现代信息科技2025，Vol.9Issue(16)：70-75,81,7.DOI:10.19850/j.cnki.2096-4706.2025.16.013
基于工业大数据的FPSO生产流程自主诊断系统
FPSO Production Process Autonomous Diagnosis System Based on Industrial Big Data
刘东辉 1刘雪松 1孙海防 1仝英利 1邓欣1
作者信息
- 1. 中海油能源发展股份有限公司采油服务分公司,天津 300452
- 折叠
摘要
Abstract
Aiming at the problems of dynamic anomaly of control loop and abnormal detection of process parameter fluctuation in the operation of Floating Production Storage and Offloading(FPSO)unit,this paper studies and proposes an autonomous diagnosis system for FPSO production process.Firstly,the anomaly diagnosis module of the control loop is constructed by correlation analysis,K-means clustering and Support Vector Data Description(SVDD).Secondly,the abnormal diagnosis module of process parameters is constructed by rules and rolling Principal Component Analysis(PCA)method.Finally,combined with historical data and expert knowledge base,a fault tree model is established to infer the cause of the abnormality online.Experiments show that the system can identify complex anomalies and provide maintenance decision support through a visual interface,which effectively improves the accuracy of FPSO autonomous diagnosis.关键词
数据驱动/在线诊断/机器学习/控制回路/工艺参数Key words
data driven/online diagnosis/Machine Learning/control loop/process parameters分类
信息技术与安全科学引用本文复制引用
刘东辉,刘雪松,孙海防,仝英利,邓欣..基于工业大数据的FPSO生产流程自主诊断系统[J].现代信息科技,2025,9(16):70-75,81,7.
