Model- and knowledge-based fault detection and diagnosis of gas transmission networks

This paper describes an expert system for online fault detection and diagnosis of gas transmission networks, combining model- and knowledge-based methods. It consists of a set of hierarchically structured components which include signal processing, Luenberger-type state observation, rule-based knowledge processing as well as an advanced user interface. The diagnosis system was tested with real measurement data from a medium sized gas distribution network. Its real-time capability and effectiveness for basic fault detection purposes was demonstrated by industrial applications.<
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