Browsing NTNU Open by Author "Shi, Fan"
Now showing items 1-9 of 9
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A Blockchain-Empowered Cluster-based Federated Learning Model for Blade Icing Estimation on IoT-enabled Wind Turbine
Cheng, Xu; Tian, Weiwei; Shi, Fan; Zhao, Meng; Chen, Shengyong; Wang, Hao (Peer reviewed; Journal article, 2022)Wind energy is a fast-growing renewable energy but faces the blade icing. Data-driven methods provide talented solutions for blade icing detection but a considerable amount of data need to be collected to a central server, ... -
A Class-Imbalanced Heterogeneous Federated Learning Model for Detecting Icing on Wind Turbine Blades
Cheng, Xu; Shi, Fan; Liu, Yongping; Zhou, Jiehan; Liu, Xiufeng; Huang, Lizhen (Peer reviewed; Journal article, 2022)Wind farms are typically located at high latitudes, resulting in a high risk of blade icing. Data-driven approaches offer promising solutions for blade icing detection, but they rely on a considerable amount of data. Data ... -
An Enhanced Lightweight Convolutional Neural Network for Ship Detection in Maritime Surveillance System
Yin, Yifan; Cheng, Xu; Shi, Fan; Zhao, Meng; Li, Guoyuan; Chen, Shengyong (Peer reviewed; Journal article, 2022)With the extensive application of artificial intelligence, ship detection from optical satellite remote sensing images using deep learning technology can significantly improve detection accuracy. However, the existing ... -
Fused 3-Stage Image Segmentation for Pleural Effusion Cell Clusters
Ma, Sike; Zhao, Meng; Wang, Hao; Shi, Fan; Sun, Xuguo; Chen, Shengyong; Dai, Hong-Ning (Chapter, 2021)The appearance of tumor cell clusters in pleural effusion is usually a vital sign of cancer metastasis. Segmentation, as an indispensable basis, is of crucial importance for diagnosing, chemical treatment, and prognosis ... -
Gated Convolutional Neural Network for Wind Turbine Blade Icing Detection
Tian, Weiwei; Cheng, Xu; Shi, Fan; Li, Guoyuan; Chen, Shengyong; Zhang, Houxiang (Chapter, 2022)Blade icing detection plays an important role in wind turbine protection and maintenance. Employing well trained deep learning model is a promising method for blade ice detection but needs effective neural networks for ... -
MSS-WISN: Multiscale Multistaining WBCs Instance Segmentation Network
Zhao, Meng; Yang, Hongxia; Shi, Fan; Zhang, Xinpeng; Zhang, Yao; Sun, Xuguo; Wang, Hao (Journal article; Peer reviewed, 2022) -
A Multilevel Convolutional Recurrent Neural Network for Blade Icing Detection of Wind Turbine
Tian, Weiwei; Cheng, Xu; Li, Guoyuan; Shi, Fan; Chen, Shengyong; Zhang, Houxiang (Peer reviewed; Journal article, 2021)Blade icing detection becomes increasingly significant as it can avoid revenue loss and power degradation. Conventional methods are usually limited by additional costs, and model-driven methods heavily depend on prior ... -
Temporal Attention Convolutional Neural Network for Estimation of Icing Probability on Wind Turbine Blades
Cheng, Xu; Shi, Fan; Zhao, Meng; Li, Guoyuan; Zhang, Houxiang; Chen, Shengyong (Peer reviewed; Journal article, 2021)Wind farms are usually located in high-latitude areas, which increases produced energy but creates a high risk of icing. Traditional methods of anti-blade-icing are limited by the extra cost and the potential damages to ... -
Wind turbine blade icing detection: a federated learning approach
Cheng, Xu; Shi, Fan; Liu, Yongping; Liu, Xiufeng; Huang, Lizhen (Peer reviewed; Journal article, 2022)Wind farms are often located at high latitudes, which entails a high risk of icing for wind turbine blades. Traditional anti-icing methods rely primarily on manual observation, the use of special materials, or external ...