摘要
选煤厂振动筛主要对原煤进行分级、脱泥、脱水,是洗选过程的重要组成部分,但振动筛长期在恶劣环境和高负荷下运行,经常发生故障,影响生产。研究对振动筛运行状态数据进行采集,构建运行状态监测指标体系,建立基于LSTM算法的故障诊断模型,实现了振动筛运行状态监测与故障诊断系统。研究成果应用于大海则煤矿选煤厂,实现了较好的安全和经济效果。
The vibrating screen in the coal preparation plant is mainly used for grading,desliming and dehydration of raw coal,which is an important part of the washing process.However,the vibrating screen always has been operated in harsh environments and worked under high load for a long time and then breaks down,so that will affect the production process.The research has collected massive data on the operation state of the vibrating screen and has constructed the index system of monitoring operation state,and then basing on LSTM algorithm,has established the fault diagnosis model,and finally has completed the operating state monitoring and fault diagnosis system of the vibrating screen.Now the research results have been applied to the coal preparation plant of Dahaize Coal Mine,and have achieved huge benefits on safety and economic.
作者
王喜升
Wang Xisheng(China Coal Information Technology(Beijing)Co.,Ltd.,Beijing,100120)
出处
《当代化工研究》
2022年第21期104-107,共4页
Modern Chemical Research
关键词
振动筛
指标体系
LSTM
状态监测
故障诊断
vibrating screen
index system
LSTM
condition monitoring
fault diagnosis
