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  • Open Access

    ARTICLE

    Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+ Deep Learning Model

    Wanrun Li1,2,3,*, Wenhai Zhao1, Tongtong Wang1, Yongfeng Du1,2,3

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 553-575, 2024, DOI:10.32604/sdhm.2024.050751 - 19 July 2024

    Abstract The accumulation of defects on wind turbine blade surfaces can lead to irreversible damage, impacting the aerodynamic performance of the blades. To address the challenge of detecting and quantifying surface defects on wind turbine blades, a blade surface defect detection and quantification method based on an improved Deeplabv3+ deep learning model is proposed. Firstly, an improved method for wind turbine blade surface defect detection, utilizing Mobilenetv2 as the backbone feature extraction network, is proposed based on an original Deeplabv3+ deep learning model to address the issue of limited robustness. Secondly, through integrating the concept of… More > Graphic Abstract

    Surface Defect Detection and Evaluation Method of Large Wind Turbine Blades Based on an Improved Deeplabv3+ Deep Learning Model

  • Open Access

    RETRACTION

    Retraction: Optimized Design of Bio-inspired Wind Turbine Blades

    Yuanjun Dai1,4,*, Dong Wang1, Xiongfei Liu2, Weimin Wu3

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1665-1665, 2024, DOI:10.32604/fdmp.2024.053146 - 23 July 2024

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Analysis of Snow Distribution and Displacement in the Bogie Region of a High-Speed Train

    Zhihui Du1, Mengge Yu1,*, Jiali Liu2, Xiulong Yao1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1687-1701, 2024, DOI:10.32604/fdmp.2024.047315 - 23 July 2024

    Abstract Snow interacting with a high-speed train can cause the formation of ice in the train bogie region and affect its safety. In this study, a wind-snow multiphase numerical approach is introduced for high-speed train bogies on the basis of the Euler-Lagrange discrete phase model. A particle-wall impact criterion is implemented to account for the presence of snow particles on the surface. Subsequently, numerical simulations are conducted, considering various snow particle diameter distributions and densities. The research results indicate that when the particle diameter is relatively small, the distribution of snow particles in the bogie cavity More >

  • Open Access

    ARTICLE

    Study on the Relationship between Structural Aspects and Aerodynamic Characteristics of Archimedes Spiral Wind Turbines

    Yuanjun Dai1,2,3,*, Zetao Deng1, Baohua Li2, Lei Zhong1, Jianping Wang1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1517-1537, 2024, DOI:10.32604/fdmp.2024.046828 - 23 July 2024

    Abstract A combined experimental and numerical research study is conducted to investigate the complex relationship between the structure and the aerodynamic performances of an Archimedes spiral wind turbine (ASWT). Two ASWTs are considered, a prototypical version and an improved version. It is shown that the latter achieves the best aerodynamic performance when the spread angles at the three sets of blades are α = 30°, α = 55°, α = 60°, respectively and the blade thickness is 4 mm. For a velocity V = 10 m/s, a tip speed ratio (TSR) = 1.58 and 2, the maximum C values More > Graphic Abstract

    Study on the Relationship between Structural Aspects and Aerodynamic Characteristics of Archimedes Spiral Wind Turbines

  • Open Access

    ARTICLE

    Optimized Design of Bio-Inspired Wind Turbine Blades

    Yuanjun Dai1,4,*, Dong Wang1, Xiongfei Liu2, Weimin Wu3

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1647-1664, 2024, DOI:10.32604/fdmp.2024.046158 - 23 July 2024

    Abstract To enhance the aerodynamic performance of wind turbine blades, this study proposes the adoption of a bionic airfoil inspired by the aerodynamic shape of an eagle. Based on the blade element theory, a non-uniform extraction method of blade elements is employed for the optimization design of the considered wind turbine blades. Moreover, Computational Fluid Dynamics (CFD) is used to determine the aerodynamic performances of the eagle airfoil and a NACA2412 airfoil, thereby demonstrating the superior aerodynamic performance of the former. Finally, a mathematical model for optimizing the design of wind turbine blades is introduced and More >

