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On Inverse Problems in Turbine Engine Parameter Estimation

[+] Author Affiliations
M. Henriksson

Volvo Aero Corporation AB, Trollhättan, Sweden

S. Borguet, O. Léonard

University of Liège, Liège, Wallonia, Belgium

T. Grönstedt

Chalmers University of Technology, Göteborg, Sweden

Paper No. GT2007-27756, pp. 703-711; 9 pages
doi:10.1115/GT2007-27756
From:
  • ASME Turbo Expo 2007: Power for Land, Sea, and Air
  • Volume 1: Turbo Expo 2007
  • Montreal, Canada, May 14–17, 2007
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 0-7918-4790-X | eISBN: 0-7918-3796-3
  • Copyright © 2007 by ASME

abstract

This paper extends previous work on model order reduction based on singular value decomposition. It is shown how the decrease in estimator variance must be balanced against the bias on the estimate inevitably introduced by solving the inverse problem in a reduced order space. A proof for the decrease in estimator variance by means of multi-point analysis is provided. The proof relies on comparing the Cramer-Rao lower bound of the single point and the multi-point estimators. Model order selection is discussed in the presence of a varying degree of a priori parameter information, through the use of a regularization parameter. Simulation results on the SR-30 turbojet engine indicate that the theoretically attainable multi-point improvements are difficult to realize in practical jet engine applications.

Copyright © 2007 by ASME

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