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International Conference on Power Electronics and Motion control (IPEMC)

作者： Yi Yang Xiaohua Wu Gang Yang Ji Yan Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province School of Automobile and Transportation Xihua University Chengdu China Sichuan Engineering Research Center of Intelligent Control and Simulation Test Technology for New Energy Vehicles Xihua University Chengdu China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

Lithium-ion batteries’ state of health (SOH) is critical to safely managing electric vehicles (EVs). This paper proposes a battery health prognostic framework based on charging data for real-world EVs. First, the capacity of the battery is calculated using the ampere-hour integration method based on historical charging data. The capacity trend is fitted using the locally weighted linear regression (LWLR) algorithm and the effect of charging depth on the capacity calculation results is eliminated. Then, the features strongly correlated with battery capacity are extracted using Pearson correlation analysis (PCA). Finally, Gaussian process regression (GPR) is employed to establish the capacity estimation model of lithium-ion batteries. The effectiveness and accuracy of the proposed method are validated on EVs from different regions. The results indicate that the mean absolute error (MAE) and the root mean square error (RMSE) of the estimated capacity on the test set are both less than 0.5.

关键词： Lithium-ion batteries Accuracy Estimation Feature extraction Market research Electric vehicles State of charge

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MIMO Radar Polyphase Waveform Design via Optimal Loss Function-Based Soft Quantization

MIMO Radar Polyphase Waveform Design via Optimal Loss Functi...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Ye Yuan Xin Tai Kai Zhong Yongfeng Zuo Jinfeng Hu Yangtze Delta Region Institute (Quzhou) University of Electronic Science and Technology of China Quzhou China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Electronic Test and Measurement Laboratory Ceyear Technologies Company Ltd

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Polyphase waveform design for the minimization of Integrated Sidelobe Level Ratio (ISLR) is the key technology in Multiple-Input Multiple-Output (MIMO) radar systems. Due to the discrete phase constraint, the problem is non-convex and challenging to solve. Existing methods often rely on experience-based hard quantization with fixed thresholds, leading to limited performance due to the hard quantization. To address this issue, we propose the Optimal Loss Function-Based Soft Quantization (OLF-SQ) method with adjustable quantization thresholds. Firstly, the Complex Circle Manifold (CCM) space is constructed to satisfy the constant modulus constraint, and then the Gradient Descent (GD) model-driven network layer based on the CCM is devised to obtain the continuous waveform. Secondly, the soft quantization function is derived with adjustable quantization thresholds, and then the soft quantization network layer is devised to obtain the discrete waveform, where the quantization thresholds are learned by the unsupervised learning network. Compared with the existing methods, the proposed method has better performance in terms of ISLR and beampattern shaping.

关键词： Manifolds Quantization (signal) MIMO radar Geoscience and remote sensing Minimization Computational complexity Unsupervised learning

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Reconfigurable Feed Network For Multi-Polar Antennas

Reconfigurable Feed Network For Multi-Polar Antennas

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Fengyuan Shi Juan Chen Wenjing Xu Jianfeng Yang Jing Tan School of information and communication engineering Xi'an Jiaotong University Xi'an China School of Information and control engineering Xi'an University of Architecture and Technology Xi'an China Department of Antenna Shanghai Aerospace Electronic Technology Institute Shanghai China

A reconfigurable feed network for multi-polar antennas is proposed in this article. It uses PIN diodes to make reconfigurable structure and change the output. The network can produce four kinds of output signal with only one input port. It has four output ports with specific phase delay, which uses differential-feed to suppress cross polarization. The simulated results show that the operating frequency range of the feed network is about 2.5-3.5 GHz with good matching and isolation performance. The variable polarization and wide band make it be a good choice for late-model multi-polar antennas with both linear and circular polarization.

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Optimal controller Design for Non-Affine Nonlinear Power Systems with Static Var Compensators for Hybrid UAVs

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Tsinghua Science and technology 2022年第1期27卷 196-206页

作者： Yanchu Li Qingqing Ding Shufang Li Stanimir Valtchev Beijing Key Laboratory of Network System Architecture and Convergence Beijing Laboratory of Advanced Information Networkand School of Information&Communication EngineeringBeijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua UniversityBeijing 100084China the Nova School of Science and Technology(FCT/UNL) Caparica 2829-516LisbonPortugal Technical University of Sofia(TUS) Sofia 2125Bulgaria

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator(SVC)or State Var System(SVS)for hybrid Unmanned Aerial Vehicles(UAVs).The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its *** the inverse system method and the Linear Quadratic Regulation(LQR),an optimized SVC controller is *** simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

关键词： Static Var Compensator(SVC) Unmanned Aerial Vehicles(UAV) power system non-affine nonlinear control inverse system method Linear Quadratic Regulation(LQR)

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Video Stabilization via Prediction with Time-Series Network and Image Inpainting with Pyramid Fusion

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Chinese Journal of Electronics 2021年第6期30卷 1103-1110页

作者： CHENG Keyang LI Shichao RONG Lan WANG Wenshan SHI Wenxi ZHAN Yongzhao School of Computer Science and Communication Engineering Jiangsu University Jiangsu Province Big Data Ubiquitous Perception and Intelligent Agricultural Application Engineering Research Center Cyber Space Security Academy of Jiangsu University National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data Xinjiang Lianhaichuangzhi Information Technology Co. Ltd.

