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山东大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (5): 187-194.doi: 10.6040/j.issn.1672-3961.0.2017.239

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基于因果拓扑图的工业过程故障诊断

王梦园1,2,张雄1,2,马亮1,2,彭开香1,2   

  1. 1. 北京科技大学自动化学院, 北京 100083;2. 北京科技大学钢铁流程先进控制教育部重点实验室, 北京 100083
  • 收稿日期:2017-02-10 出版日期:2017-10-20 发布日期:2017-02-10
  • 作者简介:王梦园(1992— ),女,辽宁锦州人,硕士研究生,主要研究方向为故障诊断. E-mail: s20150635@xs.ustb.edu.cn

Fault diagnosis for industrial processes based on causal topological graph

WANG Mengyuan1,2, ZHANG Xiong1.2, MA Liang1,2, PENG Kaixiang1,2   

  1. 1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China;
    2. Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2017-02-10 Online:2017-10-20 Published:2017-02-10

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摘要： 基于因果拓扑图的工业过程故障诊断方法,将过程知识与数据驱动故障诊断方法结合,有效解决了故障定位和故障传播路径辨识问题。 在因果拓扑图的基础上,基于偏相关系数提出一种相关性指标(correlation index, CI)定量衡量因果拓扑中变量间的相关性,实现变量间因果性和相关性的良好结合。为得到准确的故障检测结果,采用概率主元分析(PPCA)对CI指标进行监测。在检测出故障后,应用重构贡献图(reconstruction-based contribution, RBC)和因果拓扑图,并引入加权平均值的概念辨识出最可能的故障传播路径。将提出的方法用于带钢热连轧过程,结果表明,基于因果拓扑图的故障诊断方法能够准确地定位故障源,辨识故障传播路径。

关键词: 故障诊断, 因果拓扑图, 相关性分析, 重构贡献图, 概率主元分析

Abstract: With the combination of the process knowledge and data driven methods, the fault diagnosis method based on causal topological graph could effectively deal with the fault location and fault propagation identification. A correlation index(CI)based on partial correlation coefficient was applied to the causal topological graph to analyze the correlation between variables quantitatively. The proposed CI was monitored via probabilistic principal component analysis method(PPCA)for fault detection. The concept of mean weighted value and causal topological graph were introduced in order to identify the optimal fault propagation path based on reconstruction-based contribution(RBC)after detecting a fault. The effectiveness of the method was verified by the application of hot strip mill process(HSMP). The results showed that the proposed method could effectively identify the fault roots and propagation paths.

Key words: PPCA, correlation analysis, fault diagnosis, causal topological graph, RBC

中图分类号: 

  • TP237
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