Multiple faults diagnosis using causal graph

Imtiez Fliss; Moncef Tagina

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arXiv · 1203.5451

Multiple faults diagnosis using causal graph

Imtiez Fliss·Moncef Tagina

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Abstract

This work proposes to put up a tool for diagnosing multi faults based on model using techniques of detection and localization inspired from the community of artificial intelligence and that of automatic. The diagnostic procedure to be integrated into the supervisory system must therefore be provided with explanatory features. Techniques based on causal reasoning are a pertinent approach for this purpose. Bond graph modeling is used to describe the cause effect relationship between process variables. Experimental results are presented and discussed in order to compare performance of causal graph technique and classic methods inspired from artificial intelligence (DX) and control theory (FDI).

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Imtiez Fliss, Moncef Tagina. 2012-03-24. Multiple faults diagnosis using causal graph. https://arxiv.org/abs/1203.5451

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