基于神经网络法的掘进机截割负载判定系统的研究  

Research on the System of Determining Cut-off Load of Roadheader Based on Neural Network Method

作　　者：张晓磊 Zhang Xiaolei(Jinneng Holding Group Wajinwan Hulonggou Coal CO.,Ltd.,Huairen Shanxi 038300)

机构地区：[1]晋能控股集团挖金湾虎龙沟煤业有限公司,山西怀仁038300

出　　处：《机械管理开发》2022年第6期241-242,共2页Mechanical Management and Development

摘　　要：针对井下地质环境复杂、能见度低,导致掘进机截割机构频繁出现磨损严重、断齿等问题,以神经网络法为基础,提出了一种新的掘进机负载判定系统。该系统结合信号识别和智能控制技术,实现对掘进机掘进作业过程中截割负载的准确判断,为实现掘进机自动截割作业、提高井下掘进效率奠定了基础,具有极大的应用推广价值。In view of the complex underground geological environment and low visibility,which leads to frequent problems such as severe wear and broken teeth in the cutting mechanism of roadheader,which greatly affects the underground tunneling operation,a new load determination system for roadheader is proposed based on neural network method,combining signal recognition and intelligent control technology to achieve accurate judgment of cutting load in the process of roadheader digging operation,and to provide the best solution for This system has laid the foundation for the realization of automatic cutting operation of roadheader and the improvement of underground drilling efficiency,and has great application value.

关 键 词：神经网络 掘进机 负载判定 自动控制 

分 类 号：TD421[矿业工程—矿山机电]