0

Full Content is available to subscribers

Subscribe/Learn More  >

Pulsations in Gas Turbine Operation: Identification and Modeling With the Purpose of Online Engine Monitoring and Optimization

[+] Author Affiliations
Frank S. Weidner, Moritz Lipperheide, Manfred C. Wirsum

RWTH Aachen University, Aachen, Germany

Stefano Bernero, Martin Gassner

GE Power, Baden, Switzerland

Paper No. GT2017-64348, pp. V04BT04A011; 10 pages
doi:10.1115/GT2017-64348
From:
  • ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
  • Volume 4B: Combustion, Fuels and Emissions
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5085-5
  • Copyright © 2017 by ASME

abstract

Lean premixed combustion has become state of the art technology in gas turbines for power generation because of its very low emission potential in the context of tightening pollutant emissions regulations. Lean premixed combustion is yet also prone to combustion instabilities, resulting in thermo-acoustically induced acoustic pressure oscillations (pulsations). Understanding pulsation behavior over an enginés lifetime is of interest to accurately monitor the engine status, as wear and degradation typically affect combustion behavior and result in changes of both pulsations and emissions. Such improved understanding can be exploited for optimizing both the engine operation concept and the design of relevant hardware parts. In return, pulsation and hardware optimization may lead to reduced degradation and thus inherently more robust long-term operational behavior.

The study presented here is conducted for one specific gas turbine of GE’s GT24/GT26 fleet with sequential annular combustion. Based on operational data of the examined gas turbine, a semi-empirical modeling approach is introduced to describe the pulsations measured in the first (EV) combustion chamber. The target is to reproduce measured pulsation amplitudes as well as their different behaviors with engine load. The modeling presented here has been focused on pulsations in a distinctive frequency range below 1kHz. A model based on a small set of data obtained from initial commissioning is able to represent the pulsation behavior within a normalized root mean square error of 11%. Validation with long-term engine data shows that predicted pulsation levels are reasonably matching the initial operation period but increasingly deviate with engine operating time. By using additional data from later engine commissioning and adjustments, the robustness of the model is sensibly increased. Model accuracy on the training dataset remains similar at around 11%, but validation on the long-term data shows a significant decrease of the normalized root mean square error from over 21% to below 16%. Additional model improvements to further reduce prediction errors on long-term data have been also identified.

Copyright © 2017 by ASME

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In