基于大数据技术的造纸车间设备运行指标实时监测方法

Realtime Monitoring Method of Equipment Operation Index in Papermaking Workshop Based on Big Data Technology

电商贸易发展速度的加快,使得纸张需求量急剧增加,造纸车间规模也随之扩大,设备数量、种类、结构复杂度等均呈现上涨的趋势,为设备管理与控制提出了较大的挑战。为了保障设备运行的稳定性,提出基于大数据技术的造纸车间设备运行指标实时监测方法研究。选取适当的造纸车间设备运行指标,以此为基础,应用多种传感器采集运行指标数据,采用线性插值算法填充缺失数据,基于滑动窗口获取候选异常数据集合,引入大数据技术——改进PSO-PFCM算法对异常数据候选集合进行深度挖掘,完成运行指标异常数据的检测,实现设备运行指标的实时监测。实验结果表明:在不同实验工况下,提出方法可以准确地、无遗漏地监测出运行指标异常数据,充分证实了提出方法具备较佳的运行指标监测性能。

The rapid development of e-commerce trade has led to a sharp increase in the demand for paper and the expansion of the size of the papermaking workshop.The number,type and structural complexity of equipment have shown an upward trend,posing a greater challenge for equipment management and control.In order to ensure the stability of the equipment operation,a real-time monitoring method for the equipment operation indicators of the papermaking workshop based on big data technology is proposed.Select appropriate equipment operation indicators in the papermaking workshop,and on this basis,use multiple sensors to collect operation indicator data,use linear interpolation algorithm to fill in missing data,obtain candidate abnormal data sets based on sliding window,introduce big data technologyimproved PSO-PFCM algorithm to conduct in-depth mining of abnormal data candidate sets,complete the detection of abnormal data of operation indicators,and realize real-time monitoring of equipment operation indicators.The experimental results show that under different experimental conditions,the proposed method can accurately and accurately monitor the abnormal data of operating indicators,which fully proves that the proposed method has better monitoring performance of operating indicators.