Novel Causal Digraph Reasoning For Fault Diagnosis with Application on the Paper Machine Short Circulation Process

Hui Cheng; Mats Nikus; Sirkka-Liisa Jämsä-Jounela

doi:10.3182/20080706-5-KR-1001.01884

Novel Causal Digraph Reasoning For Fault Diagnosis with Application on the Paper Machine Short Circulation Process

Hui Cheng, Mats Nikus, Sirkka-Liisa Jämsä-Jounela

Research output: Contribution to journal › Conference article › Scientific › peer-review

Abstract

This paper presents an enhanced dynamic causal digraph reasoning method for fault diagnosis and its application to the short circulation process of a paper machine. In order to improve the isolation capability of the original method, an inference mechanism between the arcs of the graph is proposed to locate process faults on the arcs. Application of the proposed method to the paper machine short circulation process is presented at the end of the paper. The results show that the proposed method is able to identify the responsible arcs when the system is affected by a process fault.

Original language	English
Pages (from-to)	11118-11123
Journal	IFAC PROCEEDINGS VOLUMES
Volume	41
Issue number	2
DOIs	https://doi.org/10.3182/20080706-5-KR-1001.01884
Publication status	Published - 2008
MoE publication type	A4 Article in a conference publication
Event	IFAC World Congress - Seoul, Korea, Republic of Duration: 6 Jul 2008 → 11 Jul 2008 Conference number: 17

Keywords

Methods based on discrete event models, on hybrid or on qualitative models for FDI, Process performance monitoring/statistical process control, Distributed fault detection and isolation

Access to Document

10.3182/20080706-5-KR-1001.01884

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title = "Novel Causal Digraph Reasoning For Fault Diagnosis with Application on the Paper Machine Short Circulation Process",

abstract = "This paper presents an enhanced dynamic causal digraph reasoning method for fault diagnosis and its application to the short circulation process of a paper machine. In order to improve the isolation capability of the original method, an inference mechanism between the arcs of the graph is proposed to locate process faults on the arcs. Application of the proposed method to the paper machine short circulation process is presented at the end of the paper. The results show that the proposed method is able to identify the responsible arcs when the system is affected by a process fault.",

keywords = "Methods based on discrete event models, on hybrid or on qualitative models for FDI, Process performance monitoring/statistical process control, Distributed fault detection and isolation, Methods based on discrete event models, on hybrid or on qualitative models for FDI, Process performance monitoring/statistical process control, Distributed fault detection and isolation, Methods based on discrete event models, on hybrid or on qualitative models for FDI, Process performance monitoring/statistical process control, Distributed fault detection and isolation",

author = "Hui Cheng and Mats Nikus and Sirkka-Liisa J{\"a}ms{\"a}-Jounela",

year = "2008",

doi = "10.3182/20080706-5-KR-1001.01884",

language = "English",

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journal = "IFAC PROCEEDINGS VOLUMES",

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AB - This paper presents an enhanced dynamic causal digraph reasoning method for fault diagnosis and its application to the short circulation process of a paper machine. In order to improve the isolation capability of the original method, an inference mechanism between the arcs of the graph is proposed to locate process faults on the arcs. Application of the proposed method to the paper machine short circulation process is presented at the end of the paper. The results show that the proposed method is able to identify the responsible arcs when the system is affected by a process fault.

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