Forecasting the health of gas turbine components through an integrated performance-based approach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Authors

Colleges, School and Institutes

External organisations

  • Qatar University
  • Emirates Aviation University

Abstract

In this study, we present an integrated method for detecting and forecasting the health of gas turbine components as degraded over time. An advanced model-based real time performance adaptation approach is developed for detecting the degradation of engine components via a dynamic engine model that is built in Simulink. The detected health parameters of the engine component are then implemented in a discrete window-based analysis by a regression method in order to forecast their evolution. The proposed approach is tested for an engine with increased flexibility that characterizes modern gas turbine operations. The results demonstrate the promising capabilities of our advanced proposed method for accurate and efficient detection and forecast of the health of gas turbine compressors as degraded over time.

Details

Original languageEnglish
Title of host publication2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
Publication statusPublished - 12 Aug 2016
Event2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016 - Ottawa, Canada
Duration: 20 Jun 201622 Jun 2016

Publication series

NameIEEE International Conference on Prognostics and Health Management (ICPHM)
PublisherIEEE
Volume2016

Conference

Conference2016 IEEE International Conference on Prognostics and Health Management, ICPHM 2016
CountryCanada
CityOttawa
Period20/06/1622/06/16