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Comparative Analysis of Vibration and Noise of Axial Flux Motor with Different Pole and Slot Combinations

Chinese Journal of electrical engineering 2023年第4期9卷 144-156页

作者： Qixu Chen Zhizhong Chen Guoli Li Dechen Wu Peng Li School of Electrical Engineering and Automation Anhui UniversityHefei 230601China National Engineering Laboratory of Energy-Saving Motor&Control Technology Anhui UniversityHefei 230601China

The electromagnetic vibration noise in axial flux motors was meticulously *** this study,24-slot/10-pole and 12-slot/10-pole axial flux motors were chosen as the subjects of *** spatial characteristics of the axial electromagnetic force were derived analytically and confirmed via two-dimensional Fourier *** finite-element method was used to simulate the low-order axial modes of both ***,a modal experiment on the stator of a 24-slot/10-pole axial flux motor was conducted to validate the simulation’s *** integrating the electromagnetic and structural models,a comprehensive multi-physical field model was developed to calculate the vibration noise of the axial flux *** precision of this model was subsequently corroborated with noise *** findings from this study aim to offer insights into identifying the sources of vibration noise in axial flux motors.

关键词： Axial electromagnetic force vibration noise axial flux motors modal analysis

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A Short-term PV Power Prediction and Uncertainty Analysis Model Based on CEEMDAN and AHA-BP

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Distributed Generation and Alternative Energy Journal 2024年第4期39卷 875-898页

作者： Zeng, Zhiyuan Li, Tianyou Su, Jun Yang, Yihan Lin, Yajun School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen China

The stochastic and intermittent nature of photovoltaic (PV) generation brings a series of scheduling problems to the power system. An effective prediction of PV power is essential to minimize the impact of uncertainty. Therefore, this paper presents an integrated prediction model with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the artificial hummingbird algorithm (AHA), and the BP neural network (BPNN) for predicting power generation from PV power plants, and a methodology for uncertainty analysis by using the nonparametric kernel density estimation (NPKDE). First, one month of PV power is decomposed into an array of components using CEEMDAN. Then, the weights and thresholds of the BPNN are optimized by using AHA. These components are trained using the BPNN. Finally, the final prediction results are obtained by superimposing the components, and NPKDE is employed to compute the probability density and confidence interval of the prediction error. The proposed prediction method demonstrates superior predictive performance in comparison with other models. Also, the NPKDE approach better describes the accuracy of the probability density distribution. © 2024 River Publishers.

关键词： Prediction models

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Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

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Science China(Technological Sciences) 2023年第6期66卷 1797-1814页

作者： REN GuoRui WANG Wei WAN Jie HONG Feng YANG Ke YU DaRen School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China Xi’an Thermal Power Research Institute Co. Ltd.Xi’an 710054China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Air density plays an important role in assessing wind *** density significantly fluctuates both spatially and *** literature typically used standard air density or local annual average air density to assess wind *** present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in *** air density at 100 m height is accurately calculated by using air temperature,pressure,and *** spatial-temporal variation features of air density are firstly *** the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,***ρstoverestimates the annual wind energy production(AEP)in 93.6%of the study *** significantly affects AEP in central and southern China *** more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are ***ρsitesignificantly reduces the estimation error in *** AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in *** for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρ***ρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as *** impacts of air density on assessing wind resource are almost independent of the wind turbine types.

关键词： air density spatial-temporal variation power curve wind resource assessment fluctuation ERA-5

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An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 511-525页

作者： Yongbai Liu Keping Liu Gang Wang Jiliang Zhang Yao Chou Zhongbo Sun Department of Mechanical Engineering Changchun University of TechnologyChangchunChina Department of Control Engineering Changchun University of TechnologyChangchunChina School of Electrical and Information Engineering Jilin Engineering Normal UniversityChangchunChina College of Information Science and Engineering Northeastern UniversityShenyangChina Department of Electrical and Computer Engineering Brigham Young UniversityProvoUtahUSA

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ***,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be *** deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI *** upper limb-robotic exoskeleton system is re-modelled as an artificial *** on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical ***,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and *** results substantiate the global convergence and robustness of the proposed controller in the presence of different external *** addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

关键词： neural network pattern recognition robotics signal processing

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Effects of Distributed Generation on Carbon Emission Reduction of Distribution Network

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Distributed Generation and Alternative Energy Journal 2024年第1期39卷 57-82页

作者： Wu, Di Su, Jun Chen, Zhengyu Liu, Hanhan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen China

Increasing renewable energy integration in power systems is an important way of decarbonising carbon emissions. Recently, the ever-increasing deployment of distributed generation (DG) is considered effective in reducing carbon emissions and power loss, such as wind, photovoltaic (PV), and combined heat and power generation (CHP) on the demand side. Thus, the evaluation of carbon emission flow (CEF) will be a crucial factor for distribution network planning with the integration of DGs, which may act as a supplemented indicator in addition to traditional power flow study. In the planning stage, it is paramount to ensure that decarbonisation process of the power distribution system is in line with environmental and technical targets. Thus, the paper proposes a modelling strategy to combine the power flow and carbon emission flow. It aims to analyse and calculate the CEF based on the power-flow study. The novel model satisfies the power flow and CEF balance and can be directly used to evaluate the decarbonization of power system. The results of this study can help relevant energy decision-makers to do appropriate renewable energy generation planning and guide the power system to achieve carbon neutrality. © 2024 Taylor and Francis Inc.. All rights reserved.

