Combining Different Intelligent Reasoning Techniques for Explaining Faults on Turbine Generators

Expert systems have been developed for the diagnosis of turbine generators, and are heuristic-based systems. The level of diagnostic explanations they provide to their end users is questionable. This paper presents and discusses the results of case- and model-based reasoning techniques for diagnosin...

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Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy Part A: Journal of Power and Energy, 1996-01, Vol.210 (4), p.253-261
Main Authors: Georgin, E, McDonald, J R, Ricard, B
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Energy
Energy. Thermal use of fuels
Engines and turbines
Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc
Exact sciences and technology
Expert systems
Failure analysis
Formal logic
Heuristic methods
Intelligent structures
Machine vibrations
Mathematical models
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Summary:Expert systems have been developed for the diagnosis of turbine generators, and are heuristic-based systems. The level of diagnostic explanations they provide to their end users is questionable. This paper presents and discusses the results of case- and model-based reasoning techniques for diagnosing and explaining faults of turbine generators. The techniques provide explanations that match user's expectations and reflect less ‘human expert rules’. This also led to the design of a new generation of smart systems which will explain and persuade better plant operators that their diagnosis was correct.
ISSN:0957-6509
2041-2967
DOI:10.1243/PIME_PROC_1996_210_044_02