基于数据和知识的工业过程监视及故障诊断综述

Translated title of the contribution: Progress of data-driven and knowledge-driven process monitoring and fault diagnosis for industry process

刘强*, 柴天佑, 秦泗钊, 赵立杰

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

40 Citations (Scopus)

Abstract

从复杂工业过程所可能具有的过程特性及数据存取过程中引入的数据特性分析出发, 综述了具有复杂数据特性的工业过程的多元统计监视方法, 并分别讨论了基于数据和基于知识方法进行故障诊断的优势、进展、适用范围及二者结合的可能. 最后探讨了这一领域中值得进一步研究的问题和可能的发展方向.

從復雜工業過程所可能具有的過程特性及數據存取過程中引入的數據特性分析出發, 綜述了具有復雜數據特性的工業過程的多元統計監視方法, 并分別討論了基于數據和基于知識方法進行故障診斷的優勢、進展、適用范圍及二者結合的可能. 最后探討了這一領域中值得進一步研究的問題和可能的發展方向.

Based on the analysis of complex data characteristics due to the process characteristics or the data collection and storage problem, the developments of theory the researches on complex industry process multivariate statistical monitoring are reviewed. The advantages, development, applicable domain of the data-based and knowledge-based diagnosis methods are discussed. And the possibility of these two types of methods' combination are studied. Finally, some problems and their research tendencies in this field are presented.

Translated title of the contributionProgress of data-driven and knowledge-driven process monitoring and fault diagnosis for industry process
Original languageChinese (Simplified)
Pages (from-to)801-807, 813
Number of pages8
Journal控制与决策/Control and Decision
Volume25
Issue number6
Publication statusPublished - Jun 2010
Externally publishedYes

Keywords

  • Data-based fault diagnosis
  • Industry process
  • Knowledge-based fault diagnosis
  • Multivariate statistical process monitoring
  • 多元统计过程监视
  • 基于数据的诊断
  • 基于知识的诊断
  • 工业过程

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