The aim of this paper is to present an intelligent software tool, using Artificial Intelligence (AI) techniques, which allows the execution of an alarm analysis, during the remote sensing activity of complex plants. The AI component allows to identify all the primary faults of the system, discriminating them from the side effect alarms. In other words this tool shows which alarms are directly connected to primary faults and which alarms are consequential effects of the primary ones. The core of the software is an algorithm which uses a knowledge ontology and a set of alarm propagation rules, which are both based on a Multilevel Flow Modelling (MFM) paradigm. The algorithm has been tested implementing a rule based expert system (RBES) referred to an existing water plant. The main features of the water plant have been identified and all the main components and their possible alarm states have been analyzed to carry out the knowledge base.
Improving automatic control of complex water systems, using AI techniques: design of an expert component for the alarms analysis
G. Gallone, R. Gueli, A. Patti, A. Tropea; Improving automatic control of complex water systems, using AI techniques: design of an expert component for the alarms analysis. Water Supply 1 December 2004; 4 (5-6): 375–381. doi: https://doi.org/10.2166/ws.2004.0128
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