SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:mdh-57249"
 

Search: onr:"swepub:oai:DiVA.org:mdh-57249" > Estimation and Miti...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Estimation and Mitigation of Unknown Airplane Installation Effects on GPA Diagnostics

Stenfelt, Mikael (author)
Mälardalens universitet,Framtidens energi,SAAB Aeronut, S-58254 Linkoping, Sweden.
Kyprianidis, Konstantinos (author)
Mälardalens universitet,Framtidens energi
 (creator_code:org_t)
2022-01-04
2022
English.
In: Machines. - : MDPI. - 2075-1702. ; 10:1
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • In gas turbines used for airplane propulsion, the number of sensors are kept at a minimum for accurate control and safe operation. Additionally, when data are communicated between the airplane main computer and the various subsystems, different systems may have different constraints and requirements regarding what data transmit. Early in the design process, these parameters are relatively easy to change, compared to a mature product. If the gas turbine diagnostic system is not considered early in the design process, it may lead to diagnostic functions having to operate with reduced amount of data. In this paper, a scenario where the diagnostic function cannot obtain airplane installation effects is considered. The installation effects in question is air intake pressure loss (pressure recovery), bleed flow and shaft power extraction. A framework is presented where the unknown installation effects are estimated based on available data through surrogate models, which is incorporated into the diagnostic framework. The method has been evaluated for a low-bypass turbofan with two different sensor suites. It has also been evaluated for two different diagnostic schemes, both determined and underdetermined. Results show that, compared to assuming a best-guess constant-bleed and shaft power, the proposed method reduce the RMS in health parameter estimation from 26% up to 80% for the selected health parameters. At the same time, the proposed method show the same degradation pattern as if the installation effects were known.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Keyword

gas turbine diagnostics
gas path analysis
installation effects
neural networks

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

  • Machines (Search for host publication in LIBRIS)

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Find more in SwePub

By the author/editor
Stenfelt, Mikael
Kyprianidis, Kon ...
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Mechanical Engin ...
and Energy Engineeri ...
Articles in the publication
Machines
By the university
Mälardalen University

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view