  • Open Access

    ARTICLE

    Evolutionary Variational YOLOv8 Network for Fault Detection in Wind Turbines

    Hongjiang Wang1, Qingze Shen2,*, Qin Dai1, Yingcai Gao2, Jing Gao2, Tian Zhang3,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 625-642, 2024, DOI:10.32604/cmc.2024.051757 - 18 July 2024

    Abstract Deep learning has emerged in many practical applications, such as image classification, fault diagnosis, and object detection. More recently, convolutional neural networks (CNNs), representative models of deep learning, have been used to solve fault detection. However, the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error. For this reason, an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection. YOLOv8 is a CNN-backed object detection model. Specifically, to reduce… More >

  • Open Access

    ARTICLE

    Impact of Blade-Flapping Vibration on Aerodynamic Characteristics of Wind Turbines under Yaw Conditions

    Shaokun Liu1, Zhiying Gao1,2,*, Rina Su1,2, Mengmeng Yan1, Jianwen Wang1,2

    Energy Engineering, Vol.121, No.8, pp. 2213-2229, 2024, DOI:10.32604/ee.2024.049616 - 19 July 2024

    Abstract Although the aerodynamic loading of wind turbine blades under various conditions has been widely studied, the radial distribution of load along the blade under various yaw conditions and with blade flapping phenomena is poorly understood. This study aims to investigate the effects of second-order flapwise vibration on the mean and fluctuation characteristics of the torque and axial thrust of wind turbines under yaw conditions using computational fluid dynamics (CFD). In the CFD model, the blades are segmented radially to comprehensively analyze the distribution patterns of torque, axial load, and tangential load. The following results are… More >

  • Open Access

    ARTICLE

    Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

    Yirui Li1, Dongliang Xiao1,3,*, Haoyong Chen1, Weijun Cai1, Josue Campos do Prado2

    Energy Engineering, Vol.121, No.8, pp. 2093-2127, 2024, DOI:10.32604/ee.2024.049232 - 19 July 2024

    Abstract Currently, both regulated and deregulated power trading exist in China’s power system, which has caused imbalanced funds in the electricity market. In this paper, a simulation analysis of the electricity market with wind energy resources is conducted, and the calculation methods of unbalanced funds are investigated systematically. In detail, the calculation formulas of unbalanced funds are illustrated based on their definition, and a two-track electricity market clearing model is established. Firstly, the concept of the dual-track system is explained, and the specific calculation formulas of various types of unbalanced funds are provided. Next, considering the More >

  • Open Access

    ARTICLE

    Ladder Time Stepwise Inertia Coordinated Control Method of Multiple Wind Farms to Suppress System Frequency Secondary Drop

    He Li1, Xianchao Liu2,*, Jidong Li1, Yuchen Qiu2

    Energy Engineering, Vol.121, No.8, pp. 2293-2311, 2024, DOI:10.32604/ee.2024.048752 - 19 July 2024

    Abstract When employing stepwise inertial control (SIC), wind power generation can offer significant frequency support to the power system, concurrently mitigating energy shortages and suppressing secondary frequency drop. Nonetheless, further investigation is imperative for implementing stepped inertia control due to variations in frequency regulation capabilities and operational safety among diverse wind farm groups. Consequently, this paper advocates a multi-wind farm ladder timing SIC method designed to alleviate secondary drops in system frequency. Initially, the paper introduces the fundamental principles of stepped inertia control for a doubly-fed induction generator (DFIG) and deduces the relationship between support energy,… More >

  • Open Access

    ARTICLE

    Research on the IL-Bagging-DHKELM Short-Term Wind Power Prediction Algorithm Based on Error AP Clustering Analysis

    Jing Gao*, Mingxuan Ji, Hongjiang Wang, Zhongxiao Du

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5017-5030, 2024, DOI:10.32604/cmc.2024.050158 - 20 June 2024

    Abstract With the continuous advancement of China’s “peak carbon dioxide emissions and Carbon Neutrality” process, the proportion of wind power is increasing. In the current research, aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data, a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine (IL-Bagging-DHKELM) error affinity propagation cluster analysis is proposed. The algorithm effectively combines deep hybrid kernel extreme learning machine (DHKELM) with incremental learning (IL). Firstly, an initial wind power prediction model is trained using the Bagging-DHKELM… More >

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