摘要
旨在研究分布式控制系统(DCS)监测数据支撑下复杂机电系统特征谱的构建方法。通过DCS收集大量的时间序列数据,并分析其海量性、非线性、关联性和层次性4个关键特性。采用数据分类和色彩编码技术,将监测数据转化为系统状态特征谱。通过构建二维数据矩阵对监测数据进行分类,并根据颜色编码将其映射为可视化的数字图像,以便直观地检测和评估系统的运行状态和健康状况。以化工厂空气压缩机组为例,验证了该方法在实际工业系统中的有效性和实用性。通过该方法,可以更方便地识别关键设备故障,预测潜在问题,进一步优化生产过程,从而提高系统的安全性和可靠性。
Aiming to study the construction method of complex electromechanical system characteristic spectrum supported by Distributed Control System(DCS)monitoring data.Analyze the four key characteristics of massive,nonlinear,correlated,and hierarchical time series data collected through DCS.Using data classification and color coding techniques,the monitoring data is transformed into a system state feature spectrum.By constructing a two-dimensional data matrix to classify monitoring data and mapping it into visual digital images based on color coding,the operational status and health condition of the system can be intuitively detected and evaluated.Taking the air compressor unit in a chemical plant as an example,the effectiveness and practicality of this method in practical industrial systems have been verified.Through this method,it is more convenient to identify key equipment failures,predict potential problems,further optimize the production process,and thus improve the safety and reliability of the system.
作者
杨红鸣
YANG Hongming(Zhongkong Technology Co.,Ltd.,Hangzhou,Zhejiang 310000,China)
出处
《自动化应用》
2025年第4期122-125,共4页
Automation Application
关键词
分布式控制系统
特征谱构建
状态监测
数据可视化
DCS
construction of characteristic spectra
status monitoring
data visualization
