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Hidden Markov Model for Health Estimation and Prognosis of Turbofan Engines

[+] Author Affiliations
Andrea Giantomassi, Francesco Ferracuti, Alessandro Benini, Gianluca Ippoliti, Sauro Longhi, Antonio Petrucci

Università Politecnica delle Marche, Ancona, Italy

Paper No. DETC2011-48174, pp. 681-689; 9 pages
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 3: 2011 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5480-8
  • Copyright © 2011 by ASME


Determining the residual life time of systems is a determinant factor for machinery and environment safety. In this paper the problem of estimate the residual useful life (RUL) of turbo-fan engines is addressed. The adopted approach is especially suitable for situations in which a large amount of data is available offline, by allowing the processing of such data for the determination of RUL. The procedure allows to calculate the RUL through the following steps: features extraction by Artificial Neural Networks (ANN) and determination of remaining life time by-prediction models based on a Hidden Markov Model (HMM). Simulations confirm the effectiveness of the proposed approach and the promising power of Bayesian methods.

Copyright © 2011 by ASME
Topics: Engines , Turbofans



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