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arXiv 2024年

作者： Liu, Kaige Zhang, Hengkang Liu, Zeqi Zhang, Bin Fu, Xing Yuan, Qiang Liu, Qiang Ministry of Education Beijing100084 China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Tsinghua University Beijing100084 China Research Center of Laser Fusion China Academy of Engineering Physics Mianyang621900 China Beijing Institute of Control Engineering Beijing100190 China Beijing Institute of Electronic System Engineering Beijing100854 China

Strongly scattering media disrupt both the wavefront distribution and the polarization state of the incident light field. controlling and effectively utilizing depolarization effects are crucial for optical applications in highly scattering environments, such as imaging through dense fog. However, current simulation models have difficulty simulating the evolution of vector light fields within scattering media, posing challenges for studying vector light fields in strongly scattering environments. Here, we propose the Vector Angular Spectrum (VAS) model for simulating the propagation of vector light fields within scattering media. By introducing the angular spectrum distribution of vector light scattering and polarization conversion mechanisms, this model can simulate the depolarization effects of vector light propagating through strongly scattering media. The VAS model has also been used to investigate the focusing of vector scattered light through scattering media. Furthermore, the simulation results of the model have been validated through experiments. The proposed VAS model is expected to play a role in the theoretical research of vector scattered light and optical applications in strongly scattering environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Vectors

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Sensing With Random Communication Signals

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IEEE Network 2025年

作者： Lu, Shihang Liu, Fan Xiong, Yifeng Du, Zhen Cui, Yuanhao Li, Shuangyang Yuan, Weijie Yang, Jie Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China Nanjing University of Information Science and Technology School of Electronic and Information Engineering Nanjing210044 China Technical University of Berlin Faculty of Electrical Engineering and Computer Science Berlin10587 Germany Shenzhen518055 China Frontiers Science Center for Mobile Information Communication and Security China Southeast University MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing211189 China

Communication-centric Integrated Sensing and Communication (ISAC) has been recognized as a promising methodology to implement wireless sensing functionality over existing network architectures, due to its cost-effectiveness and backward compatibility to legacy cellular systems. However, the inherent randomness of the communication signal may incur huge fluctuations in sensing capabilities, leading to unfavorable detection and estimation performance. To address this issue, we elaborate on random ISAC signal processing methods in this article, aiming at improving the sensing performance without unduly deteriorating the communication functionality. Specifically, we commence by discussing the fundamentals of sensing with random communication signals, including the performance metrics and optimal ranging waveforms. Building on these concepts, we then present a general framework for random ISAC signal transmission, followed by an in-depth exploration of time-domain pulse shaping, frequency-domain constellation shaping, and spatial-domain precoding methods. We provide a comprehensive overview of each of these topics, including models, results, and design guidelines. Finally, we conclude this article by identifying several promising research directions for random ISAC signal transmission. © 2025 IEEE.

关键词： Mobile telecommunication systems

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Rotating machinery fault diagnosis based on convolutional neural network and infrared thermal imaging

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Chinese Journal of Aeronautics 2020年第2期33卷 427-438页

作者： Yongbo LI Xiaoqiang DU Fangyi WAN Xianzhi WANG Huangchao YU MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi’an 710072China School of Mechanical Engineering Northwestern Polytechnical UniversityXi’an 710072China Institute of Unmanned System National University of Defense TechnologyChangsha 410073China

Rotating machinery is widely applied in industrial *** diagnosis of rotating machinery is vital in manufacturing system,which can prevent catastrophic failure and reduce financial ***,Deep Learning(DL)-based fault diagnosis method becomes a hot *** Neural Network(CNN)is an effective DL method to extract the features of raw data *** paper develops a fault diagnosis method using CNN for InfRared Thermal(IRT)***,IRT technique is utilized to capture the IRT images of rotating ***,the CNN is applied to extract fault features from the IRT *** the end,the obtained features are fed into the Softmax Regression(SR)classifier for fault pattern *** effectiveness of the proposed method is validated using two different experimental *** show that the proposed method has a superior performance in identification various faults on rotor and bearings comparing with other deep learning models and traditional vibration-based method.

关键词： Convolutional neural network Feature extraction Infrared thermography(IRT) Intelligent fault diagnosis Rotating machinery

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A New Method to Estimate the Severity of Interturn Short-Circuit Fault for PMSM

A New Method to Estimate the Severity of Interturn Short-Cir...

