Causal Model Based Fault Diagnosis Applied on a Paper Machine Simulator

Cheng, Hui; Nikus, Mats; Jämsä‐Jounela, Sirkka‐Liisa

doi:10.3182/20060830-2-sf-4903.00038

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2008

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“…2007.12. 003 the discrete state space models describing the cause-effect relationships was reported by Cheng et al [15]. The latest development of the dynamic causal reasoning fault diagnosis method is the introduction of the set-membership approach, which considers the uncertainty in the modelling and fault detection phases [1].…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis of the paper machine short circulation process using novel dynamic causal digraph reasoning

Cheng

Nikus

Jämsä‐Jounela

2008

Journal of Process Control

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This paper presents a novel 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 fault detection ability of the original causal digraph method, a residual modification approach that takes into account the direction of different fault effects is presented. An improvement of the isolation capability of the original method, an inference mechanism between the arcs of the graph, is also proposed to locate process faults on the arcs. The results from the application show that the proposed method, compared to the conventional method, is able to detect the correct nodes and to identify the responsible arcs when the system is affected by a process fault.

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Section: Introductionmentioning

confidence: 99%