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ship speed power performance under relative wind profile. in relation to sensor fault detection

Journal of Ocean Engineering and Science 2018年第4期3卷 355-366页

作者： Lokukaluge P.Perera B.Mo UiT The Arctic University of Norway TromsoNorway SINTEF Ocean TrondheimNorway

Statistical data analysis and visualization approaches to identify ship speed power performance under relative wind(*** wind)profile. are considered in this *** performance and navigation data of a selected vessel are analyzed,where various data anomalies,*** related erroneous data conditions,are *** erroneous data conditions are investigated and several approaches to isolate such situations are also presented by considering appropriate data visualization ***,the cleaned data are used to derive various relationships among ship performance and navigation parameters that have been visualized in this study,*** results show that the wind profile. along ship routes can be used to evaluate vessel performance and navigation conditions by assuming the respective sea states relate to their wind ***,the results are useful to derive appropriate mathematical models that represent ship performance and navigation *** mathematical models can be used for weather routing type applications(*** planning),where the respective weather forecast can be used to derive optimal ship routes to improve vessel performance and reduce fuel *** study presents not only an overview of statistical data analysis of ship performance and navigation data but also the respective challenges in data anomalies(*** data intervals and sensor faults)due to onboard sensors and data handling ***,the respective solutions to such challenges in data quality have also been presented by considering data visualization approaches.

关键词： Speed power performance Data anomaly detection Sensor fault identification Weather routing Statistical data analysis ship wind profile.

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