摘要
对钢铁行业的颗粒物监测系统进行了概述,分析了现有系统的局限性与挑战,提出了优化策略,包括数据融合与多源数据分析、算法优化与性能提升以及系统实时性与稳定性优化;通过案例分析,验证了所提出优化方案的实际效果,进一步展示了大数据在提高颗粒物监测系统性能中的重要应用价值。
An overview of the particulate matter monitoring system in the iron and steel industry is given,the limitations and challenges of the existing system are analyzed,and optimization strategies are proposed,including data fusion and multi-source data analysis,algorithm optimization and performance improvement,and optimization of real-time performance and stability of the system;the practical effects of the proposed optimization scheme are verified through case studies,which further demonstrates the important role of big data in improving the performance of the particulate matter monitoring system.The case study further demonstrates the important value of big data in improving the performance of particulate matter monitoring system.
作者
张健
Zhang Jian(Hebei Iron and Steel Group Co.,Ltd,Handan Branch,Handan Hebei 056011,China)
出处
《现代工业经济和信息化》
2025年第7期78-79,86,共3页
Modern Industrial Economy and Informationization
关键词
大数据分析
钢铁行业
颗粒物
自动监测
系统优化
big data analysis
iron and steel industry
particulate matter
automatic monitoring
system optimization
