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Optimization Design of Axial Flux Permanent Magnet Synchronous Motor Based on Multi-Objective Genetic Algorithm

Progress in Electromagnetics research C 2025年 155卷 85-93页

作者： Liu, Huijun College of Mechanical and Electrical Engineering Zhumadian Vocational and Technical College Zhumadian463000 China Henan Intelligent Sorting Technology Application Engineering Research Center Zhumadian Vocational and Technical College Zhumadian463000 China

As a new type of motor, axial flux permanent magnet synchronous motor has the advantages of compact structure and high power density. It shows good application prospects in new energy vehicles, unmanned aerial vehicles, and other fields. However, axial flux permanent magnet synchronous motor needs to consider the balance of multiple objectives during the design process, which makes its optimal design a complex multi-objective optimization problem. Therefore, the study proposes a motor optimization method based on multi-objective genetic algorithm. The method optimizes the rotor and stator parameters of the motor by establishing an analytical model of the motor’s magnetic field and combining it with a multi-objective genetic algorithm. The experimental results indicated that the optimized motor with multi-objective genetic algorithm reached 92% in terms of efficiency, 25% in terms of power density; energy consumption was reduced to 2.5 kWh; failure rate was reduced to 1.5%; and noise level was reduced to 65 dB. In addition, the multi-objective genetic algorithm significantly improved the control stability index, which increased to 98%, indicating a more stable motor response under varying loads. The disturbance rejection capability was enhanced to 99%, demonstrating strong resistance to external noise and parameter fluctuations. Furthermore, the system response frequency reached 100 Hz, reflecting a faster dynamic response to input variations. It is indicated that the optimization method based on multi-objective genetic algorithm can effectively enhance the comprehensive performance of axial flux permanent magnet synchronous motor and significantly improve its competitiveness in high power density and high efficiency applications. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Multiobjective optimization

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A Helmet Detection Algorithm Based on Transformers with Deformable Attention Module

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Chinese Journal of Electronics 2025年第1期34卷 229-241页

作者： Songle Chen Hongbo Sun Yuxin Wu Lei Shang Xiukai Ruan Engineering Research Center of Post Big Data Technology and Application of Jiangsu Province Nanjing University of Posts and Telecommunications State Key Lab for Novel Software Technology Nanjing University Institute of Intelligent Locks Wenzhou University

Wearing a helmet is one of the effective measures to protect workers' safety. To address the challenges of severe occlusion, multi-scale, and small target issues in helmet detection, this paper proposes a helmet detection algorithm based on deformable attention transformers. The main contributions of this paper are as follows. A compact end-to-end network architecture for safety helmet detection based on transformers is proposed. It cancels the computationally intensive transformer encoder module in the existing detection transformer(DETR) and uses the transformer decoder module directly on the output of feature extraction for query decoding, which effectively improves the efficiency of helmet detection. A novel feature extraction network named Swin transformer with deformable attention module(DSwin transformer) is proposed. By sparse cross-window attention, it enhances the contextual awareness of multi-scale features extracted by Swin transformer, and keeps high computational efficiency simultaneously. The proposed method generates the query reference points and query embeddings based on the joint prediction probabilities, and selects an appropriate number of decoding feature maps and sparse sampling points for query decoding, which further enhance the inference capability and processing speed. On the benchmark safety-helmet-wearing-dataset(SHWD), the proposed method achieves the average detection accuracy mAP@0.5 of 95.4% with 133.35G floating-point operations per second(FLOPs) and 20 frames per second(FPS), the state-of-the-art method for safety helmet detection.

关键词： Head Accuracy Network architecture Benchmark testing Transformers Feature extraction Safety Decoding Computational efficiency Detection algorithms

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Self-assembled Fe_(3)O_(4)nanoparticles on V2C MXene for enhanced supercapacitor and microwave absorption applications

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Journal of Advanced Ceramics 2025年第3期14卷 183-196页

作者： Qixun Xia Ranlu Miao Wen Guo Min Xia Libo Wang Qianku Hu Aiguo Zhou School of Materials Science and Engineering Henan Polytechnic UniversityJiaozuo 454003China Henan Province Expressway Efficient Energy Storage Technology and Application Engineering Research Center Zhengzhou 450121China Department of Macromolecular Science Fudan UniversityShanghai 200438China Henan Radio Requlation Information System Backup Center Zhengzhou 450008China

