摘要
为了解决回坡底煤矿11-109工作面刮板输送机未知运行形态造成工作面的停产问题,基于机器学习理论,通过滚动预测模型和核方法,对刮板输送机运行形态进行了监测和预测研究,对比分析真实测量值和理论测量值之间的差异,证明了该理论对刮板输送机运行形态监测的可行性,且具有高准确率、高速度的计算特点。
In order to solve the problem of the shutdown of the working face caused by the unknown operation mode of the scraper conveyor at the 11-109 working face of Huipodi Coal Mine,and based on the theory of machine learning,by rolling forecast model and the method of the scraper conveyor running pattern for the monitoring and prediction research,analysis of actual measured values of the difference between measured value and theory,proved that the theory on monitoring the feasibility of the scraper conveyor running forms,The characteristics of high accuracy and high speed make the theory more applicable in practical engineering.
作者
李亮亮
Li liangliang(Shanxi Fenhe Coking Coal Co.,LTD.,Huozhou Coal and Power Group,Shanxi hongtong 041600)
出处
《江西煤炭科技》
2022年第2期211-213,共3页
Jiangxi Coal Science & Technology
关键词
刮板输送机
机器学习理论
预测模型
核方法
运行形态监测
scraper conveyor
Machine learning theory
Rolling prediction model
Nuclear method
Operational form monitoring
