0

Full Content is available to subscribers

Subscribe/Learn More  >

Development of On-Line Performance Diagnostics Program of a Helicopter Propulsion System

[+] Author Affiliations
Jayoung Ki

EASY Gas Turbine R&D Co., Ltd., Daejeon, Republic of Korea

Changduk Kong, Seonghee Kho

Chosun University, Kwangju, Republic of Korea

Jaehwan Kim, Ieeki Ahn, Daesung Lee

Korea Aerospace Research Institute, Daejeon, Republic of Korea

Paper No. GT2009-59519, pp. 189-195; 7 pages
doi:10.1115/GT2009-59519
From:
  • ASME Turbo Expo 2009: Power for Land, Sea, and Air
  • Volume 4: Cycle Innovations; Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Marine
  • Orlando, Florida, USA, June 8–12, 2009
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4885-2 | eISBN: 978-0-7918-3849-5
  • Copyright © 2009 by ASME

abstract

The engine health monitoring system has been generally applied to the aircraft system to improve reliability and durability of the aircraft propulsion system and to minimize its operational cost. The helicopter flies at low altitude level flight mode in its own operational range comparing to other aircraft categories. The low level flight means that the engine operates at variable atmospheric condition such as hot and cold temperature, snow, heavy rain, etc. Furthermore, it may increase the possibility of foreign object ingestion, such as sand, dust, etc., i.e. this operating condition gives rise to damages of engine gas path components. Because types and severities of most helicopter engine faults are very complicate, the conventional model based fault diagnostic approach like the GPA (Gas Path Analysis) method is not adequate to monitor such a complex engine fault condition. An on-line diagnostic program was developed by using SIMULINK, where measurement signals were simulated by an input module. This study proposes a neural network algorithm for calculating variation of mass flow and efficiency in each engine component from measuring data. The neural network was trained by damages at each component such as compressor, compressor turbine or power turbine. The used database for training the neural network was obtained from simulation under various flight conditions. Reliability and capability of the developed on-line diagnostics program were evaluated through application to a helicopter engine health monitoring.

Copyright © 2009 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