Volume 5: Manufacturing Materials and Metallurgy; Ceramics; Structures and Dynamics; Controls, Diagnostics and Instrumentation; 1991
DOI: 10.1115/91-gt-259
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A Procedure for Automated Gas Turbine Blade Fault Identification Based on Spectral Pattern Analysis

Abstract: A method for diagnosing the existence and the kind of faults in blades of a Gas Turbine compressor is presented in the present paper. The innovative feature of this method is that it performs the diagnosis automatically, namely it gives a direct answer to whether a fault exists and what fault it is, without requiring the interpretation of results by a human expert. This is achieved by the derivation of the values of discriminants calculated from spectral patterns of fast response measurement data. A decision a… Show more

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Cited by 2 publications
(3 citation statements)
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“…Automated fault identification for gas turbines based on spectral features of measure· ments of various dynamic quantities, such as internal pressure, casing acceleration, acoustic data is presented and applied by Loukis et al , (1992). The examined faults were rotor fouling (fault of all the blades), individual rotor blade fouting (fault of 2 blades of stage 1 rotor), individual rotor blade twisted, stator blade restaggering.…”
Section: Reciprocating Machine and Gos Turbine Fault Detectionmentioning
confidence: 99%
See 1 more Smart Citation
“…Automated fault identification for gas turbines based on spectral features of measure· ments of various dynamic quantities, such as internal pressure, casing acceleration, acoustic data is presented and applied by Loukis et al , (1992). The examined faults were rotor fouling (fault of all the blades), individual rotor blade fouting (fault of 2 blades of stage 1 rotor), individual rotor blade twisted, stator blade restaggering.…”
Section: Reciprocating Machine and Gos Turbine Fault Detectionmentioning
confidence: 99%
“…1 The technique presented briefly previously has been developed on the basis of the data available from experiments in an industrial gas turbine with specific implanted faults (Loukis et al, 1992). 1 The technique presented briefly previously has been developed on the basis of the data available from experiments in an industrial gas turbine with specific implanted faults (Loukis et al, 1992).…”
Section: Reciprocating Machine and Gos Turbine Fault Detectionmentioning
confidence: 99%
“…The gas turbine blading fault diagnosis problem was originally addressed in [4,5], based on classical pattern recognition methods. In the present paper a (NN) approach is developed for this problem.…”
Section: Introductionmentioning
confidence: 99%