Blar i NTNU Open på forfatter "Liu, Xiufeng"
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Analysis and Visualization of Urban Emission Measurements in Smart Cities
Ahlers, Dirk; Kraemer, Frank Alexander; Bråten, Anders Eivind; Liu, Xiufeng; Anthonisen, Fredrik Valde; Driscoll, Patrick Arthur; Krogstie, John (Chapter, 2018)Cities worldwide aim to reduce their greenhouse gas emissions and improve air quality for their citizens. Therefore, there is a need to implement smart city approaches to monitor, model, and understand local emissions to ... -
Automated infection risks assessments (AIRa) for decision-making using a blockchain-based alert system: A case study in a representative building
Wan, Paul Kengfai; Huang, Lizhen; Lai, Zhichen; Liu, Xiufeng; Nowostawski, Mariusz; Holtskog, Halvor; Liu, Yongping (Peer reviewed; Journal article, 2022)Indoor air quality (IAQ) is an important parameter in protecting the occupants of an indoor environment. Previous studies have shown that an indoor environment with poor ventilation increases airborne virus transmission. ... -
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 ... -
A Contextual Anomaly Detection Framework for Energy Smart Meter Data
Liu, Xiufeng; lai, zhichen; wang, xin; Huang, Lizhen; Nielsen, Per Sieverts (Chapter, 2009)Monitoring abnormal energy consumption is helpful for demand-side management. This paper proposes a framework for contextual anomaly detection (CAD) for residential energy consumption. This framework uses a sliding window ... -
Multiscale Wavelet-Driven Graph Convolutional Network for Blade Icing Detection of Wind Turbines
Lai, Zhichen; Cheng, Xu; Liu, Xiufeng; Huang, Lizhen; Liu, Yongping (Peer reviewed; Journal article, 2022)Blade icing detection is critical to maintaining the health of wind turbines, especially in cold climates. Rapid and accurate icing detection allows proper control of wind turbines, including shutting down and clearing the ... -
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 ...