Deep reinforcement learning for cost-optimal condition-based maintenance policy of offshore wind turbine components
暂无分享,去创建一个
Yan Liu | Wei Li | Tian-yun Li | Jianda Cheng
[1] A. Kolios,et al. Self-adaptive optimized maintenance of offshore wind turbines by intelligent Petri nets , 2022, Reliab. Eng. Syst. Saf..
[2] Yan Liu,et al. Optimum condition-based maintenance policy with dynamic inspections based on reinforcement learning , 2022, Ocean Engineering.
[3] David Y. Yang. Deep Reinforcement Learning–Enabled Bridge Management Considering Asset and Network Risks , 2022, Journal of Infrastructure Systems.
[4] G. Lanza,et al. Opportunistic maintenance scheduling with deep reinforcement learning , 2022, Journal of Manufacturing Systems.
[5] A. Du,et al. Parameterized deep reinforcement learning-enabled maintenance decision-support and life-cycle risk assessment for highway bridge portfolios , 2022, Structural Safety.
[6] Ning Zhang,et al. Maintenance policy optimization for multi-component systems considering dynamic importance of components , 2022, Reliab. Eng. Syst. Saf..
[7] R. Mohammadi,et al. A deep reinforcement learning approach for rail renewal and maintenance planning , 2022, Reliab. Eng. Syst. Saf..
[8] Dusit Niyato,et al. Deep-Reinforcement-Learning-Based Predictive Maintenance Model for Effective Resource Management in Industrial IoT , 2022, IEEE Internet of Things Journal.
[9] S. Chou,et al. Developing an Exhaustive Optimal Maintenance Schedule for Offshore Wind Turbines Based on Risk-Assessment, Technical Factors and Cost-Effective Evaluation , 2022, SSRN Electronic Journal.
[10] E. Zio,et al. Optimization of the Operation and Maintenance of Renewable Energy Systems by Deep Reinforcement Learning , 2021, SSRN Electronic Journal.
[11] Dan M. Frangopol,et al. A Decision-Making Framework for Load Rating Planning of Aging Bridges Using Deep Reinforcement Learning , 2021, J. Comput. Civ. Eng..
[12] Tianyang Zhao,et al. Deep Reinforcement Learning Based Preventive Maintenance for Wind Turbines , 2021, 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2).
[13] E. Zio,et al. Deep Reinforcement Learning Based on Proximal Policy Optimization for the Maintenance of a Wind Farm with Multiple Crews , 2021, Energies.
[14] Dan M. Frangopol,et al. Optimal load rating-based inspection planning of corroded steel girders using Markov decision process , 2021 .
[15] Zhengru Ren,et al. Offshore wind turbine operations and maintenance: A state-of-the-art review , 2021, Renewable and Sustainable Energy Reviews.
[16] Yifan Zhou,et al. Comparison of three preventive maintenance warranty policies for products deteriorating with age and a time-varying covariate , 2021, Reliab. Eng. Syst. Saf..
[17] C. Dao,et al. Integrated condition‐based maintenance modelling and optimisation for offshore wind turbines , 2021, Wind Energy.
[18] Rui Zheng,et al. Condition-based maintenance with dynamic thresholds for a system using the proportional hazards model , 2020, Reliab. Eng. Syst. Saf..
[19] Wujun Si,et al. Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks , 2020, Reliab. Eng. Syst. Saf..
[20] Carlos Guedes Soares,et al. Risk-based maintenance planning of offshore wind turbine farms , 2020, Reliab. Eng. Syst. Saf..
[21] Jichuan Kang,et al. Condition-Based Maintenance for Offshore Wind Turbines Based on Support Vector Machine , 2020, Energies.
[22] Linyi Yao,et al. Deep reinforcement learning for long‐term pavement maintenance planning , 2020, Comput. Aided Civ. Infrastructure Eng..
[23] Hui Li,et al. Optimal policy for structure maintenance: A deep reinforcement learning framework , 2020 .
[24] C. Guedes Soares,et al. Risk-based life-cycle assessment of offshore wind turbine support structures accounting for economic constraints , 2019, Structural Safety.
[25] Qing Li,et al. Integrated optimization of offshore wind farm layout design and turbine opportunistic condition-based maintenance , 2018, Comput. Ind. Eng..
[26] Liping Sun,et al. Condition based maintenance optimization for offshore wind turbine considering opportunities based on neural network approach , 2018 .
[27] Torgeir Moan,et al. Life cycle structural integrity management of offshore structures , 2018 .
[28] Shuo-Yan Chou,et al. Maintenance strategy selection for improving cost-effectiveness of offshore wind systems , 2018 .
[29] Torgeir Moan,et al. Probabilistic methods for planning of inspection for fatigue cracks in offshore structures , 2016 .
[30] Xin-gang Zhao,et al. Focus on the development of offshore wind power in China: Has the golden period come? , 2015 .
[31] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[32] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[33] Konstantinos Papakonstantinou,et al. Optimum inspection and maintenance policies for corroded structures using partially observable Markov decision processes and stochastic, physically based models , 2014 .
[34] J. Cidrás,et al. Review of power curve modelling for wind turbines , 2013 .
[35] Dan M. Frangopol,et al. Generalized Probabilistic Framework for Optimum Inspection and Maintenance Planning , 2013 .
[36] Hong-shan Zhao,et al. Optimization maintenance of wind turbines using Markov decision processes , 2010, 2010 International Conference on Power System Technology.
[37] U. Rieder,et al. Markov Decision Processes , 2010 .
[38] Rwg Bucknall,et al. Planned intervention as a maintenance and repair strategy for offshore wind turbines , 2010 .
[39] Mohammed Kishk,et al. Optimisation of Wind Turbine Inspection Intervals , 2008 .
[40] Ronald J. Williams,et al. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning , 2004, Machine Learning.
[41] David McMillan,et al. Operation and Maintenance of Offshore Wind Farms , 2014 .
[42] John Dalsgaard Sørensen,et al. On risk-based operation and maintenance of offshore wind turbine components , 2011, Reliab. Eng. Syst. Saf..