Application of the Enhanced Dynamic Causal Digraph Method on a Three-Layer Board Machine

Hui Cheng, Vesa-Matti Tikkala, Alexey Zakharov, Tommi Myller, Sirkka-Liisa Jamsa-Jounela

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)
182 Downloads (Pure)


This brief presents an enhanced dynamic causal digraph (EDCDG) reasoning method for fault diagnosis. In order to improve the fault isolation ability of the dynamic causal digraph method, a new algorithm for separating the positive and negative fault effect contributions is proposed. The proposed method was tested with an application on a three-layer board machine process. The results show that the proposed method, compared to the conventional dynamic causal digraph method, is able to detect the correct nodes, to form a better fault propagation path and to identify the responsible arcs when the system is affected by a process fault.
Original languageEnglish
Pages (from-to)644-655
JournalIEEE Transactions on Control Systems Technology
Issue number3
Publication statusPublished - 2011
MoE publication typeA1 Journal article-refereed


  • board machine
  • causal digraph
  • fault diagnosis
  • industrial application
  • Paper making

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