Gas Turbine Fault Diagnosis Using Fuzzy-Based Decision Fusion

A two-step information fusion technique allowing the combination of fast response and performance data for the improvement of gas turbines diagnostic procedures is proposed. The proposed technique is derived from the notion of decision level fusion. Different diagnostic methods provide assessments f...

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Bibliographic Details
Published in:Journal of propulsion and power 2009-03, Vol.25 (2), p.335-343
Main Authors: Kyriazis, A, Mathioudakis, K
Format: Article
Language:English
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Summary:A two-step information fusion technique allowing the combination of fast response and performance data for the improvement of gas turbines diagnostic procedures is proposed. The proposed technique is derived from the notion of decision level fusion. Different diagnostic methods provide assessments for the condition of an engine, and the final decision is derived from a combination of these assessments. The diagnostic method of probabilistic neural networks acts independently and in parallel on data of a different nature. The conclusions are given for the first step of the fusion technique and are aggregated deriving the probability consensus. In a second step this consensus is classified within a set of examined faults using the fuzzy set theory and fuzzy logic, thus providing the final diagnostic decision. The effectiveness of the proposed technique is demonstrated through the application to data from a radial and an axial compressor. [PUBLISHER ABSTRACT]
ISSN:0748-4658
1533-3876
DOI:10.2514/1.38629