标题
Digital tools for floating offshore wind turbines (FOWT): A state of the art
作者
关键词
-
出版物
Energy Reports
Volume 8, Issue -, Pages 1207-1228
出版商
Elsevier BV
发表日期
2021-12-30
DOI
10.1016/j.egyr.2021.12.034
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Deep Learning Method for Fault Detection of Wind Turbine Converter
- (2021) Cheng Xiao et al. Applied Sciences-Basel
- Model of Bio-Colonisation on Mooring Lines: Updating Strategy Based on a Static Qualifying Sea State for Floating Wind Turbines
- (2020) Benjamin Decurey et al. Journal of Marine Science and Engineering
- Mooring-Failure Monitoring of Submerged Floating Tunnel Using Deep Neural Network
- (2020) Do-Soo Kwon et al. Applied Sciences-Basel
- Reliability analysis of a floating offshore wind turbine using Bayesian Networks
- (2020) He Li et al. OCEAN ENGINEERING
- Digital Twin in Industry: State-of-the-Art
- (2019) Fei Tao et al. IEEE Transactions on Industrial Informatics
- Integrated GNSS/IMU hub motion estimator for offshore wind turbine blade installation
- (2019) Zhengru Ren et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Structural health monitoring of towers and blades for floating offshore wind turbines using operational modal analysis and modal properties with numerical-sensor signals
- (2019) Hyoung-Chul Kim et al. OCEAN ENGINEERING
- Methodology for modeling and service life monitoring of mooring lines of floating wind turbines
- (2019) Hong-Duc Pham et al. OCEAN ENGINEERING
- Maintenance management based on Machine Learning and nonlinear features in wind turbines
- (2019) Alfredo Arcos Jiménez et al. RENEWABLE ENERGY
- Human exposure to motion during maintenance on floating offshore wind turbines
- (2018) Matti Scheu et al. OCEAN ENGINEERING
- Deep Learning for fault detection in wind turbines
- (2018) Georg Helbing et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Fault Tree Analysis of floating offshore wind turbines
- (2018) Jichuan Kang et al. RENEWABLE ENERGY
- Machine learning methods for wind turbine condition monitoring: A review
- (2018) Adrian Stetco et al. RENEWABLE ENERGY
- Risk assessment of floating offshore wind turbine based on correlation-FMEA
- (2017) Jichuan Kang et al. OCEAN ENGINEERING
- A New Fault Location Approach for Acoustic Emission Techniques in Wind Turbines
- (2016) Carlos Gómez Muñoz et al. Energies
- Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm
- (2016) Maria Martinez-Luengo et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Damage detection in wind turbine blades by using operational modal analysis
- (2016) Emilio Di Lorenzo et al. STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
- Numerical error estimation of conventional anemometry mounted on offshore floating met-masts
- (2016) Raúl Guanche et al. WIND ENERGY
- A survey of health monitoring systems for wind turbines
- (2015) Mathew L. Wymore et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Structural integrity monitoring of onshore wind turbine concrete foundations
- (2015) Magnus Currie et al. RENEWABLE ENERGY
- Failure rate, repair time and unscheduled O&M cost analysis of offshore wind turbines
- (2015) James Carroll et al. WIND ENERGY
- Wind turbine condition monitoring: technical and commercial challenges
- (2012) Wenxian Yang et al. WIND ENERGY
- Feasibility of monitoring large wind turbines using photogrammetry
- (2010) Muammer Ozbek et al. ENERGY
- The economics of wind energy
- (2008) María Isabel Blanco RENEWABLE & SUSTAINABLE ENERGY REVIEWS
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started