Rapid advancements in modern electronic devices necessitate the development of materials that can simultaneously provide efficient energy storage and effective microwave ***,a novel composite material was prepared via the self-assembly of Fe_(3)O_(4)nanoparticles on the surface of V2C *** composite exhibited characteristics suitable for supercapacitor and electromagnetic absorption applications,highlighting the synergistic relationship between energy storage and electromagnetic wave absorption *** electrochemical tests revealed that the specific capacity of the V_(2)C MXene/Fe_(3)O_(4)composite(42.67 mAh·g^(−1))considerably improved compared with those of the raw *** prepared V2C MXene/Fe_(3)O_(4)//V_(2)C MXene/Fe_(3)O_(4)symmetric supercapacitor(SSC)demonstrated an energy density of 44.8 Wh·L^(−1),a power density of 959.4 W·L−1,and a capacity retention of 80.14%after 8000 ***,the V2C MXene/Fe_(3)O_(4)composite exhibited an optimal reflection loss(RL)of−42.4 dB in the Ku band,with an effective absorption bandwidth of 1.9 GHz(14.6–16.5 GHz).This composite material has broad application potential in modern electronic devices owing to its high energy storage capacity and effective electromagnetic wave *** dual functionality improves device performance and offers a compact solution for energy storage and effective microwave absorption.

关键词： MXenes Fe_(3)O_(4) two-dimensional(2D)materials supercapacitors microwave absorption

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Multi-Motor Synchronous Control Strategy Based on Fuzzy Internal Model PID and Virtual Spindle Synchronous Control

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Progress in Electromagnetics research C 2025年 152卷 187-195页

作者： Yan, Wei Li, Shasha College of Mechanical and Electronic Engineering Huanghe Jiaotong University Jiaozuo454950 China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo454950 China

To achieve high-precision synchronous control of multiple motors, this study utilizes a permanent magnet synchronous motor as a case study. It adopts a fuzzy internal model proportional-integral-derivative algorithm with integral separation for single-motor control. On this basis, the virtual spindle synchronization strategy of multi-motor synchronous control and fuzzy control algorithm are further introduced to adjust the feedback torque compensation coefficient dynamically, optimizing the virtual spindle synchronization strategy. The results showed that in single-motor control, the dual closed-loop fuzzy proportional-integral control algorithm achieved a torque fluctuation error of 4 N · m when the load torque changed significantly. The fuzzy internal model proportional-integral-derivative control algorithm with integral separation had a relatively smooth adjustment process, and the maximum torque fluctuation did not exceed 1 N · m. In multi-motor synchronous control, the improved virtual spindle synchronous control strategy had a synchronization error of only 14.2 r/min between motor 1 and motor 2, as well as between motor 1 and motor 3. The single-motor and multi-motor synchronous control strategies used in the study have high control accuracy and response efficiency, which is conducive to improving the synchronization accuracy and coordination between motors. The improved strategy provides a reliable control scheme for industrial automation systems. © 2025, Electromagnetics Academy. All rights reserved.

关键词： Permanent magnets

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Graph Neural Network-Based User Preference Model for Social Network Access Control

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第16期49卷 21-36页

作者： Zhang, Yuan Xuchang Vocational Technical College Xuchang461000 China Henan Province Data Intelligence and Security Application Engineering Technology Research Center Xuchang461000 China

The popularity and deepening of social networks have increased the risk of personal information leakage for users. To enhance the security of social networks, this study constructed an access control model based on the preferences of social network users. This model utilizes graph neural networks to generate access control strategies based on user preferences, and introduces a multi-layer attention mechanism to optimize the graph neural network. To better capture user preference information, the study sets the learning rate to 0.0001. The experimental results demonstrated that in the Twitter dataset, the accuracy of the proposed model reached 95.7% and the F1 score reached 96.2%, which were significantly higher than those of other models. These results indicated that the model could more accurately classify access control in social networks and reduce false positives. The area under the receiver operation characteristic curve of the proposed model was 0.982, which was higher than other models. The decision time was 13.77 seconds, significantly lower than other models. This indicated that the model could more effectively distinguish different types of user access requests and provide more reliable guarantees for secure access to social networks. The user's preferred social network access control model based on graph neural networks has superior performance, effectively ensuring the information security of social network users and laying the foundation for further development of access control technology. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Access control models

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A Method for Fast Feature Selection Utilizing Cross-Similarity within the Context of Fuzzy Relations

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Computers, Materials & Continua 2025年第4期83卷 1195-1218页

