This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.
Skip Nav Destination
ASME Turbo Expo 2010: Power for Land, Sea, and Air
June 14–18, 2010
Glasgow, UK
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
978-0-7918-4398-7
PROCEEDINGS PAPER
A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications Available to Purchase
Donald L. Simon,
Donald L. Simon
NASA Glenn Research Center, Cleveland, OH
Search for other works by this author on:
Jonathan S. Litt
Jonathan S. Litt
NASA Glenn Research Center, Cleveland, OH
Search for other works by this author on:
Donald L. Simon
NASA Glenn Research Center, Cleveland, OH
Jonathan S. Litt
NASA Glenn Research Center, Cleveland, OH
Paper No:
GT2010-22818, pp. 191-200; 10 pages
Published Online:
December 22, 2010
Citation
Simon, DL, & Litt, JS. "A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications." Proceedings of the ASME Turbo Expo 2010: Power for Land, Sea, and Air. Volume 3: Controls, Diagnostics and Instrumentation; Cycle Innovations; Marine. Glasgow, UK. June 14–18, 2010. pp. 191-200. ASME. https://doi.org/10.1115/GT2010-22818
Download citation file:
18
Views
Related Articles
A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications
J. Eng. Gas Turbines Power (July,2011)
A Comparison of Ordinary Differential Equation Solvers for Dynamical Systems With Impacts
J. Comput. Nonlinear Dynam (November,2017)
Optimizing Aircraft Performance With Adaptive, Integrated Flight/Propulsion Control
J. Eng. Gas Turbines Power (January,1991)
Related Chapters
Measuring Graph Similarity Using Node Indexing and Message Passing
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
Ultra High-Speed Microbridge Chaos Domain
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
A Novel Approach for LFC and AVR of an Autonomous Power Generating System
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)