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A Novel Approach For Gas Turbine Condition Monitoring Combining Cusum Technique And Artificial Neural Network

In English

Författare

Summary, in English

Investigation of a novel condition monitoring approach, combining artificial neural network (ANN) with a sequential analysis technique, has been reported in this paper. For this purpose operational data from a Siemens SGT600 gas turbine has been employed for the training of an ANN model. This ANN model is subsequently used for the prediction of performance parameters of the gas turbine. Simulated anomalies are introduced on two different sets of operational data, acquired one year apart, whereupon this data is compared with corresponding ANN predictions. The cumulative sum (CUSUM) technique is used to improve and facilitate the detection of such anomalies in the gas turbine's performance. The results are promising, displaying fast detection of small changes and detection of changes even for a degraded gas turbine.

Avdelning/ar

Publiceringsår

2009

Språk

Engelska

Sidor

567-574

Publikation/Tidskrift/Serie

Proceedings Of The Asme Turbo Expo 2009, Vol 1

Dokumenttyp

Konferensbidrag

Förlag

American Society Of Mechanical Engineers (ASME)

Ämne

  • Energy Engineering

Nyckelord

  • condition monitoring
  • ANN
  • CUSUM
  • gas turbine

Conference name

54th ASME Turbo Expo 2009

Conference date

2009-06-08 - 2009-06-12

Conference place

Orlando, FL, United States

Status

Published

ISBN/ISSN/Övrigt

  • ISBN: 978-0-7918-4882-1