作者： Wenchang Yu Xiaoqin Ma Zheqing Zhang Qinli Zhang School of Big Data and Artificial Intelligence Chizhou UniversityChizhou247000China Anhui Education Big Data Intelligent Perception and Application Engineering Research Center Anhui Provincial Joint Construction Key Laboratory of Intelligent Education Equipment and TechnologyChizhou247000China

Feature selection methods rooted in rough sets confront two notable limitations:their high computa-tional complexity and sensitivity to noise,rendering them impractical for managing large-scale and noisy *** primary issue stems from these methods’undue reliance on all *** overcome these challenges,we introduce the concept of cross-similarity grounded in a robust fuzzy relation and design a rapid and robust feature selection ***,we construct a robust fuzzy relation by introducing a truncation ***,based on this fuzzy relation,we propose the concept of cross-similarity,which emphasizes the sample-to-sample similarity relations that uniquely determine feature importance,rather than considering all such relations *** studying the manifestations and properties of cross-similarity across different fuzzy granularities,we propose a forward greedy feature selection algorithm that leverages cross-similarity as the foundation for information *** algorithm significantly reduces the time complexity from O(m2n2)to O(mn2).Experimental findings reveal that the average runtime of five state-of-the-art comparison algorithms is roughly 3.7 times longer than our algorithm,while our algorithm achieves an average accuracy that surpasses those of the five comparison algorithms by approximately 3.52%.This underscores the effectiveness of our *** paper paves the way for applying feature selection algorithms grounded in fuzzy rough sets to large-scale gene datasets.

关键词： Fuzzy rough sets feature selection cross-similarity fuzzy relations

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Influence of Undercooling on the Solidification Behaviour and Microstructure of Non-equilibrium Solidification of Cu-based Alloys

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Journal of Wuhan University of technology(Materials Science) 2025年第2期40卷 610-618页

作者： LI Hejun AN Hongen Willey Liew Yun Hsien Ismal Saad Bih Lii Chuab Nancy Julius Siambun CAO Shichao WANG Hongfu YAO Wei College of Mechanical and Electronic Engineering Huanghe Jiaotong UniversityJiaozuo 454950China Henan Engineering Technology Research Center on Intelligent Manufacturing Technology and Equipment Jiaozuo 454950China Faculty of Engineering University Malaysia SabahKota Kinabalu 88400Malaysia School of Mechanical Engineering North University of ChinaTaiyuan 030051China Jiaozuo Robot Engineering Technology Center Jiaozuo 454950China

The evolution of the microstructure and morphology of Cu55Ni45 and Cu60Ni40 alloys under varying degrees of undercooling was investigated through molten glass purification and cyclic superheating *** increasing the Cu content,the effect of Cu on the evolution of the microstructure and morphology of the Cu-Ni alloy during undercooling was *** mechanism of grain refinement at different degrees of undercooling and the effect of Cu content on its solidification behaviour were *** solidification behaviour of Cu55Ni45 and Cu60Ni40 alloys was investigated using infrared thermometry and high-speed *** results indicate that both Cu55Ni45 and Cu60Ni40 alloy melts undergo only one recalescence during rapid *** degree of recalescence increases approximately linearly with increasing *** solidification front of the alloy melts undergoes a transition process from a small-angle plane to a sharp front and then to a smooth ***,the growth of the subcooled melt is constrained to a narrow range,facilitating the formation of a coarse dendritic crystal morphology in the Cu-Ni *** large undercooling,the stress breakdown of the directionally growing dendrites is primarily caused by thermal *** strain remaining in the dendritic fragments provides the driving force for recrystallisation of the tissue to occur,which in turn refines the tissue.

关键词： undercooling microstructure grain refinement solidification rate

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Masked hybrid attention with Laplacian query fusion and tripartite sequence matching for medical image segmentation

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Neural Computing and applications 2025年第8期37卷 5891-5911页

作者： Ekong, Favour Yu, Yongbin Patamia, Rutherford Agbeshi Sarpong, Kwabena Ukwuoma, Chiagoziem C. Wang, Xiangxiang Ukot, Akpanika Robert Cai, Jingye School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan Chengdu610059 China Sichuan Engineering Technology Research Center for Industrial Internet Intelligent Monitoring and Application Chengdu University of Technology Sichuan Chengdu610059 China

