Two distinct and parallel research communities have been working along the lines of the model-based diagnosis approach: the fault detection and isolation (FDI) community and the diagnostic (DX) community that have evolved in the fields of automatic control and artificial intelligence, respectively. This paper clarifies and links the concepts and assumptions that underlie the FDI analytical redundancy approach and the DX consistency-based logical approach. A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.

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Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives

Alarm systems play critically important roles for the safe and efficient operation of modern industrial plants. However, most existing industrial alarm systems suffer from poor performance, noticeably having too many alarms to be handled by operators in control rooms. Such alarm overloading is extremely detrimental to the important role played by alarm systems. This paper provides an overview of industrial alarm systems. Four main causes are identified as the culprits for alarm overloading, namely, chattering alarms due to noise and disturbance, alarm variables incorrectly configured, alarm design isolated from related variables, and abnormality propagation owing to physical connections. Industrial examples from a large-scale thermal power plant are provided as supportive evidences. The current research status for industrial alarm systems is summarized by focusing on existing studies related to these main causes. Eight fundamental research problems to be solved are formulated for the complete lifecycle of alarm variables including alarm configuration, alarm design, and alarm removal.

An Overview of Industrial Alarm Systems: Main Causes for Alarm Overloading, Research Status, and Open Problems

Articulation and codification of collective know-how in the steel industry: evidence from blast furnace control in France

Modelling of thermofluid systems is complex because of the coupling of thermal and hydraulic energies. Bond graph language is a suitable tool for modelling such nonlinearmultienergy domain systems ...

Component-Based Modelling of Thermofluid Systems for Sensor Placement and Fault Detection

Fuzzy theory approach for temporal model-based diagnosis: An application to medical domains

The ‘ALARM’ research group has been running two years as a multidlabs group within the French National Program on Artificial Intelligence PRCdIA The group’s objective was to bring together representatives of the academic and industrial worlds in order to analyze, on real applications, the various problems raised by alarm interpretation and to define the potential benefits of AI techniques in this field This paper presents the conclusions stemming from the analysis and discussions which took place during this period It describes the industrial applications which the members of the group dealt with and compares them in a table with respect to several criteria identified as the most significant

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Papers

Monitoring and alarm interpretation in industrial environments