Jonathan Bailey, R. Bamford, Suvabrata Das, Soma S. Maroju, R. J. Barker
{"title":"生成Glen Lyon FPSO的数字孪生体","authors":"Jonathan Bailey, R. Bamford, Suvabrata Das, Soma S. Maroju, R. J. Barker","doi":"10.1115/omae2022-80547","DOIUrl":null,"url":null,"abstract":"\n A Digital Twin has been developed for the Glen Lyon FPSO to maintain vessel integrity and ensure operation within the allowable design limits. At the core of this Digital Twin are two components: the Integrated Marine Monitoring System (IMMS) installed on the FPSO, and BMT DEEP, a cloud-based platform that stores, manages, integrates, post-processes and displays the vast data sets collected by the IMMS as well as other data sources. This paper focuses on harnessing the benefits of Digital Twin Technology, by bringing in data from all sources and enabling to synthesize and monitor the FPSO in near real-time from any remote location. This Digital Twin is designed to allow rapid query of the data by filtering with any time window in terms of hour, day, month, quarter, and year of data collection for the life of the asset.\n Several sensors feed data to the Glen Lyon IMMS. The sensors include FPSO motion, stress response monitoring, and metocean monitoring. In addition to the FPSO based measurements, metocean data is also available from Met Office weather buoy K7, and wind measurements from the nearby Clair platform. A composite of the measured metocean parameters is generated from the quality control of the data. This quality-controlled data is visualized on DEEP as a time series, as well as comparisons with the basis of design data for the facility in terms of several statistical charts that form the metocean and structural dashboards. Some key insights and findings from these comparisons are presented.","PeriodicalId":23502,"journal":{"name":"Volume 1: Offshore Technology","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generating a Digital Twin of the Glen Lyon FPSO\",\"authors\":\"Jonathan Bailey, R. Bamford, Suvabrata Das, Soma S. Maroju, R. J. Barker\",\"doi\":\"10.1115/omae2022-80547\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n A Digital Twin has been developed for the Glen Lyon FPSO to maintain vessel integrity and ensure operation within the allowable design limits. At the core of this Digital Twin are two components: the Integrated Marine Monitoring System (IMMS) installed on the FPSO, and BMT DEEP, a cloud-based platform that stores, manages, integrates, post-processes and displays the vast data sets collected by the IMMS as well as other data sources. This paper focuses on harnessing the benefits of Digital Twin Technology, by bringing in data from all sources and enabling to synthesize and monitor the FPSO in near real-time from any remote location. This Digital Twin is designed to allow rapid query of the data by filtering with any time window in terms of hour, day, month, quarter, and year of data collection for the life of the asset.\\n Several sensors feed data to the Glen Lyon IMMS. The sensors include FPSO motion, stress response monitoring, and metocean monitoring. In addition to the FPSO based measurements, metocean data is also available from Met Office weather buoy K7, and wind measurements from the nearby Clair platform. A composite of the measured metocean parameters is generated from the quality control of the data. This quality-controlled data is visualized on DEEP as a time series, as well as comparisons with the basis of design data for the facility in terms of several statistical charts that form the metocean and structural dashboards. Some key insights and findings from these comparisons are presented.\",\"PeriodicalId\":23502,\"journal\":{\"name\":\"Volume 1: Offshore Technology\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 1: Offshore Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/omae2022-80547\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 1: Offshore Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/omae2022-80547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Digital Twin has been developed for the Glen Lyon FPSO to maintain vessel integrity and ensure operation within the allowable design limits. At the core of this Digital Twin are two components: the Integrated Marine Monitoring System (IMMS) installed on the FPSO, and BMT DEEP, a cloud-based platform that stores, manages, integrates, post-processes and displays the vast data sets collected by the IMMS as well as other data sources. This paper focuses on harnessing the benefits of Digital Twin Technology, by bringing in data from all sources and enabling to synthesize and monitor the FPSO in near real-time from any remote location. This Digital Twin is designed to allow rapid query of the data by filtering with any time window in terms of hour, day, month, quarter, and year of data collection for the life of the asset.
Several sensors feed data to the Glen Lyon IMMS. The sensors include FPSO motion, stress response monitoring, and metocean monitoring. In addition to the FPSO based measurements, metocean data is also available from Met Office weather buoy K7, and wind measurements from the nearby Clair platform. A composite of the measured metocean parameters is generated from the quality control of the data. This quality-controlled data is visualized on DEEP as a time series, as well as comparisons with the basis of design data for the facility in terms of several statistical charts that form the metocean and structural dashboards. Some key insights and findings from these comparisons are presented.