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dc.contributor.authorPerera, Lokukaluge Prasad
dc.contributor.authorMo, Brage
dc.date.accessioned2018-12-17T10:15:47Z
dc.date.available2018-12-17T10:15:47Z
dc.date.issued2018-11-19
dc.description.abstractStatistical Data analysis and visualization approaches to identify ship speed power performance under relative wind (i.e. apparent wind) profiles are considered in this study. Ship performance and navigation data of a selected vessel are analyzed, where various data anomalies, i.e. sensor related erroneous data conditions, are identified. Those erroneous data conditions are investigated and several approaches to isolate such situations are presented by considering appropriate data visualization methods. Then, the cleaned data are used to derive various relationships among ship performance and navigation parameters that have been visualized in this study, appropriately. The results show that wind profiles along ship routes can be used to evaluate vessel performance and navigation conditions by assuming the respective sea states relate to their wind conditions. Hence, the results are useful to derive appropriate mathematical models that can represent ship performance and navigation conditions. Such mathematical models can be used for weather routing type applications (i.e. voyage planning), where the respective weather forecast can be used to derive optimal ship routes to improve vessel performance and reduce fuel consumption. This study presents not only an overview of statistical data analysis of ship performance and navigation data but also the respective challenges in data anomalies (i.e. erroneous data intervals and sensor faults) due to onboard sensors and data handling. Furthermore, the respective solutions to such challenges in data quality have also been presented by considering data visualization approaches in this study.en_US
dc.descriptionSource at <a href=https://doi.org/10.1016/j.joes.2018.11.001> https://doi.org/10.1016/j.joes.2018.11.001</a>. Licensed <a href=http://creativecommons.org/licenses/by-nc-nd/4.0/> CC BY-NC-ND 4.0.</a>en_US
dc.identifier.citationPerera, L.P. & Mo, B. (2018). Ship speed power performance under relative wind profiles in relation to sensor fault detection. <i>Journal of Ocean Engineering and Science</i>, 3(4), 355-366. https://doi.org/10.1016/j.joes.2018.11.001en_US
dc.identifier.cristinIDFRIDAID 1634608
dc.identifier.doi10.1016/j.joes.2018.11.001
dc.identifier.issn2468-0133
dc.identifier.urihttps://hdl.handle.net/10037/14353
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalJournal of Ocean Engineering and Science
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/SFI/237917/Norway/SFI Smart Maritime - Norwegian Centre for improved energy-efficiency and reduced emissions from the maritime sector//en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Technology: 500::Marine technology: 580en_US
dc.subjectVDP::Teknologi: 500::Marin teknologi: 580en_US
dc.subjectSpeed power performanceen_US
dc.subjectData anomaly detectionen_US
dc.subjectSensor fault identificationen_US
dc.subjectWeather routingen_US
dc.subjectStatistical data analysisen_US
dc.subjectShip wind profileen_US
dc.titleShip speed power performance under relative wind profiles in relation to sensor fault detectionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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