Prognosis of gear health using stochastic dynamical models with online parameter estimation
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
In this paper we present a statistical approach to the estimation of the time in which an operating gear will achieve the critical stage. The approach relies on measured vibration signals. From these signals features are extracted first and then their evolution over time is predicted. This is done owing to the dynamic model that relates hidden degradation phenomena with measured outputs. The Expectation-Maximization algorithm is used to estimate the parameters of the underlying state- space model on-line. Time to reach safety alarm threshold is determined by making the prediction using the estimated linear model. The results obtained on a pilot testbed are presented.
How to Cite
##plugins.themes.bootstrap3.article.details##
damage detection, damage modeling, gears, materials damage prognostics, prognostics, remaining useful life (RUL)
(G. Niu, 2009) Bo-Suk Yang G. Niu. Dempstershafer regression for multi-step-ahead time-series prediction towards data-driven machinery prognosis. Mechanical Systems and Signal Processing, 23:740– 751, 2009.
(Gibson and Ninness, 2005) S. Gibson and B. Nin- ness. Robust maximum-likelihood estimation of multivariable dynamic systems. Automatica, 41:1667–1682, 2005.
(Ho and Randall, 2000) D. Ho and R. B. Randall. Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals. Mechanical Systems and Signal Processing, 14:763–788, 2000.
(Howard, 1994) I. Howard. A review of rolling element bearing vibration ”Detection, Diagnosis and Prognosis”. DSTO Aeronautical and Maritime Research Laboratory, 1994.
(Orchard and Vachtsevanos, 2009) M. E. Orchard and G. J. Vachtsevanos. A particle-filtering approachfor on-line fault diagnosis and failure prognosis. Transactions of the Institute of Measurement and Control, 31:221246, 2009.
(Rubini and Meneghetti, 2001) R. Rubini and U. Meneghetti. Application of the envelope and wavelet transform and analyses for the diagnosis of incipient faults in ball bearings. Mechanical Systems and Signal Processing, 15:287–302, 2001.
(W. Q. Wanga and Ismailb, 2004) M. F. Golnaraghib W. Q. Wanga and F. Ismailb. Prognosis of machine health condition using neuro-fuzzy systems. Mechanical Systems and Signal Processing, 18:813– 831, 2004.
(Wang et al., 2003) W. Q. Wang, M. F. Golnaragh, and F. Ismail. Prognosis of machine health condition using neuro-fuzzy systems. Mechanical Systems and Signal Processing, 18:813–831, 2003.
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.