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Energy optimization and experimental for a permanent magnet-biased redial magnetic bearing

Guangxue Jingmi Gongcheng/Optics and Precision engineering 2019年第11期27卷 2420-2428页

作者： Liu, Qiang Zhao, Ming-Shi Han, Bang-Cheng Fan, Ya-Hong Sun, Jin-Ji Zheng, Shi-Qiang Institute of Precision Electromagnetic Equipment and Advanced Measurement Technology Beijing Institute of Petrochemical Technology Beijing102617 China Key Laboratory of Inertial Technology Beihang University Beijing100191 China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100190 China

To address the requirement for low power of a magnetically suspended flywheel, the energy optimization of permanent magnet-biased radial magnetic bearing is studied. The magnetic circuit and working principles are introduced, based on the current stiffness and displacement stiffness mathematical models of a magnetic bearing, and the energy optimization factor σ of a magnetic bearing is obtained. The objective function of the power consumption of the magnetic bearing is then established, followed by optimization of the consumption. Subsequently, a mathematical expression for optimal power consumption and the value of σ are determined. The power consumption of the magnetic bearing is simulated and verified using the finite element method. The obtained results are tallied with the results of the theoretical analysis. Finally, based on the results of the optimization, a magnetic bearing is developed and power consumption is tested to improve the existing 15-Nms magnetically suspended flywheel. The results show that when the amplitude is 10 μm, the value of optimal power consumption for each winding is 0.85 W, with a maximum error of 7% compared with the theoretical optimal power consumption of 0.79 W. The designed efficiency of a magnetic bearing consuming low power is improved using the energy optimization method, which is important for the power optimization of flywheel systems. © 2019, Science Press. All right reserved.

关键词： Finite element method

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Unbalance vibration feedforward restraint and experiments for a magnetic bearing spherical flywheel

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Zhendong yu Chongji/Journal of Vibration and Shock 2019年第10期38卷 92-97and123页

作者： Liu, Qiang Yin, Zhaojing Wu, Bo Ren, Yuan Xin, Chaojun Fan, Yahong Institute of Precision Electromagnetic Equipment and Advanced Measurement Technology Beijing Institute of Petrochemical Technology Beijing102617 China Department of Space Equipment Aerospace Engineering University Beijing101416 China Beijing Institute of Control Engineering Beijing100190 China

Aiming at the unbalance vibration of a magnetic bearing spherical flywheel rotor, an unbalance vibration feedforward restraint method was presented by establishing the dynamic model of its spherical rotor-magnetic bearing. Based on the D'Alembert's principle, the unbalance mass moments was equivalent to two counterweights on the end planes of rotor, and the dynamic reaction of the magnetic bearing was obtained. To keep the shell gap its spherical configuration between stator and rotor and relieve the negative magnetic deflection moment induced by non-uniform magnetic field, the sphere centers of the rotor was made always coinciding with that of the stator. The centrifugal force caused by the deviation between the rotor mass center and spin axis was analysed. Considerning the electromagnetic levitation force always pointing to the sphere center, the caused negative moment was also calculated when the rotor mass center deviates from the rotor sphere center. When the two unbalance mass moments with phase difference of π were identical, the feedforward restraint simulations were implemented at the speed of 8 000 r/min. The results show that the rotor's radial and axial amplitudes decrease from 13.8 μm and 21.6 μm to 3.3 μm and 5.6 μm, which are reduced by 76.1% and 74.1%, respectively. The tests results have a good agreement with those of the simulations, which indicates the dynamic model is correct and feedforward restraint method is effective. © 2019, Editorial Office of Journal of Vibration and Shock. All right reserved.

关键词： Flywheels

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Covert beamforming design for intelligent reflecting surface assisted IoT networks

arXiv

引用

arXiv 2021年

作者： Ma, Shuai Zhang, Yunqi Li, Hang Sun, Junchang Shi, Jia Zhang, Han Shen, Chao Li, Shiyin School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Data-driven Information System Laboratory Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China State Key Laboratory of ISN School of Telecommunications Engineering Xidian University Xi’an710071 China Institute for Communication Systems University of Surrey GuildfordGU2 7XH United Kingdom State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

In this paper, we consider covert beamforming design for intelligent reflecting surface (IRS) assisted Internet of Things (IoT) networks, where Alice utilizes IRS to covertly transmit a message to Bob without being recognized by Willie. We investigate the joint beamformer design of Alice and IRS to maximize the covert rate of Bob when the knowledge about Willie’s channel state information (WCSI) is perfect and imperfect at Alice, respectively. For the former case, we develop a covert beamformer under the perfect covert constraint by applying semidefinite relaxation. For the later case, the optimal decision threshold of Willie is derived, and we analyze the false alarm and the missed detection probabilities. Furthermore, we utilize the property of Kullback-Leibler divergence to develop the robust beamformer based on a relaxation, S-Lemma and alternate iteration approach. Finally, the numerical experiments evaluate the performance of the proposed covert beamformer design and robust beamformer design. © 2021, CC BY.

关键词： Beamforming

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Carrying capacity calculation method of regional rail transit line based on flexible train formation

Carrying capacity calculation method of regional rail transi...

