大数据分析技术下给煤机运行中的异常分析与处理

Abnormal Analysis and Treatment in Coal Feeder Operation Under Big Data Analysis Technology

由于给煤机运行中低电压穿越能力差,累积流量存在异常,本研究在应用大数据分析技术研究给煤机运行中的异常分析与处理方法。运用大数据分析技术对给煤机运行数据中的工况数据进行预处理,清洗偏离严重的点。建立给煤机运行异常模型,判断煤机运行状态是否异常。添加延时模块,准确计算给煤机的煤量累积,解决累积流量异常问题。改造给煤机变频器低电压穿越,加装隔离电压延缓装置,提升其低电压穿越能力。运行效果显示,给煤机运行正常,累积流量偏差值为0,较好地实现了异常分析与处理。

Due to the poor low voltage crossing ability and abnormal accumulated flow in the operation of coal feeder,this research studies the abnormal analysis and treatment methods in the operation of coal feeder by applying big data analysis technology.The big data analysis technology is used to preprocess the working condition data in the coal feeder operation data and clean the serious deviation points.The abnormal operation model of coal feeder is established,and judge whether the running state of coal feeder is abnormal.Delay module is added to accurately calculate the coal amount accumulation of coal feeder to solve the problem of abnormal cumulative flow.To improve the low voltage crossing ability of coal feeder converter,the isolation voltage delay device is installed.The operation results show that the coal feeder runs normally and the accumulated flow deviation value is 0,which better realizes the abnormal analysis and processing.