Fault root-cause diagnosis based on granger causality test for petrochemical process system

被引：0

作者：

Hu, Jinqiu ^{[1
]}

Zhang, Laibin ^{[1
]}

Wang, Anqi ^{[1
]}

机构：

[1] Research Center of Accident Prevention and Control for Oil and Gas Industry, College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing,102249, China

来源：

Shiyou Xuebao, Shiyou Jiagong/Acta Petrolei Sinica (Petroleum Processing Section) | 2016年 / 32卷 / 06期

关键词：

Petrochemicals - Statistical tests - Condition monitoring - Distillation equipment - Petrochemical plants - Distillation;

D O I：

10.3969/j.issn.1001-8719.2016.06.025

中图分类号：

学科分类号：

摘要：

In order to reduce the fault impact on petrochemical process system, quick diagnosis of the root cause of the fault is necessary, for which the granger causality test is introduced to study the fault interdependency by analyzing the relationship between process parameters of petrochemical units and establishing an effect diagram of the process parameters. When alarm occurred on condition monitoring system, the effect relationship diagram of the process parameters was used to select the related process parameters, which didn't exceed the alarming threshold, but might indicate an incipient fault. Then the selected parameters were pairwise checked by granger causality test. According to the degree of the causal relationship of the process parameters, the fault quantitative cause and effect diagram could be established, by which the path with the biggest quantitative value of causal relationship could be considered as the most probable fault propagation path. In this way, the root cause of the alarm could be revealed easily. The pilot application for atmospheric and vacuum distillation unit in a petrochemical plant validated the effectiveness of the proposed method and its application value. © 2016, Science Press. All right reserved.

引用

页码：1266 / 1272