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2022 IEEE International Conference on Power systems and Electrical Technology, PSET 2022

作者： Zeng, Zhaofei Zhang, Man Chen, Luan Huang, Qi Sun, Ding University of Electron Ic Science and Technology of China Key Laboratory of Wi De-area Measurement and Control on Power System of Sichuan Province Chengdu611731 China University of Electronic Science and Technology of China Chengdu611731 China Institute of Electronic and Information Engineering of Uestc in Guangdong Uestc in Guangdong Dongguan523808 China Chengdu Univer Sity of Technology Chengdu610095 China

ISBN: (纸本)9781665489157

This paper proposes a new method to determine the number of shorted turns for permanent magnet synchronous motor (PMSM). At first, the equivalent circuit model of PMSM under both normal condition and inter-turn short-circuit (ITSC) fault are presented. Then, the procedure to estimate the severity of ITSC in PMSM is introduced. In detailed, the stator winding of PMSM at standstill is excited by a low AC voltage, the corresponding current can be measured including its amplitude and phase, finally, the severity estimation indicator is established based on the electromagnetic parameters, including amplitude and phase of voltage and current, phase inductance and resistance. The effectiveness of the proposed method is verified by some simulations, which illustrates that the proposed method have good accuracy in the number of shorted turns detection in the range from the fault-free state to the full-winding fault state. The method proposed in this paper can be directly implemented without installing complex equipment and additional sensors on the motor, and it has utility value in the maintenance of PMSM. © 2022 IEEE.

关键词： Permanent magnets

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Hybrid Beamforming Design for Bistatic Integrated Sensing and Communication systems

arXiv

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arXiv 2025年

作者： Mao, Tianhao Yang, Jie Liang, Le Jin, Shi National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

Integrated sensing and communication (ISAC) in millimeter wave is a key enabler for next-generation networks, which leverages large bandwidth and extensive antenna arrays, benefiting both communication and sensing functionalities. The associated high costs can be mitigated by adopting a hybrid beamforming structure. However, the well-studied monostatic ISAC systems face challenges related to full-duplex operation. To address this issue, this paper focuses on a three-dimensional bistatic configuration that requires only half-duplex base stations. To intuitively evaluate the error bound of bistatic sensing using orthogonal frequency division multiplexing waveforms, we propose a positioning scheme that combines angle-of-arrival and time-of-arrival estimation, deriving the closed-form expression of the position error bound (PEB). Using this PEB, we develop two hybrid beamforming algorithms for joint waveform design, aimed at maximizing achievable spectral efficiency (SE) while ensuring a predefined PEB threshold. The first algorithm leverages a Riemannian trust-region approach, achieving superior performance in terms of global optima and convergence speed compared to conventional gradient-based methods, but with higher complexity. In contrast, the second algorithm, which employs orthogonal matching pursuit, offers a more computationally efficient solution, delivering reasonable SE while maintaining the PEB constraint. Numerical results are provided to validate the effectiveness of the proposed designs. Copyright © 2025, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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High-Order Disturbance Observer-Based Attitude control with Prescribed Performance for Hypersonic Vehicle

High-Order Disturbance Observer-Based Attitude Control with ...

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第40届中国控制会议

作者： GuangHui Yang Xinming Wang Beijing Aerospace Automatic Control Institute School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Eduaction

This paper presents a high-order disturbance observer-based attitude tracking controller design with prescribed performance for hypersonic vehicle. The lumped disturbances caused by parameters perturbations, external disturbances and unmodelled dynamics are estimated accurately by utilizing high-order disturbance observers. Based on the disturbances estimation,a composite attitude tracking controller with guaranteeing prescribed transient and steady performance is proposed and the stability analysis of the closed-loop system is rigorously analyzed using the Lyapunov technique. The proposed controller not only ensures the tracking errors are within the desired performance envelope but also considering the disturbance rejection. Finally,the effectiveness of the proposed method is verified by simulations.

关键词： Hypersonic Vehicle Disturbance Observer Prescribed Performance control Dynamics Surface control

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New Sensing Technologies for Monitoring Machinery,Structures,and Manufacturing Processes

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Journal of Dynamics, Monitoring and Diagnostics 2023年第2期2卷 69-88页

作者： JDMD Editorial Office Zhaoyan Fan Robert X.Gao Qingbo He Yi Huang Tianxi Jiang Zhike Peng Luc Thévenaz Yuyong Xiong Shuncong Zhong Editorial Office of JDMD Chongqing University of TechnologyChongqingPeople’s Republic of China Department of Mechanical Industrialand Manufacturing EngineeringOregon State UniversityCorvallisORUSA Department of Mechanical and Aerospace Engineering Case Western Reserve UniversityClevelandOHUSA State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghaiPeople’s Republic of China Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhouPeople’s Republic of China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhouPeople’s Republic of China School of Mechanical Engineering Ningxia UniversityYinchuanPeople’s Republic of China EPFL Ecole Polytechnique Fédérale de Lausanne Group for Fibre OpticsSCI-STI-LT Station 111015 LausanneSwitzerland

Sensing is the fundamental technique for sensor data acquisition in monitoring the operation condition of the machinery,structures,and manufacturing *** this paper,we briefly discuss the general idea and advances of various new sensing technologies,including multiphysics sensing,smart materials and metamaterials sensing,microwave sensing,fiber optic sensors,and terahertz sensing,for measuring vibration,deformation,strain,acoustics,temperature,spectroscopic,*** on the observations from the state of the art,we provide comprehensive discussions on the possible opportunities and challenges of these new sensing technologies so as to steer future development.

