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J. Lawless, M. Crowder (2004)
Covariates and Random Effects in a Gamma Process Model with Application to Degradation and FailureLifetime Data Analysis, 10
F. Kozin, J. Bogdanoff (1985)
Analysis of Stochastic Equation Models of Crack Growth
M. Kallen, J. Noortwijk (2005)
Optimal maintenance decisions under imperfect inspectionReliab. Eng. Syst. Saf., 90
D. Lu, M. Pandey, W. Xie (2013)
An efficient method for the estimation of parameters of stochastic gamma process from noisy degradation measurementsProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 227
R. Zhou, N. Gebraeel, N. Serban (2012)
Degradation modeling and monitoring of truncated degradation signalsIIE Transactions, 44
K. Son, M. Fouladirad, A. Barros (2016)
Remaining useful lifetime estimation and noisy gamma deterioration processReliab. Eng. Syst. Saf., 149
Chien‐Yu Peng, S. Tseng (2009)
Mis-Specification Analysis of Linear Degradation ModelsIEEE Transactions on Reliability, 58
G. Whitmore (1995)
Estimating degradation by a wiener diffusion process subject to measurement errorLifetime Data Analysis, 1
Xiaosheng Si, Wenbin Wang, Changhua Hu, Donghua Zhou (2014)
Estimating Remaining Useful Life With Three-Source Variability in Degradation ModelingIEEE Transactions on Reliability, 63
Qingqing Zhai, Z. Ye (2017)
Robust Degradation Analysis With Non-Gaussian Measurement ErrorsIEEE Transactions on Instrumentation and Measurement, 66
F Kozin, JL Bogdanoff (1985)
Probabilistic Methods in the Mechanics of Solids and Structures
L. Bordes, C. Paroissin, A. Salami (2010)
Parametric inference in a perturbed gamma degradation processCommunications in Statistics - Theory and Methods, 45
G. Pulcini (2016)
A perturbed gamma process with statistically dependent measurement errorsReliab. Eng. Syst. Saf., 152
G. Welch, G. Bishop (1995)
An Introduction to Kalman Filter
Zhengguo Xu, Yindong Ji, Donghua Zhou (2008)
Real-time Reliability Prediction for a Dynamic System Based on the Hidden Degradation Process IdentificationIEEE Transactions on Reliability, 57
H. Akaike (1974)
A new look at the statistical model identificationIEEE Transactions on Automatic Control, 19
Xiaohui Si, Wenbin Wang, Changhua Hu, Donghua Zhou, M. Pecht (2012)
Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation ProcessIEEE Transactions on Reliability, 61
D Simon (2006)
Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
This paper proposes and illustrates a new perturbed gamma degradation process where the measurement error is modeled as a non‐Gaussian random variable that depends stochastically on the actual degradation level. The expression of the likelihood function for a generic set of noisy degradation measurements is derived, and the expression of the remaining useful life distribution of a degrading unit that fails when its degradation level exceeds a given threshold limit is formulated. A particle filter method is suggested, which allows one to compute the likelihood function and to estimate the remaining useful life distribution in a quick yet efficient manner. In addition, a closed‐form approximation of the perturbed gamma process is proposed to use in the special, yet meaningful, case where the standard deviation of the measurement error depends linearly on the actual degradation level. Finally, an applicative example is discussed, where the parameters of the perturbed gamma process, the remaining useful life distribution, and the mean remaining useful life of the degrading units are estimated from a set of noisy real degradation data.
Applied Stochastic Models in Business and Industry – Wiley
Published: Mar 1, 2019
Keywords: ; ; ; ; ;
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