Hidden Markov Model for Health Estimation and Prognosis of Turbofan Engines

Authors - A. Giantomassi, F. Ferracuti, A. Benini, G. Ippoliti, S. Longhi, A. Petrucci

Abstract - 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.

This paper is available on ASME Digital Collection.

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