关键词： fiber optic sensor metamaterials sensing microwave sensing multiphysics sensing terahertz sensing

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Biologically inspired information integration pooling module of spiking neural networks for rolling bearing fault diagnosis

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Expert systems with Applications 2025年 286卷

作者： Shi, Mingfei Jiang, Feng Li, Yongbo Du, Lin MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China Unmanned System Research Institute Northwestern Polytechnical University Xi'an710072 China School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'an710072 China School of Aeronautics Northwestern Polytechnical University Xi'an710072 China School of Mathematics and Statics Northwestern Polytechnical University Xi'an710072 China MOE Key Laboratory for Complexity Science in Aerospace Northwestern Polytechnical University Xi'an710072 China

Rolling bearings constitute critical components in mechanical systems, and their effective fault diagnosis plays a vital role in ensuring operational safety and reliability. Despite substantial advancements in diagnostic methodologies, achieving high-precision, low-latency fault detection in large-scale rolling bearing datasets remains a persistent challenge. Artificial neural networks to spiking neural networks (ANN-to-SNN) conversion algorithms offer promising solutions for reducing computational costs and hardware adaptation barriers compared to conventional approaches. However, inherent information degradation during conversion processes has been demonstrated to significantly undermine model performance in terms of accuracy, stability, and interpretability. To overcome these limitations, we propose IIPooling, a novel Information-Integration biological neural mechanism-inspired Pooling module designed to enhance global structural feature extraction. The proposed framework incorporates three core neurobiological information processing principles: (1) promotion, (2) lateral inhibition, and (3) longitudinal inhibition, effectively simulating biological neuronal spiking patterns while optimally utilizing ANN activation characteristics. Additionally, we develop two adaptive learning mechanisms — Surrogate Gradient Adaptive Learning and Spiking Spatiotemporal Adaptive Learning — to implement negative feedback mechanism and adaptive parameter adjustment, thereby improving cross-conditional generalization capabilities. Comprehensive evaluations conducted on five bearing datasets (CWRU: DE/FE, PU, and Lab-collected: 6025/N205EW) demonstrate superior performance across four metrics (ACC, AUC, AUPRC, Mean-ACC). Our method achieves state-of-the-art results, notably attaining ACC values of 0.959 (CWRU-DE) and 0.861 (Lab-N205EW) in IIPooling-ST configurations, confirming its effectiveness for real-time, high-accuracy fault detection in complex operational environments. © 2025

关键词： Failure rate

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Stochastic DoS Attack Allocation Against Collaborative Estimation in Sensor Networks

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IEEE/CAA Journal of Automatica Sinica 2020年第5期7卷 1225-1234页

作者： Ya Zhang Lishuang Du Frank L.Lewis School of Automation Southeast Universityand also with the Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of EducationNanjing 210096China University of Texas at Arlington Research Institute Fort WorthTX 76118 USA IEEE

In this paper,denial of service(DoS)attack management for destroying the collaborative estimation in sensor networks and minimizing attack energy from the attacker perspective is *** the communication channels between sensors and a remote estimator,the attacker chooses some channels to randomly jam DoS attacks to make their packets randomly dropped.A stochastic power allocation approach composed of three steps is ***,the minimum number of channels and the channel set to be attacked are ***,a necessary condition and a sufficient condition on the packet loss probabilities of the channels in the attack set are provided for general and special systems,***,by converting the original coupling nonlinear programming problem to a linear programming problem,a method of searching attack probabilities and power to minimize the attack energy is *** effectiveness of the proposed scheme is verified by simulation examples.

关键词： Attack allocation denial of service(DoS)attack packet loss remote estimation sensor networks

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An enhanced algorithm for cell-level anomaly segmentation in photovoltaic solar panels using electroluminescence imaging

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Energy 2025年 331卷

作者： Ruiyao Duan Yongjian Wang Xisong Chen Shihua Li School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 PR China Institute for Automatic Control and Complex System University of Duisburg–Essen Duisburg 47057 Germany

Electroluminescence imaging is a crucial diagnostic tool for assessing the quality and performance of photovoltaic (PV) modules. However, current research often focuses on defect detection in PV modules, neglecting the need for detailed segmentation at the individual cell level. To address the limitations of existing methods in recognizing complex defects and suppressing background noise, this paper proposes a novel semantic segmentation algorithm (CAAK-Net), capable of identifying anomalies at the cell level of photovoltaic panels. To enhance network performance, CAAK-Net uses K-Net as a baseline and incorporates the Convolutional Block Attention Module (CBAM), Attention Refinement Module (ARM), and Atrous Spatial Pyramid Pooling (ASPP) modules. Experimental results comparing CAAK-Net with mainstream segmentation networks demonstrate its superior segmentation performance, particularly in recognizing defect edges and small-area attached defects. Additionally, we establish a quantitative correlation model between detection errors and PV system efficiency losses, pioneering the translation of pixel-level segmentation accuracy into measurable operational costs, thereby providing an economic assessment framework for industrial PV inspection. Furthermore, the network exhibits a certain degree of robustness in noisy environments, showcasing its segmentation advantages in diverse defect scenarios.

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