{"title":"基于数字孪生虚拟传感器的海上风机传动系统疲劳损伤在线监测","authors":"F. C. Mehlan, A. Nejad, Zhenghua Gao","doi":"10.1115/1.4055551","DOIUrl":null,"url":null,"abstract":"\n In this article a virtual sensor for online load monitoring and subsequent remaining useful life (RUL) assessment of wind turbine gearbox bearings is presented. Utilizing a Digital Twin framework the virtual sensor combines data from readily available sensors of the condition monitoring (CMS) and supervisory control and data acquisition (SCADA) system with a physics-based gearbox model. Different state estimation methods including Kalman Filter, Least Square estimator and a quasi-static approach are employed for load estimation. For RUL assessment the accumulated fatigue damage is calculated with the Palmgren-Miner model. A case study using simulation measurements from a high-fidelity gearbox model is conducted to evaluate the proposed method. Estimated loads at the considered IMS and HSS bearings show moderate to high correlation (R = 0.50-0.96) to measurements, as lower frequency internal dynamics are not fully captured. The estimated fatigue damage differs by 5-15 % from measurements.","PeriodicalId":50106,"journal":{"name":"Journal of Offshore Mechanics and Arctic Engineering-Transactions of the Asme","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Digital twin based virtual sensor for online fatigue damage monitoring in offshore wind turbine drivetrains\",\"authors\":\"F. C. Mehlan, A. Nejad, Zhenghua Gao\",\"doi\":\"10.1115/1.4055551\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n In this article a virtual sensor for online load monitoring and subsequent remaining useful life (RUL) assessment of wind turbine gearbox bearings is presented. Utilizing a Digital Twin framework the virtual sensor combines data from readily available sensors of the condition monitoring (CMS) and supervisory control and data acquisition (SCADA) system with a physics-based gearbox model. Different state estimation methods including Kalman Filter, Least Square estimator and a quasi-static approach are employed for load estimation. For RUL assessment the accumulated fatigue damage is calculated with the Palmgren-Miner model. A case study using simulation measurements from a high-fidelity gearbox model is conducted to evaluate the proposed method. Estimated loads at the considered IMS and HSS bearings show moderate to high correlation (R = 0.50-0.96) to measurements, as lower frequency internal dynamics are not fully captured. The estimated fatigue damage differs by 5-15 % from measurements.\",\"PeriodicalId\":50106,\"journal\":{\"name\":\"Journal of Offshore Mechanics and Arctic Engineering-Transactions of the Asme\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Offshore Mechanics and Arctic Engineering-Transactions of the Asme\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4055551\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Offshore Mechanics and Arctic Engineering-Transactions of the Asme","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1115/1.4055551","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Digital twin based virtual sensor for online fatigue damage monitoring in offshore wind turbine drivetrains
In this article a virtual sensor for online load monitoring and subsequent remaining useful life (RUL) assessment of wind turbine gearbox bearings is presented. Utilizing a Digital Twin framework the virtual sensor combines data from readily available sensors of the condition monitoring (CMS) and supervisory control and data acquisition (SCADA) system with a physics-based gearbox model. Different state estimation methods including Kalman Filter, Least Square estimator and a quasi-static approach are employed for load estimation. For RUL assessment the accumulated fatigue damage is calculated with the Palmgren-Miner model. A case study using simulation measurements from a high-fidelity gearbox model is conducted to evaluate the proposed method. Estimated loads at the considered IMS and HSS bearings show moderate to high correlation (R = 0.50-0.96) to measurements, as lower frequency internal dynamics are not fully captured. The estimated fatigue damage differs by 5-15 % from measurements.
期刊介绍:
The Journal of Offshore Mechanics and Arctic Engineering is an international resource for original peer-reviewed research that advances the state of knowledge on all aspects of analysis, design, and technology development in ocean, offshore, arctic, and related fields. Its main goals are to provide a forum for timely and in-depth exchanges of scientific and technical information among researchers and engineers. It emphasizes fundamental research and development studies as well as review articles that offer either retrospective perspectives on well-established topics or exposures to innovative or novel developments. Case histories are not encouraged. The journal also documents significant developments in related fields and major accomplishments of renowned scientists by programming themed issues to record such events.
Scope: Offshore Mechanics, Drilling Technology, Fixed and Floating Production Systems; Ocean Engineering, Hydrodynamics, and Ship Motions; Ocean Climate Statistics, Storms, Extremes, and Hurricanes; Structural Mechanics; Safety, Reliability, Risk Assessment, and Uncertainty Quantification; Riser Mechanics, Cable and Mooring Dynamics, Pipeline and Subsea Technology; Materials Engineering, Fatigue, Fracture, Welding Technology, Non-destructive Testing, Inspection Technologies, Corrosion Protection and Control; Fluid-structure Interaction, Computational Fluid Dynamics, Flow and Vortex-Induced Vibrations; Marine and Offshore Geotechnics, Soil Mechanics, Soil-pipeline Interaction; Ocean Renewable Energy; Ocean Space Utilization and Aquaculture Engineering; Petroleum Technology; Polar and Arctic Science and Technology, Ice Mechanics, Arctic Drilling and Exploration, Arctic Structures, Ice-structure and Ship Interaction, Permafrost Engineering, Arctic and Thermal Design.