Prognostics for Hidden and Age-Dependent Nonlinear Degrading Systems

With the rapid development of modern condition monitoring (CM) techniques, condition-based maintenance (CBM) which implements maintenance actions based on the CM information has become an active research area for reducing operation and maintenance costs.

[1]  Wenbin Wang,et al.  A prognosis model for wear prediction based on oil-based monitoring , 2007, J. Oper. Res. Soc..

[2]  Rong Li,et al.  Residual-life distributions from component degradation signals: A Bayesian approach , 2005 .

[3]  Maurizio Guida,et al.  A State-Dependent Wear Model With an Application to Marine Engine Cylinder Liners , 2010, Technometrics.

[4]  Xiao-Sheng Si,et al.  An adaptive and nonlinear drift-based Wiener process for remaining useful life estimation , 2011, 2011 Prognostics and System Health Managment Confernece.

[5]  Maurizio Guida,et al.  An age- and state-dependent Markov model for degradation processes , 2011 .

[6]  T.D. Batzel,et al.  Prognostic Health Management of Aircraft Power Generators , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[7]  Wenbin Wang A two-stage prognosis model in condition based maintenance , 2007, Eur. J. Oper. Res..

[8]  Alaa Elwany,et al.  Residual Life Predictions in the Absence of Prior Degradation Knowledge , 2009, IEEE Transactions on Reliability.

[9]  Donghua Zhou,et al.  Remaining useful life estimation - A review on the statistical data driven approaches , 2011, Eur. J. Oper. Res..

[10]  Li Zeng,et al.  Inferring the Interactions in Complex Manufacturing Processes Using Graphical Models , 2007, Technometrics.

[11]  Michael Pecht,et al.  Application of a state space modeling technique to system prognostics based on a health index for condition-based maintenance , 2012 .

[12]  Jionghua Jin,et al.  State Space Modeling of Sheet Metal Assembly for Dimensional Control , 1999 .

[13]  Gianpaolo Pulcini,et al.  A continuous-state Markov model for age- and state-dependent degradation processes , 2011 .

[14]  Thomas B. Schön,et al.  An Explanation of the Expectation Maximization Algorithm , 2009 .

[15]  Lin Li,et al.  Cost-Effective Updated Sequential Predictive Maintenance Policy for Continuously Monitored Degrading Systems , 2010, IEEE Transactions on Automation Science and Engineering.

[16]  Zhaojun Li,et al.  Continuous-state reliability measures based on fuzzy sets , 2012 .

[17]  Enrico Zio,et al.  Monte Carlo-based filtering for fatigue crack growth estimation , 2009 .

[18]  Zhao Jianmin,et al.  Remaining useful life prediction based on nonlinear state space model , 2011, 2011 Prognostics and System Health Managment Confernece.

[19]  A. H. Christer,et al.  A state space condition monitoring model for furnace erosion prediction and replacement , 1997 .

[20]  Bhaskar Saha,et al.  Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.

[21]  Sheng-Tsaing Tseng,et al.  Mis-Specification Analysis of Linear Degradation Models , 2009, IEEE Transactions on Reliability.

[22]  Donghua Zhou,et al.  Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process , 2012, IEEE Transactions on Reliability.

[23]  G. A. Whitmore,et al.  Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary , 2006, 0708.0346.

[24]  Xiao Wang,et al.  Wiener processes with random effects for degradation data , 2010, J. Multivar. Anal..

[25]  W. Wang,et al.  A data-model-fusion prognostic framework for dynamic system state forecasting , 2012, Eng. Appl. Artif. Intell..

[26]  Sheng-Tsaing Tseng,et al.  Optimal design for step-stress accelerated degradation tests , 2006, IEEE Trans. Reliab..

[27]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[28]  W. J. Padgett,et al.  Inference from Accelerated Degradation and Failure Data Based on Gaussian Process Models , 2004, Lifetime data analysis.

[29]  K. Doksum,et al.  Models for variable-stress accelerated life testing experiments based on Wiener processes and the inverse Gaussian distribution , 1992 .

[30]  Kai Goebel,et al.  Comparison of prognostic algorithms for estimating remaining useful life of batteries , 2009 .

[31]  George J. Vachtsevanos,et al.  A particle-filtering approach for on-line fault diagnosis and failure prognosis , 2009 .

[32]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[33]  C. Joseph Lu,et al.  Using Degradation Measures to Estimate a Time-to-Failure Distribution , 1993 .

[34]  Enrico Zio,et al.  Particle filtering prognostic estimation of the remaining useful life of nonlinear components , 2011, Reliab. Eng. Syst. Saf..

[35]  K. Goebel,et al.  An integrated approach to battery health monitoring using bayesian regression and state estimation , 2007, 2007 IEEE Autotestcon.

[36]  M E Robinson,et al.  Bayesian Methods for a Growth-Curve Degradation Model with Repeated Measures , 2000, Lifetime data analysis.

[37]  Vivek S. Borkar,et al.  Application of nonlinear filtering to credit risk , 2010, Oper. Res. Lett..

[38]  Lin Ma,et al.  LATENT DEGRADATION INDICATOR ESTIMATION USING CONDITION MONITORING INFORMATION , 2008, WCE 2008.

[39]  Donghua Zhou,et al.  Real-time Reliability Prediction for a Dynamic System Based on the Hidden Degradation Process Identification , 2008, IEEE Transactions on Reliability.

[40]  Đani Juričić,et al.  Model-based prognostics of gear health using stochastic dynamical models , 2011 .

[41]  Jye-Chyi Lu,et al.  Statistical inference of a time-to-failure distribution derived from linear degradation , 1997 .

[42]  G A Whitmore,et al.  Modelling Accelerated Degradation Data Using Wiener Diffusion With A Time Scale Transformation , 1997, Lifetime data analysis.

[43]  C. T. Barker,et al.  Optimal non-periodic inspection for a multivariate degradation model , 2009, Reliab. Eng. Syst. Saf..

[44]  Yifan Zhou,et al.  Latent degradation indicators estimation and prediction : a Monte Carlo approach , 2011 .

[45]  P. Kloeden,et al.  Numerical Solution of Stochastic Differential Equations , 1992 .

[46]  Kailash C. Kapur,et al.  Models and customer-centric system performance measures using fuzzy reliability , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[47]  Ratna Babu Chinnam,et al.  Health-State Estimation and Prognostics in Machining Processes , 2010, IEEE Transactions on Automation Science and Engineering.

[48]  Wenbin Wang,et al.  An approximate algorithm for prognostic modelling using condition monitoring information , 2011, Eur. J. Oper. Res..

[49]  Ruey Huei Yeh,et al.  Optimal replacement policies for multistate deteriorating systems , 1994 .

[50]  M. D. Pandey,et al.  The influence of temporal uncertainty of deterioration on life-cycle management of structures , 2009 .

[51]  Nagi Gebraeel,et al.  Sensory-Updated Residual Life Distributions for Components With Exponential Degradation Patterns , 2006, IEEE Transactions on Automation Science and Engineering.