关键词： Carbon

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Enhancing Unmanned Ground Vehicle Evasion Through Generative Adversarial Imitation Learning in UAV Pursuit Scenarios

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Guidance,Navigation and control 2025年第1期05卷 149-154页

作者： Shuai Hao Zhaoyu Zhang Mengzhen Huo Chen Wei School of Automation Science and Electrical Engineering Beihang University National Key Laboratory of Aircraft Integrated Flight Control Beihang University

This study focuses on enhancing the evasion capabilities of unmanned ground vehicles(UGVs) using Generative Adversarial Imitation Learning(GAIL). The UGVs are trained to evade unmanned aerial vehicles(UAVs). A decision-making neural network has been trained via GAIL to refine evasion strategies with expert demonstrations. The simulation environment was developed with OpenAI Gym and calibrated with real-world data for the improvement of accuracy. The integrated platform including the proposed algorithm was tested in flight experiments. Results showed that the UGVs could effectively evade UAVs in the complex and dynamic environment.

关键词： Unmanned ground vehicles unmanned aerial vehicles imitation learning flight experiment

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Effects of mechanical interfaces on magnetic levitation systems and analysis of self-excited vibration mechanisms in coupled systems

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Science China(Technological Sciences) 2024年第12期67卷 3925-3939页

作者： TANG JingHu LI ChaoFeng ZHOU Jin WU ZhiWei School of Mechanical Engineering&Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Northeastern University Shenyang 110819China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 20016China

Magnetic levitation is a non-self-stabilizing system that requires high control *** system's stability is affected by the mechanical interface between the levitation object and the loading device,with self-excited vibration generated in the operation *** paper proposes to consider the mechanical behavior of the contact interface in the magnetic levitation *** electromagnetic and control systems are mechanically equivalent,the coupled electric-magnetic-mechanical model is established by adopting the lumped mechanical modeling ***,the effect of the contact clearance on the mechanical behavior of the system is analyzed using the Routh-Hurwitz *** research results show that with the decrease in the contact clearance,the vibration frequency *** the vibration frequency exceeds the critical value,a continuous vibration phenomenon occurs in the system under the joint action of feedback and energy ***,the effect of interface parameters on the vibration characteristics is analyzed using the fourth-order Runge-kutta numerical *** analyses show that the interface contact leads to combination frequency and frequency multiplication components in the coupled system.

关键词： magnetic levitation coupled systems self-excited vibrations mechanical interfaces nonlinear vibrations

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Blockchain based federated learning for intrusion detection for Internet of Things

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Frontiers of computer Science 2024年第5期18卷 109-119页

作者： Nan SUN Wei WANG Yongxin TONG Kexin LIU School of Cyber Science and Technology Beihang UniversityBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China School of Computer Science and Engineering Beihang UniversityBeijing 100191China

In Internet of Things(loT),data sharing among different devices can improve manufacture efficiency and reduce workload,and yet make the network systems be more vulnerable to various intrusion *** has been realistic demand to develop an efficient intrusion detection algorithm for connected *** of existing intrusion detection methods are trained in a centralized manner and are incapable to identify new unlabeled attack *** this paper,a distributed federated intrusion detection method is proposed,utilizing the information contained in the labeled data as the prior knowledge to discover new unlabeled attack ***,the blockchain technique is introduced in the federated learning process for the consensus of the entire *** results are provided to show that our approach can identify the malicious entities,while outperforming the existing methods in discovering new intrusion attack types.

关键词： intrusion detection federated learning new attacks discovering blockchain

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Research and application of composite stochastic resonance in enhancement detection

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Chinese Physics B 2024年第1期33卷 264-273页

作者：高蕊焦尚彬薛琼婕 School of Automation and Information Engineering Xi'an University of TechnologyXi'an 710048China School of Electronic and Electrical Engineering Baoji University of Arts and SciencesBaoji 721016China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an 710048China

Aiming at the problem that the intermediate potential part of the traditional bistable stochastic resonance model cannot be adjusted independently, a new composite stochastic resonance(NCSR) model is proposed by combining the Woods–Saxon(WS) model and the improved piecewise bistable model. The model retains the characteristics of the independent parameters of WS model and the improved piecewise model has no output saturation, all the parameters in the new model have no coupling characteristics. Under α stable noise environment, the new model is used to detect periodic signal and aperiodic signal, the detection results indicate that the new model has higher noise utilization and better detection ***, the new model is applied to image denoising, the results showed that under the same conditions, the output peak signal-to-noise ratio(PSNR) and the correlation number of NCSR method is higher than that of other commonly used linear denoising methods and improved piecewise SR methods, the effectiveness of the new model is verified.

关键词： Woods–Saxon improved piecewise model composite stochastic resonance(SR) image denoising

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Research on modeling and self-excited vibration mechanism in magnetic levitation-collision interface coupling system

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 873-890页

作者： Jinghu TANG Chaofeng LI Jin ZHOU Zhiwei WU School of Mechanical Engineering&Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems of Ministry of Education of China Northeastern UniversityShenyang 110819China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The modeling and self-excited vibration mechanism in the magnetic levitation-collision interface coupling system are *** effects of the control and interface parameters on the system's stability are *** frequency range of self-excited vibrations is investigated from the energy point of *** phenomenon of self-excited vibrations is elaborated with the phase *** corresponding control strategies are briefly analyzed with respect to the vibration *** results show that when the levitation objects collide with the mechanical interface,the system's vibration frequency becomes larger with the decrease in the collision gap;when the vibration frequency exceeds the critical frequency,the electromagnetic system continues to provide energy to the system,and the collision interface continuously dissipates energy so that the system enters the self-excited vibration state.

关键词： magnetic levitation coupling system self-excited vibration mechanical interface vibration frequency

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