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Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Machinery prognostics is one of the major tasks in condition based maintenance (CBM),
which aims to predict the remaining useful life (RUL) of machinery based on condition …
which aims to predict the remaining useful life (RUL) of machinery based on condition …
Remaining useful life prediction based on a multi-sensor data fusion model
With the rapid development of Industrial Internet of Things, more and more sensors have
been used for condition monitoring and prognostics of industrial systems. Big data collected …
been used for condition monitoring and prognostics of industrial systems. Big data collected …
Copula-based reliability analysis of degrading systems with dependent failures
Consider a coherent system, in which the degradation processes of its performance
characteristics are positively correlated, this paper systematically investigates a bivariate …
characteristics are positively correlated, this paper systematically investigates a bivariate …
Stochastic process-based degradation modeling and RUL prediction: from Brownian motion to fractional Brownian motion
Brownian motion (BM) has been widely used for degradation modeling and remaining
useful life (RUL) prediction, but it is essentially Markovian. This implies that the future state in …
useful life (RUL) prediction, but it is essentially Markovian. This implies that the future state in …
A Bayesian inference for remaining useful life estimation by fusing accelerated degradation data and condition monitoring data
This article addresses the problem of estimating the remaining useful life (RUL) of degrading
products by fusing the accelerated degradation data and condition monitoring (CM) data …
products by fusing the accelerated degradation data and condition monitoring (CM) data …
Big data and reliability applications: The complexity dimension
Big data features not only large volumes of data but also data with complicated structures.
Complexity imposes unique challenges on big data analytics. Meeker and Hong (2014; …
Complexity imposes unique challenges on big data analytics. Meeker and Hong (2014; …
Analysis of multivariate dependent accelerated degradation data using a random-effect general Wiener process and D-vine Copula
A modern product usually shows multiple performance characteristics that degrade
simultaneously. It is quite common that these degradation processes are dependent due to …
simultaneously. It is quite common that these degradation processes are dependent due to …
An artificial neural network supported stochastic process for degradation modeling and prediction
An artificial neural network supported stochastic process for degradation modeling and
prediction is proposed in this paper. An artificial neural network is applied to describe the …
prediction is proposed in this paper. An artificial neural network is applied to describe the …
An artificial neural network supported Wiener process based reliability estimation method considering individual difference and measurement error
Due to the powerful ability of artificial neural network in data fitting, it has been applied to
describe the mean function in Wiener process for degradation modeling and estimating …
describe the mean function in Wiener process for degradation modeling and estimating …
Degradation prognostics of aerial bundled cables based on multi-sensor data fusion
Development of advanced health monitoring sensors and high-performance computing
enabled multi-sensors information to analyse degradation in complex engineering …
enabled multi-sensors information to analyse degradation in complex engineering …