Supporting predictive maintenance of a ship by analysis of onboard measurements
Ship hull and propeller fouling has a severe impact both on fuel costs and on greenhouse gas emission, thus, it is an important subject to consider when developing a maintenance plan to enhance energy efficiency and reduce gas emissions from ships. This paper presents a two-step approach for evaluat...
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sg-ntu-dr.10356-1606532022-07-29T05:25:17Z Supporting predictive maintenance of a ship by analysis of onboard measurements Liu, Shukui Chen, Haoliang Shang, Baoguo Papanikolaou, Apostolos School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Ship Fouling Onboard Measurement Ship hull and propeller fouling has a severe impact both on fuel costs and on greenhouse gas emission, thus, it is an important subject to consider when developing a maintenance plan to enhance energy efficiency and reduce gas emissions from ships. This paper presents a two-step approach for evaluating the actual propulsive performance of a ship through analyzing continuous onboard measurement. First, the onboard monitored data are corrected for the wind and wave effects using fast and transparent empirical methods. Second, the corrected data are filtered based on hydrodynamic criteria. A case study is presented to demonstrate the effectiveness of the methodol-ogy. Subsequently, the processed data are analyzed by mathematical tools to derive an engine power–rpm curve to represent the actual propulsive performance of the ship. By comparing the derived curve against the nominal curve for engine design, it is possible to identify the deterioration of the ship’s condition, which is the key task in developing the identification capability that is needed in a proactive maintenance procedure. This methodology is expected to support the maritime sector in combating climate change by reducing the Greenhouse Gas (GHG) emissions from ship operations. Published version 2022-07-29T05:25:16Z 2022-07-29T05:25:16Z 2022 Journal Article Liu, S., Chen, H., Shang, B. & Papanikolaou, A. (2022). Supporting predictive maintenance of a ship by analysis of onboard measurements. Journal of Marine Science and Engineering, 10(2), 215-. https://dx.doi.org/10.3390/jmse10020215 2077-1312 https://hdl.handle.net/10356/160653 10.3390/jmse10020215 2-s2.0-85124289631 2 10 215 en Journal of Marine Science and Engineering © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons. org/licenses/by/4.0/). application/pdf |
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Engineering::Mechanical engineering Ship Fouling Onboard Measurement Liu, Shukui Chen, Haoliang Shang, Baoguo Papanikolaou, Apostolos Supporting predictive maintenance of a ship by analysis of onboard measurements |
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Ship hull and propeller fouling has a severe impact both on fuel costs and on greenhouse gas emission, thus, it is an important subject to consider when developing a maintenance plan to enhance energy efficiency and reduce gas emissions from ships. This paper presents a two-step approach for evaluating the actual propulsive performance of a ship through analyzing continuous onboard measurement. First, the onboard monitored data are corrected for the wind and wave effects using fast and transparent empirical methods. Second, the corrected data are filtered based on hydrodynamic criteria. A case study is presented to demonstrate the effectiveness of the methodol-ogy. Subsequently, the processed data are analyzed by mathematical tools to derive an engine power–rpm curve to represent the actual propulsive performance of the ship. By comparing the derived curve against the nominal curve for engine design, it is possible to identify the deterioration of the ship’s condition, which is the key task in developing the identification capability that is needed in a proactive maintenance procedure. This methodology is expected to support the maritime sector in combating climate change by reducing the Greenhouse Gas (GHG) emissions from ship operations. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Liu, Shukui Chen, Haoliang Shang, Baoguo Papanikolaou, Apostolos |
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Article |
author |
Liu, Shukui Chen, Haoliang Shang, Baoguo Papanikolaou, Apostolos |
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Liu, Shukui |
title |
Supporting predictive maintenance of a ship by analysis of onboard measurements |
title_short |
Supporting predictive maintenance of a ship by analysis of onboard measurements |
title_full |
Supporting predictive maintenance of a ship by analysis of onboard measurements |
title_fullStr |
Supporting predictive maintenance of a ship by analysis of onboard measurements |
title_full_unstemmed |
Supporting predictive maintenance of a ship by analysis of onboard measurements |
title_sort |
supporting predictive maintenance of a ship by analysis of onboard measurements |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/160653 |
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1739837404320104448 |