Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system-Reference-Cited by-同舟云学术

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Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Published:2018-01 Issue:1 Volume:31 Page:1-9
ISSN:1000-9361
Container-title:Chinese Journal of Aeronautics
language:en
Short-container-title:Chinese Journal of Aeronautics

Author:

HANACHI Houman,LIU Jie,MECHEFSKE Christopher

Funder

Fond de Recherche Nature et Technologies

Natural Sciences and Engineering Research Council

Life Prediction Technologies Inc.

Publisher

Elsevier BV

Subject

Mechanical Engineering,Aerospace Engineering

Reference34 articles.

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2. Granovskiy A, Kostege M, Lomakin N. Parametrical investigation of turbine stages with open tip clearance for the purpose of stage efficiency increase. Proceedings of ASME turbo expo 2010 conference; 2010 June 14–18. Glasgow, UK. New York: ASME; 2010. p. 1425–32.

3. Matsuda H, Otomo F, Kawagishi H, Inomata A, Niizeki Y, Sasaki T. Influence of surface roughness on turbine nozzle profile loss and secondary loss. Proceedings of ASME turbo expo 2006 conference; 2006 May 8–11. Barcelona, Spain. New York: ASME; 2006. p. 781–8.

4. Panov V. Auto-tuning of real-time dynamic gas turbine models. Proceedings of ASME turbo expo 2014 conference; 2014 June 16–20; Düsseldorf, Germany. New York: ASME; 2014.

5. Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation;Hanachi;Mech Syst Signal Process,2016

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