SCI和EI收录∣中国化工学会会刊

›› 2016, Vol. 24 ›› Issue (8): 952-962.DOI: 10.1016/j.cjche.2016.05.039

• Review • Previous Articles     Next Articles

A review of control loop monitoring and diagnosis: Prospects of controller maintenance in big data era

Xinqing Gao1,2, Fan Yang1,2, Chao Shang1,2, Dexian Huang1,2   

  1. 1 Department of Automation, Tsinghua University, Beijing 100084, China;
    2 Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China
  • Received:2015-11-06 Revised:2016-02-29 Online:2016-09-21 Published:2016-08-28
  • Supported by:
    Supported by the National Basic Research Program of China (2012CB720505), the National Natural Science Foundation of China (21276137, 61433001), Tsinghua University Initiative Scientific Research Program and the seventh framework programme (FP7-PEOPLE-2013-IRSES-612230) of European Union.

A review of control loop monitoring and diagnosis: Prospects of controller maintenance in big data era

Xinqing Gao1,2, Fan Yang1,2, Chao Shang1,2, Dexian Huang1,2   

  1. 1 Department of Automation, Tsinghua University, Beijing 100084, China;
    2 Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China
  • 通讯作者: Dexian Huang
  • 基金资助:
    Supported by the National Basic Research Program of China (2012CB720505), the National Natural Science Foundation of China (21276137, 61433001), Tsinghua University Initiative Scientific Research Program and the seventh framework programme (FP7-PEOPLE-2013-IRSES-612230) of European Union.

Abstract: Owing to wide applications of automatic control systems in the process industries, the impacts of controller performance on industrial processes are becoming increasingly significant. Consequently, controller maintenance is critical to guarantee routine operations of industrial processes. The workflow of controller maintenance generally involves the following steps:monitor operating controller performance and detect performance degradation, diagnose probable root causes of control system malfunctions, and take specific actions to resolve associated problems. In this article, a comprehensive overview of the mainstream of control loop monitoring and diagnosis is provided, and some existing problems are also analyzed and discussed. From the viewpoint of synthesizing abundant information in the context of big data, some prospective ideas and promising methods are outlined to potentially solve problems in industrial applications.

Key words: Control loop performance assessment, Industrial alarm system, Process knowledge, Root cause diagnosis, Big data

摘要: Owing to wide applications of automatic control systems in the process industries, the impacts of controller performance on industrial processes are becoming increasingly significant. Consequently, controller maintenance is critical to guarantee routine operations of industrial processes. The workflow of controller maintenance generally involves the following steps:monitor operating controller performance and detect performance degradation, diagnose probable root causes of control system malfunctions, and take specific actions to resolve associated problems. In this article, a comprehensive overview of the mainstream of control loop monitoring and diagnosis is provided, and some existing problems are also analyzed and discussed. From the viewpoint of synthesizing abundant information in the context of big data, some prospective ideas and promising methods are outlined to potentially solve problems in industrial applications.

关键词: Control loop performance assessment, Industrial alarm system, Process knowledge, Root cause diagnosis, Big data