Materials Science at Beihang: A Special Issue of Materials Lab Dedicated to the 70th Anniversary of Beihang University

Zhao, Li‐Dong; Guo, Hao; Jiang, Chengbao

doi:10.54227/mlab.20220050

Cited by 4 publications

(4 citation statements)

References 178 publications

(264 reference statements)

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“…The independent variable pitch control system is usually co-simulated by FAST and MATLAB software [9]- [10]. The wind speed environment is TurbSim with an average turbulent wind of 16m/s [11], as shown in Figure 4.…”

Section: Simulation Resultsmentioning

confidence: 99%

Independent Pitch Controller based on Fuzzy Adaptive Tuning PI for Load Mitigation of Large Land Wind Turbine

Li,

Du,

et al. 2023

J. Phys.: Conf. Ser.

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With the development of wind power generation units towards the mega-scale, the blade root and tower have large load and vibration problems during the operation of wind turbines. In order to extend the operational life of wind turbines, a PI independent pitch control (IPC) strategy with fuzzy adaptive tuning (FAT) is introduced based on the existing wind turbine model and control strategy to achieve optimal control of wind turbine loads. Simulations are carried out by the FAST software of the US Renewable Energy Laboratory to compare the independent pitch and the cooperative pitch. The results show that IPC reduces the load on the blade roots and improves the quality of the electrical energy.

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Section: Simulation Resultsmentioning

confidence: 99%

Independent Pitch Controller based on Fuzzy Adaptive Tuning PI for Load Mitigation of Large Land Wind Turbine

Li,

Du,

et al. 2023

J. Phys.: Conf. Ser.

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“…In this section, a computationally efficient semi-analytical method is proposed for circulating current loss evaluation. It is based on the open source finite element software FEMM [21] and MATLAB [22] platform to realize the rapid calculation of the circulating currents among the parallel strands [3]. FEMM is a toolbox in MATLAB that solves the electromagnetic field using magnetostatic finite element method.…”

Section: Studied Machine and Fea Modelmentioning

confidence: 99%

A Computationally Efficient Semi-Analytical Method for Circulating Current Loss of High Speed Permanent Magnet Machines

Li,

Fan,

Liu

et al. 2024

IEEE Trans. Energy Convers.

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This paper proposes a computationally efficient (CE) semi-analytical method for winding power loss calculation of high speed permanent magnet machines induced by circulating current. It combines a CE magnetostatic finite element method (FEM) for rapid slot leakage field extraction and an analytical circuit model for circulating current calculation. Time-space transformation based CE FEM is applied for efficient slot leakage field extraction considering the polyphase windings.Besides, a conductor model with an automatic and practical turn splitting strategy is proposed to consider the effect of conductor positions and bundle shapes on the circulating current loss. The results on circulating current waveforms and corresponding losses show that the proposed method has high accuracy and can significantly reduce the simulation time, with an error less than 2% and the simulation time only 1/400 for the studied machine compared with the commercial FEM. Using the proposed method, the influence of some factors, including the turn number, the transposition effect and the bundle shape on the circulating current loss are investigated. Finally, the proposed method is further verified by experimental measurements implemented on two stator specimens.

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“…The gray level correction of the grayscale image is performed using the contrast stretching transform function in order to make the distinction between the target subject shape and the background portion of the image more pronounced and thus ensure the quality of subsequent shape feature extraction. The function can amplify the difference between the gray level of the target subject pixel and the gray level of the background pixel [30], and the transformed image after function processing can visually distinguish the subject part from the background region more intuitively and clearly, emphasizing the target region pixel information. Image smoothing is the application of median filtering to remove noise.…”

Section: B: Image Correction and Smoothingmentioning

confidence: 99%

Image Multi-Feature Fusion for Clothing Style Classification

Zhang,

He,

Song

2023

IEEE Access

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E-commerce platforms are evolving rapidly, and consumers have adapted to shop online more effectively by utilizing product images on shopping websites. In the case of apparel, consumers pay attention not only to the information about practical attributes but also to the information about style attributes. In this study, to specifically analyze the respective style recognition capabilities of the depth feature extractor for studying different clothing styles, an empirical investigation was conducted on four commonly utilized networks: AlexNet, InceptionV3, ResNet50, and VGG16. To complete style classification, we propose the IMF model, which integrates shallow neural networks subsequent to feature engineering to incorporate the benefits of basic features and depth features. This process reinforces the basic features through secondary extraction and merges them with depth features to generate style features, ultimately accomplishing the objective of clothing style classification. Furthermore, a DeepCluster based unsupervised learning approach is used in this study as a comparison. Its classification outcomes are compared with those of the IMF model to authenticate the efficacy of IMF model in this study.

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Materials Science at Beihang: A Special Issue of Materials Lab Dedicated to the 70th Anniversary of Beihang University

Cited by 4 publications

References 178 publications

Independent Pitch Controller based on Fuzzy Adaptive Tuning PI for Load Mitigation of Large Land Wind Turbine

Independent Pitch Controller based on Fuzzy Adaptive Tuning PI for Load Mitigation of Large Land Wind Turbine

A Computationally Efficient Semi-Analytical Method for Circulating Current Loss of High Speed Permanent Magnet Machines

Image Multi-Feature Fusion for Clothing Style Classification

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