煤炭》
北大核心
2014年第12期56-59,共4页
China Coal
基金
国家自然科学基金资助项目(51205112)
河南省科技攻关资助项目(112102210105)
高校博士基金(B2011-036)
关键词
信息融合
ANFIS
煤岩识别
采煤机智能控制
informations fusion
ANFIS
coal-rock interface recognition
intelligent control of shearers
