基于异常工况预测的石化生产运营持续改进  

Continuous Improvement of Petrochemical Production and Operation based on Prediction of Abnormal Working Conditions

作　　者：黄颖 Huang Ying(Yumo Enterprise Management Consulting(Shanghai)Co.,Ltd.,Shanghai 200433)

机构地区：[1]宇墨企业管理咨询(上海)有限公司,上海200433

出　　处：《石油化工技术与经济》2020年第3期47-49,共3页Technology & Economics in Petrochemicals

摘　　要：从石化生产报警管理入手,研究了主成分分析法在石化生产过程异常工况预测领域的应用,为采用马氏距离和欧式距离预测异常工况找到了新的途径;通过离线分析石化某装置运营数据,为持续改进生产运营管理提供了解决方案。Starting with the petrochemical production alarm management,the application of the principal component analysis method in the field of abnormal conditions prediction in the production process of petrochemical enterprises is studied,and a new way has been found to predict the abnormal conditions using the Mahalanobis distance and the Euclidean distance.Through offline analysis of the operation data of a petrochemical plant,it provides solutions for continuous improvement of production and operation management.

关 键 词：生产报警监控系统 异常工况 预测 持续改进 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]