3 edition of On the estimation algorithm used in adaptive performance optimization of turbofan engines found in the catalog.
On the estimation algorithm used in adaptive performance optimization of turbofan engines
by National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, National Technical Information Service, distributor] in [Washington, DC], [Springfield, Va
Written in English
|Statement||Martín D. España and Glenn B. Gilyard.|
|Series||NASA technical memorandum -- 4551.|
|Contributions||United States. National Aeronautics and Space Administration. Scientific and Technical Information Program.|
|The Physical Object|
""MBB Studies Variable-Camber Wing for Airbus," JPRS-WST, Aug. (N). ^'Face to Face With Wesley Harris," Aerospace America, Sept. , p. 6. ^Espafta, Martin D. and Glenn B. Gilyard, On the Esti- mation Algorithm Used in Adaptive Performance Optimization of Turbofan Engines, NASA TM, Dec. Compared with the AMM-based FDI approach, the filters in IMM-based FDI algorithm interact with each other which lead to improved performance. The IMM-based FDI algorithm is compos.
An alternative is to use an approximate algorithm that solves the problem to an acceptable level of quality and provides such a solution in a reasonable time. Us-ing optimisation algorithms typically requires choosing the settings of tuning pa-rameters that adjust algorithm performance subject to this compromise betweenFile Size: 3MB. Online Estimation of Wind Turbine Tip Speed Ratio by Adaptive Neuro-Fuzzy Algorithm Aamer Bilal Asghar1, Xiaodong Liu2 School of Control Science & Engineering Faculty of Electronic Information & Electrical Engineering Dalian University of Technology Dalian , P.R. China Abstract—The efficiency of a wind turbine highly depends on.
Many other approaches to the performance analysis of adaptive estimation (hybrid estimation in which the hypothesis testing is performed using adaptive weights) can be found in the references cited in . Baram et al.  provide conditions under which, for a set of . Rough set based gas turbine fault isolation study. By Lihui. Wang. Get PDF (2 MB) Multiple operating point analysis using genetic algorithm optimization for gas turbine diagnostics”, ISABE, th International Symposium on air breathing engines, , (). Multiple point adaptive performance simulation tuned to aero-engine test Author: Lihui. Wang.
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The study allows us to decide, for the F engine, which measurement biases have more influence over the estimation process and which estimates are affected the most by the biases. We next propose a Luenberger-type estimation algorithm based on the same (steady-state) model used by the optimization process.
On the Estimation Algorithm Used in Adaptive Performance Optimization of Turbofan Engines Author: Martin D.
Espana and Glenn B. Gilyard Subject: NASA TM Keywords: Adaptive optimization, Measurement biases influence, Parameter estimatio n, Performance seeking control, Propulsion systems Created Date: 6/5/ AM. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect.
On the estimation algorithm used in adaptive performance optimization of turbofan engines. Get this from a library. On the estimation algorithm used in adaptive performance optimization of turbofan engines.
[Martín D España; United States. National Aeronautics and Space Administration. Scientific and Technical Information Program.]. The performance seeking control algorithm is designed to continuously optimize the performance of propulsion systems. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect to nominal : Glenn B.
Gilyard and Martin D. Espana. A new algorithm, based on the engine’s (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of.
A new adaptive modeling method for aircraft engine by using equilibrium manifold (EM) and its expansion (EME) model is presented, following research undertaken by the authors at School of Transport Cited by: 7.
The developed method was applied to the performance prediction of a model gas turbine engine similar to EJ low-bypass turbofan engine running at different altitudes, Mach numbers, and part load, with and without degradation, by using simulated Cited by: Multi-objective genetic algorithms (GAs) are used for Pareto approach optimization of thermodynamic cycle of ideal turbojet engines.
On this behalf, a new diversity preserving algorithm is proposed to enhance the performance of multi-objective evolutionary algorithms (MOEAs) in optimization problems with more than two objective functions.
1 These are rarely used because the obj ective of most status matches is to. predict new engine performance, not overhauled engine performance.
2 These “assumptions” (such as inlet loss) reflect the business arrangements. between the engine company and the airplane manufacturer. The purpose of this paper is to introduce a strategy for measurement selection by parameter signatures and to demonstrate its applicability to the transient decks of turbojet engines.
The validity of the selected outputs in providing observability to all the engine model parameters is independently verified by successful estimation of parameters by nonlinear least-squares by: 8.
The Multiple Model Adaptive Estimation Algorithm (MMAE)  is an algorithm in which, for hypothesis testing, the Kalman ﬁlter residuals are used to form likelihood func-tions for the different modes, which are then used as adaptive weights to ﬁnd the most probable mode.
A reﬁnement of the MMAE, the Interacting Multiple Model Algorithm (IMM). The states with high degree of observability and the measurement sets with high overall degree of observability result in high estimation accuracy in gas path diagnostics.
System Identification of Jet Engines,” On the Estimation Algorithm for Adaptive Performance Optimization of Turbofan Engines,” Paper No. AIAA– 10 Cited by: 1. Multiple-Point Adaptive Performance Simulation Tuned to Aeroengine Test-Bed Data.
An Improved Teaching-Learning Based Optimization Algorithm and Its Application to Aero-Engine Start Model Adaptation. IEEE Access, Vol.
7 Aero Gas Turbine Flight Performance Estimation Using Engine Gas Path Measurements. Yi-Guang Li;Cited by: Fig. Schematic representation the case of health parameter estimation because the health pa- rameters are modeled as constant biases (even though the rest of the state vector is still modeled as time varying).
Turbofan engine health monitoring Fig. 1 shows a schematic representation of a turbofan en- gine .Cited by: Stages of a turbofan engine. Genetic algorithms are used in this study because they are able to quickly optimize the objective functions involving subfunctions of multivariates. The resultant parameter values are accurate and can be used for design optimization in the early engine design by: M.
Espańa, “On the estimation algorithm for adaptive performance optimization of turbofan engines,” Chi Ea Chi Extended Abstracts on Human Factors in Computing Systems, vol. 24, no. 1, pp.View at: Google ScholarCited by: 1.
Evolutionary algorithm State of the technology for material parameter estimation Divides a population into complexes Two phases after initialization: Local search per complex Global evolution between complexes ABC I.
Swarm intelligence optimization algorithm Mimics foraging behavior of a honey bee swarm Combines local, global and random search. Estimation of Turbofan Engine Performance Model Accuracy and Confidence Bounds Bryce A. Roth, Dimitri N.
Mavris School of Aerospace Engineering Georgia Institute of Technology Atlanta, GA and David L. Doel GE Aircraft Engines Cincinnati, OH Abstract This paper explores the application of InferenceCited by: 8.
Abstract: Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk Cited by: 6.implementation of algorithms for performance trend monitoring of PW engines.
Two tools were developed using the R programming language. The first tool is responsible for the acquisition of stability points in cruise from recorded flight data using specific conditions and criteria and, after.predict accurately the performance of each of its engines.
DIAGNOSIS AND PROGNOSIS The research described here has been carried out for a civil three-shaft, high by-pass turbofan. This engine is monitored via 10 measurements (z), the operating condition is defined using 4 quantities (u).
The 12 performance parameters (x), efficiencies andFile Size: KB.