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Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
by
Nystad, Bent H.
, Gola, Giulio
, Mangili, Francesca
, Baraldi, Piero
, Zio, Enrico
in
AHP
/ Choke Valve Erosion
/ Chokes (restrictions)
/ Cluster analysis
/ Engineering Sciences
/ Ensemble
/ Flow coefficients
/ Kernel Regression
/ Kernels
/ Offshore drilling rigs
/ Offshore platforms
/ Parameter estimation
/ Prognostics and Health Management
/ Regression analysis
/ Regression models
/ Research Article
/ Valves
2014
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Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
by
Nystad, Bent H.
, Gola, Giulio
, Mangili, Francesca
, Baraldi, Piero
, Zio, Enrico
in
AHP
/ Choke Valve Erosion
/ Chokes (restrictions)
/ Cluster analysis
/ Engineering Sciences
/ Ensemble
/ Flow coefficients
/ Kernel Regression
/ Kernels
/ Offshore drilling rigs
/ Offshore platforms
/ Parameter estimation
/ Prognostics and Health Management
/ Regression analysis
/ Regression models
/ Research Article
/ Valves
2014
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Do you wish to request the book?
Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
by
Nystad, Bent H.
, Gola, Giulio
, Mangili, Francesca
, Baraldi, Piero
, Zio, Enrico
in
AHP
/ Choke Valve Erosion
/ Chokes (restrictions)
/ Cluster analysis
/ Engineering Sciences
/ Ensemble
/ Flow coefficients
/ Kernel Regression
/ Kernels
/ Offshore drilling rigs
/ Offshore platforms
/ Parameter estimation
/ Prognostics and Health Management
/ Regression analysis
/ Regression models
/ Research Article
/ Valves
2014
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Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
Journal Article
Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
2014
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Overview
This paper considers the problem of erosion in choke valves used on offshore oil platforms. A parameter commonly used to assess the valve erosion state is the flow coefficient, which can be analytically calculated as a function of both measured and allocated parameters. Since the allocated parameter estimation is unreliable, the obtained evaluation of the valve erosion level becomes inaccurate and undermines the possibility of achieving good prognostic results. In this work, cluster analysis is used to verify the allocated parameter values and an ensemble of Kernel Regression models is used to correct the valve flow coefficient estimates.
Publisher
Springer Netherlands,Springer Nature B.V,Atlantis Press,Springer
Subject
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