Due to the poor filling effect of the video image defect commonly used in the video stabilization field, the video is seemed still unstable after the image stabilization process, which seriously affects the visual effect. To solve this problem, we improve a video stabilization method based on time-series network prediction and pyramid fusion restoration is proposed to optimize the visual effect after image *** flow of the proposed method is as follows: First,it is adaptive to determine whether the defect of the corresponding frame at the current time needs padding inpainting. Then, for the frame that needs to be inpainting,the frames generated before the current moment are sent to the model combining the convolutional neural networks and the gate recurrent unit to predict the part to be filled. Next the current defect image and the complete image to be filled are brought into the Laplacian pyramid reconstruction, and the improved weighted optimal suture is introduced for splicing during the fusion. Finally, the video frame is cut after reconstruction. The method is tested on a data set composed of videos commonly used in the field of video stabilization. The experimental results show that the average peak signal to noise ratio of the method is 2 to 5 d B higher than that of the comparison algorithm, and the average structural similarity index is improved by about 2% to 7% compared with the contrast algorithm.

关键词： image restoration image sequences video frame cutting improved weighted optimal suture gate recurrent unit video signal processing video stabilization method image fusion Laplacian pyramid reconstruction padding inpainting image resolution neural nets convolutional neural networks video image defect pyramid fusion restoration image inpainting visual effect optimization image reconstruction time-series network prediction image stabilization process

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A Cross-Task Transfer SAR Target Recognition Method Based on AMFFNet and IACGAN

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Wan, Xunyang Du, Xiaolin Cui, Guolong Chen, Xiaolong Zheng, Jibin Yantai University School of Computer and Control Engineering Yantai264005 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Naval Aviation University Yantai264001 China Xidian University National Key Laboratory of Radar Signal Processing Xi'an710071 China

Convolutional neural networks (CNN) have shown excellent capability in synthetic aperture radar (SAR) target recognition. However, obtaining sufficient training samples for improving network recognition is difficult due to the deficiency of labeled SAR image data. To tackle the problem, a cross-task transfer method for SAR target recognition is proposed in this paper, which is based on a designed attention multi-scale feature fusion network (AMFFNet) and an improved auxiliary classifier generative adversarial network (IACGAN). In this method, firstly, a data augmentation method based on you only cut twice (YOCT) is devised for expanding the training samples. Secondly, the partial weight parameters of AMFFNet are initialized by the pre-trained IACGAN discriminator. Finally, AMFFNet is fine-tuned using the training samples. Additionally, on the network structure of AMFFNet, multi-scale features are extracted by adopting a multi-scale depth separable convolution module, which allows the model to acquire more informative features. Attention mechanisms are employed in this network to enhance its ability to capture important features while reducing the effects of noise. A multi-level feature fusion structure is used to further raise the representational capability of the model. Experimental results on multiple open-source real SAR datasets show that the proposed method can achieve better recognition performance under different percentages of training data, and the effectiveness and superiority of the method are confirmed by its robustness to noise. © 1965-2011 IEEE.

关键词： Convolutional neural networks

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Optimal Resource Allocation for UAV-Relay-Assisted Mobile Crowdsensing

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IEEE Transactions on communications 2024年

作者： Yang, Xiaolong Fu, Yaru Zheng, Jianchao Xu, Zhan Shao, Ruihao Wu, Yuan Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beijing Information Science and Technology University School of Information and Communication Engineering Beijing100101 China Hong Kong Metropolitan University School of Science and Technology Hong Kong999077 Hong Kong Academy of Military Science Beijing100091 China University of Macau State Key Laboratory of Internet of Things for Smart City The Department of Computer and Information Science Macau China