Medical image segmentation is pivotal in computer-aided diagnosis systems, demanding high precision and contextual understanding. Vision Transformer-based approaches have gained much attention recently due to their excellent performance and ability to capture long-range dependencies in medical images. However, research shows they suffer from inadequate multi-scale feature integration, poor object localization, and inconsistent mask predictions, leading to sub-optimal segmentation performance. This paper addresses these challenges by redefining semantic medical image segmentation through learnable object queries within an enhanced transformer framework with a masked hybrid attention querying mechanism, optimizing multi-scale feature fusion, object localization, and instance-specific segmentation. First, this study presents a novel transformer-based masked hybrid attention mechanism using Laplacian query fusion on learnable query features and incorporating a novel tripartite sequence matching technique as part of the enhanced decoder block to improve the consistency of mask predictions and optimize decoder queries. The designed hybrid multi-head self- and cross-attention mechanisms aim to selectively integrate multi-scale features, ensuring optimal feature combinations for precise segmentation. Secondly, multiple class tokens are incorporated to improve object localization and capture class-specific characteristics within the transformer framework, leveraging the transformer decoders’ ability to learn distinct instance representations. Experimental results and extensive ablation studies demonstrate the effectiveness of the proposed approach on three publicly available datasets, obtaining better segmentation results compared to various state-of-the-art approaches using various evaluation metrics. Specifically, the proposed model achieves a Dice Score of 95.25%, 92.75%, and 85.25% on LUNA, ISIC, and DRIVE datasets, respectively. © The Author(s), under exclusive licence

关键词： Laplace transforms

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Prediction of the Seepage Quantity Based on a Random Field Model of Soil Permeability Coefficient

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ce/papers 2025年第2期8卷 496-509页

作者： Wang, Hui Du, Mengke Jin, Mingyan Li, Liqing He, Fangchan Bian, Ke Lan, Yan Henan River Diversion Project Co. Ltd Zhengzhou450008 China School of Civil Engineering and Architecture Henan University of Technology Zhengzhou450001 China Henan Province Water Conservancy Technology Application Center Zhengzhou450003 China Yellow River Institute of Hydraulic Research Zhengzhou450004 China

Natural soils exhibit spatial variability, and predicting seepage quantity considering a random field model of soil permeability coefficient is significant for water conveyance channel. Base on the Yangtze River-Huaihe River Interbasin Water Transfer Project, employing finite element numerical simulation method to construct a three-dimensional stochastic field model using normal distribution. Four different stochastic field distribution parameters are researched to predict seepage flow. The main conclusions are as follows: ①Compared to deterministic seepage fields, the average seepage quantity increases about 30% for considering the random distribution of permeability coefficients. ②The selection of parameters in the stochastic field model significantly affects statistical values of seepage flow, with the variance of the fluctuation function having the greatest impact on both the mean and dispersion of seepage flow. Autocorrelation coefficient and fluctuation scale have a significant influence on the dispersion of seepage flow, but little effect on the mean;③Hydraulic conditions of the slope are crucial factors controlling seepage, and they exhibit clear coupling with the stochastic effects of permeability coefficients. Therefore, in practical engineering, it is necessary to select appropriate hydraulic conditions and stochastic field parameters based on on-site hydraulic conditions and statistical distribution characteristics of parameters to accurately predict seepage quantity. © 2025 Ernst & Sohn GmbH.

关键词： Normal distribution

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Cycle-GAN-based holographic reconstruction for 3D particle fields 4

Cycle-GAN-based holographic reconstruction for 3D particle f...

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4th International Computational Imaging Conference, CITA 2024

作者： Deng, Dingnan Fu, Xin Wang, Chengguo Zhang, Shuiyin School of Physics and Electronic Engineering Jiaying University Meizhou514015 China Meizhou Intelligent Photoelectric Detection Application Engineering Technology Research Center Meizhou514015 China

ISBN: (纸本)9781510688834

A self-supervised model based on CycleGAN is proposed to reconstruct the 3D particle fields from the unpaired data sets. The ground truth can be obtained by converting the 3D information of the particle field into a 2D grayscale image. The hologram of particles is the input of network model. A training model based on CycleGAN is designed. The unpaired data not only alleviates the pressure of data demand but also simplifies the design of the holographic device. Thus, the model training can proceed with incomplete data. With the cycle consistency of the mode, the particle characterization is more accurate. In order to assess the viability of the proposed scheme, the structural similarity (SSIM) between the reconstructed result and the ground truth is calculated. © 2025 SPIE.

关键词： 3D reconstruction

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