Early warning of gas turbine failure by nonlinear feature extraction using an auto-associative neural network approach

Proceedings of the ASME Turbo Expo

Volumn 3, Issue , 2011, Pages 293-304

  Palmé, Thomas ^a   Breuhaus, Peter ^a   Assadi, Mohsen ^a   Klein, Albert ^b   Kim, Minkyo ^b  

^a ALSTOM SWITZERLAND LTD   (Switzerland)

^b UNIVERSITY OF STAVANGER   (Norway)

Author keywords

Auto associative neural networks; Failure detection; Industrial gas turbines; Nonlinear principal component analysis

Indexed keywords

ABNORMAL ENGINE; AUTOASSOCIATIVE NEURAL NETWORKS; DATA DRIVEN; DATA SETS; DATA-DRIVEN APPROACH; EARLY WARNING; FAILURE DETECTION; FALSE INDICATION; INDUSTRIAL GAS TURBINES; LINEAR METHODS; NONLINEAR FEATURE EXTRACTION; NONLINEAR PCA; NONLINEAR PRINCIPAL COMPONENT ANALYSIS; OPERATIONAL DATA; OPERATIONAL PARAMETERS; PCA MODEL; RELIABLE DETECTION; RESIDUAL GENERATION;

EXHIBITIONS; FAULT DETECTION; FEATURE EXTRACTION; GAS TURBINES; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS;

DATA HANDLING;

EID: 84865477733     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/GT2011-45991     Document Type: Conference Paper

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