In this paper, we exploit an emergency mobile crowdsensing (MCS) framework that utilizes unmanned aerial vehicles (UAVs) in collaboration with uncrashed base stations (BSs) to enhance sensing and communication efficiency. In the proposed framework, mobile users (MUs) equipped with sensors collect data, while UAVs, deployed as aerial relays, collaborate with uncrushed BSs to facilitate the transmission and aggregation of the sensed data from all MUs. However, the limited resources significantly affect the deployment of UAVs and the design of the UAV-relay-assisted MCS system. Moreover, selecting MUs for sensing tasks and allocating bandwidth among them are crucial factors that determine MUs' sensing capabilities and the data transmitting policies. Incorporating with foregoing essential factors, we formulate a comprehensive problem that jointly optimizes the MU selection, bandwidth allocation, UAV deployment, as well as strategies for sensing and transmitting data, aiming to improve the total reward of agent. The formulated problem poses high challenges due to the coupling between the sensing, transmission, as well as the UAVs deployment policies. To deal with this problem, we first derive the optimal transmission power and sensing data size under given MU selection, bandwidth allocation, and UAVs deployment strategy. The original optimization problem is subsequently decomposed into three folds, corresponding to finding the optimal MU selection, bandwidth allocation solution, as well as the deployment of UAVs. Meanwhile, a joint dynamic programming and a swap-then-compare enabled algorithm is proposed to obtain the optimal MU selection and bandwidth allocation policies. Next, the successive convex approximation (SCA) techniques are used to find the optimal locations for the UAVs. Extensive numerical results verify that the proposed joint algorithm can significantly outperform several benchmark approaches. © 1972-2012 IEEE.

关键词： Bandwidth

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A Non-intrusive Method for Liquid Level measurement in Vertical Pipeline Using Ultrasonic Lamb Wave

A Non-intrusive Method for Liquid Level Measurement in Verti...

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IEEE Instrumentation and measurement technology Conference

作者： Zixiang Shi Yong Bao Chao Tan Jinhai Liu Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical and Information Engineering Tianjin University Tianjin China CNOOC Energy Technology & Services-Oil Production Services Co Tianjin China School of Information and Intelligent Engineering Tianjin Renai College Tianjin China

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

The liquid accumulation in long distance coal-bed-methane gathering and transportation pipeline will hinder the effective gas transport and accelerate pipeline corrosion. Liquid level measurement techniques, which are a crucial step to overcome these liquid-accumulation-related problems, are mostly either invasive or inaccurate due to the fluctuation of liquid phase. Concerning the limitation of the traditional level measurement technique, a clamp-on liquid level measurement method using ultrasonic Lamb waves is proposed. According to the dispersion curve in the circular pipe, the optimum operating mode and excitation parameters are determined. During experiments, the nonlinear relationship between vertical pipeline liquid level and Lamb wave amplitude is obtained. Meanwhile, the ability of identifying liquid level changes is improved by the algorithm of denoising and filtering the received signal. Based on the results, the proposed measurement can be used for liquid level measurement and provides a potential of flow condition measurement of gathering lines.

关键词： Liquids Ultrasonic variables measurement Filtering Propagation Pipelines Noise reduction Transportation

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Mitigating Receiver Impact on Radio Frequency Fingerprint Identification via Domain Adaptation

arXiv

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arXiv 2024年

作者： Yang, Liu Li, Qiang Ren, Xiaoyang Fang, Yi Wang, Shafei School of Information and Communication Engineering University of Electronic Science and Technology of China P. Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China

Radio Frequency Fingerprint Identification (RFFI), which exploits non-ideal hardware-induced unique distortion resident in the transmit signals to identify an emitter, is emerging as a means to enhance the security of communication systems. Recently, machine learning has achieved great success in developing state-of-the-art RFFI models. However, few works consider cross-receiver RFFI problems, where the RFFI model is trained and deployed on different receivers. Due to altered receiver characteristics, direct deployment of RFFI model on a new receiver leads to significant performance degradation. To address this issue, we formulate the cross-receiver RFFI as a model adaptation problem, which adapts the trained model to unlabeled signals from a new receiver. We first develop a theoretical generalization error bound for the adaptation model. Motivated by the bound, we propose a novel method to solve the cross-receiver RFFI problem, which includes domain alignment and adaptive pseudo-labeling. The former aims at finding a feature space where both domains exhibit similar distributions, effectively reducing the domain discrepancy. Meanwhile, the latter employs a dynamic pseudo-labeling scheme to implicitly transfer the label information from the labeled receiver to the new receiver. Experimental results indicate that the proposed method can effectively mitigate the receiver impact and improve the cross-receiver RFFI performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Palmprint recognition

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Optimal Scheduling Model of Community Integrated Energy System Based on Cooperative Game Theory

Optimal Scheduling Model of Community Integrated Energy Syst...

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Power and Energy (PandaFPE), Panda Forum on

作者： Jialin Du Sen Zhang Shihua Luo Yiping Yuan Weihao Hu Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

Currently, a large number of community integrated energy systems operate independently and lack coordination and cooperation with each other. On the whole, the complementary coupling potential between energy production and consumption has not been fully explored, which is not conducive to the efficient utilization of clean energy. To solve the above problem, this paper proposes an optimal scheduling model of community integrated energy system considering integrated demand response and carbon tax. Moreover, based on cooperative game theory, this paper adopts the Sharpley value to achieve fair and reasonable distribution of cooperation profits. The case study results indicate that the energy sharing model proposed in this article can achieve better economic benefits.

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