Volume 7, Issue 2, April 2014, Pages 225 - 241
Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms
Authors
Piero Baraldi, Enrico Zio, Francesca Mangili, Giulio Gola, Bent H. Nystad
Corresponding Author
Piero Baraldi
Received 14 September 2011, Accepted 27 November 2013, Available Online 1 April 2014.
- DOI
- 10.1080/18756891.2013.874670How to use a DOI?
- Keywords
- AHP, Choke Valve Erosion, Ensemble, Kernel Regression, Prognostics and Health Management
- Abstract
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.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Piero Baraldi AU - Enrico Zio AU - Francesca Mangili AU - Giulio Gola AU - Bent H. Nystad PY - 2014 DA - 2014/04/01 TI - Ensemble of Kernel Regression Models for Assessing the Health State of Choke Valves in Offshore Oil Platforms JO - International Journal of Computational Intelligence Systems SP - 225 EP - 241 VL - 7 IS - 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2013.874670 DO - 10.1080/18756891.2013.874670 ID - Baraldi2014 ER -