CIESC Journal ›› 2019, Vol. 70 ›› Issue (2): 590-598.doi: 10.11949/j.issn.0438-1157.20181349

• Process system engineering • Previous Articles     Next Articles

System-levels-based holographic fault diagnosis for complex industrial processes

Kaixiang PENG(),Chuanfang ZHANG(),Liang MA,Jie DONG,Ruihua JIAO,Peng TANG   

  1. Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2018-11-15 Revised:2018-11-25 Online:2019-02-05 Published:2018-12-04
  • Contact: Chuanfang ZHANG E-mail:kaixiang@ustb.edu.cn;zhangchuanfang@126.com

Abstract:

Complex industrial process has long processes, many system levels and a wide range of potential fault distribution space, which is a hotspot in the current fault diagnosis field. Firstly, the current mainstream fault diagnosis methods in process monitoring are classified and summarized. Secondly, this study adopts the combination of quantitative and qualitative, which is based on data and knowledge. A system-level holographic fault diagnosis framework for complex industrial process is proposed, which provides a complete set of techniques and solutions for process monitoring in complex industrial plant-wide process. Compared with current fault diagnosis methods, the framework not only includes fault detection and fault identification, but also includes root cause diagnosis, fault propagation path identification, quantitative fault diagnosis and evaluation. It is quite a practical method for process systems, which can effectively reduce or avoid the fault occurrence, guarantee the quality of the product, and improve the production efficiency and safety of enterprises. Finally, the development trend of fault diagnosis technology and problems to be solved are prospected.

Key words: process systems, plant-wide process, fault diagnosis, fault propagation, fault assessment, production, safety

CLC Number: 

  • TP 273

Fig.1

Schematic diagram for complex industrial process monitoring"

Fig.2

Integrated automation system for strip hot rolling"

Fig.3

System-levels-based holographic fault diagnosis framework for complex industrial processes"

Table 1

Description of process and quality variables in hot strip mill process"

变量类型描述单位
G1G7过程变量i机架的平均辊缝(i=1,…,7)mm
F1F7过程变量i机架的轧制力(i=1,…,7)MN
B2B7过程变量i机架的弯辊力(i=2,…,7)MN
S质量变量平直度I

Fig.4

Fault detection result of finishing mill"

Fig.5

rRBC plot of fault variables of finishing mill"

Fig.6

Fault propagation path of cooling water valves in finishing mill"

Fig.7

Fault level classification based on deviation degree"

Fig.8

Flow chart of holographic fault diagnosis"

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