摘要
现在矿井的开采深度越来越大,煤层赋存的条件也越来越复杂,采煤机端头记忆截割时截割面变化较大,可能导致采煤机负载不合理。针对这一问题,对影响采煤机负载的内在因素进行了系统分析,得到了采煤机端头负载的平衡指标。并基于小波神经网络和模糊逻辑判定,给出了采煤机端头记忆截割负载平衡的控制方法。
As the mining depth was large,and the loading condition of the end of the shearer was more complicated.In this paper,the internal factors affecting the load of the shearer were systematically analyzed,and the balance index of the load the shearer was obtained.Based on the wavelet neural method,the prediction structure of the end load was established on the basis of the end structure of the shearer.The error of the prediction model and the actual situation was within 3%.Finally,by analyzing the fuzzy membership function of the motor current,the load of the end of the shearer was analyzed.
作者
刘斌
Liu Bin(Zisheng Minef Huozhou Coal Electricity Group Corporation Ltd.,Linfen 034100,China)
出处
《煤炭与化工》
CAS
2018年第6期72-74,77,共4页
Coal and Chemical Industry
关键词
采煤机
记忆截割
负载平衡
小波神经
coal mining machine
memory truncation
load balancing
wavelet neural
作者简介
刘斌(1990—),男,河南浚县人,助理工程师。
