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Fault diagnosis and alarm management using causal graphs

The aim of the CHEM project was to develop and implement advanced Decision Support Systems (DSS) for process monitoring, data and event analysis, and operation support in industrial processes. The systems are synergistic integration of innovative software tools, which improve the safety, product quality and operation reliability as well as reduce the economic losses due to faulty states, mainly in refining, chemical and petrochemical processes.

The CHEM applications consist of integrated sets of software toolboxes that provide robust detection and diagnosis of process problems in real-time. The systems assist operators in assessing process status and responding to abnormal events. The project provides a flexible architecture and a methodology in order to facilitate the development of such applications on many processes.

This toolbox "Fault diagnosis and alarm management using causal graphs" consists in the localisation of faulty components using a causal graph (see Toolbox "Alarm generation") and Artificial Intelligence techniques.

First, a hitting set algorithm is used to determine sets of suspected components. Then, knowledge based modules containing human operator knowledge and dedicated to each suspected components are used to identify the faults and to generate messages to the operator indicating the faults and the actions that must be undertaken.

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