引用

International Conference on Intelligent Transportation

作者： Ying WANG Ling LIU Jun LIU Jing SHI Beijing National Railway Research& Design Institute of Signal &Communication Beijing China Operation Control Systems for High Speed Railways Beijing Engineering Technology Research Center Beijing China

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

Flexible train formation technology (FTFT) provides new prospects for addressing the imbalance in the space-time distribution of passenger flow in regional rail transit networks. In this study, we performed a detailed analysis of the operation organizations and technical characteristics of multiple formation, variable formation based on physical coupling, and variable formation based on virtual coupling. The proposed carrying capacity calculation method is mainly based on the parallel train diagram and is suitable for urban rail transit, suburban railway, and other lines, and adapts to FTFT. Actual data of the region are used to calculate the carrying capacity of the mainline railway in multiple scenarios. According to the verification, the calculation results are highly consistent with those of timetabling methods. We demonstrate that variable formation based on virtual coupling has the lowest impact on the carrying capacity. Finally, the applicability of different FTFT is explained according to the carrying capacity and technical operation characteristics.

关键词： Rail transportation Couplings Transportation Rails Mathematical model Organizations Periodic structures

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Calibration and orientation of industrial online photogrammetry systems in situ

Calibration and orientation of industrial online photogramme...

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7th International Symposium on Test Automation and Instrumentation, ISTAI 2018

作者： Sun, Peng Lu, Naiguang Dong, Mingli Wang, Jun Yan, Bixi Institute of Information Photonics and Optical Communication Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory: Measurement and Control of Mechanical Electrical System Beijing Information Science and Technology University Beijing China School of Instrument Science and Optoelectronics Engineering Beijing Information Science and Technology University Beijing China

This study proposes an analytical method for calibrating and orienting online photogrammetric systems using a scale bar. The primary idea is building control lengths in the measurement volume by moving and rotating the scale bar and then conducting a self-calibration bundle adjustment using images of the control lengths. In this study, the five-point relative orientation method is used to provide estimations of the exterior camera parameters. Additionally, this study elaborates the model of the lengths constrained self-calibration bundle adjustment, the block computation algorithm and the accuracy assessment. This method obtains both the interior and the exterior orientation parameters of the two cameras, and provides spatial bar length reconstruction precision as the performance evaluation. Simulations are conducted to analyze the calibration accuracy and the results show that the method achieves comparable accuracy and precision against the state-of-the-art method. However, the method does not need steady and well distributed 3D points and is easy to operate. Real data experimental results show that the maximum length measurement error of this method in a volume of 5 m × 4 m × 2 m is © 2019 Institution of engineering and technology. All rights reserved.

关键词： Photogrammetry

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A MAC Protocol Identification Approach Based on Convolutional Neural Network

A MAC Protocol Identification Approach Based on Convolutiona...

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International Conference on Wireless communications and Signal Processing (WCSP)

作者： Xutong Zhang Weiguo Shen Jianliang Xu Zitong Liu Guoru Ding Colledge of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Science and Technology on Communication Information Security Control Laboratory No.36 Research Institute of CETC Jiaxing China College of Communication Engineering Army Engineering University Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

The medium access control (MAC) protocol identification is of great application value in cognitive radio. In order to realize the MAC protocol identification with high accuracy and avoid manual feature extraction, we convert the sampled data into the form of spectrogram. Then, a graphical scheme which combines the convolutional neural network (CNN) and the spectrogram is proposed. The simulation includes CNN method and support vector machine (SVM) method. It is suggested that the CNN method has better identification performance.

关键词： Media Access Protocol Spectrogram Protocols Support vector machines Time division multiple access Feature extraction Cognitive radio

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Approximation of second order dead time system using generalized Laguerre functions

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AIP Conference Proceedings 2022年第1期2425卷

作者： Martin Tůma Pavel Jura Vilém Kárský Central European Institute of Technology CEITEC BUT Brno University of Technology Technicka 12 616 00 Brno Czech Republic Department of Control & Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Technicka 12 616 00 Brno Czech Republic

The aim of this text is to show that when approximating a 2nd order system with one double pole and with a dead time (DT), the approximation with the generalized Laguerre Function (GLF) for large DT gives better results than with the simple Laguerre function (SLF). For a given required integral square error (ISE), the GLF series has a smaller number of terms. However, for small DT, there is an area in which the SLF approximation gives a smaller ISE error.

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Leveraging uncertainties for deep multi-modal object detection in autonomous driving

arXiv

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arXiv 2020年

作者： Feng, Di Cao, Yifan Rosenbaum, Lars Timm, Fabian Dietmayer, Klaus Robert Bosch GmbH Corporate Research Driver Assistance Systems and Automated Driving Renningen71272 Germany Institute of Measurement Control and Microtechnology Ulm University Ulm89081 Germany Department of Mechanical Engineering Karlsruher Institute of Technology Karlsruhe76049 Germany

This work presents a probabilistic deep neural network that combines LiDAR point clouds and RGB camera images for robust, accurate 3D object detection. We explicitly model uncertainties in the classification and regression tasks, and leverage uncertainties to train the fusion network via a sampling mechanism. We validate our method on three datasets with challenging real-world driving scenarios. Experimental results show that the predicted uncertainties reflect complex environmental uncertainty like difficulties of a human expert to label objects. The results also show that our method consistently improves the Average Precision by up to 7% compared to the baseline method. When sensors are temporally misaligned, the sampling method improves the Average Precision by up to 20%, showing its high robustness against noisy sensor inputs. Copyright © 2020, The Authors. All rights reserved.

关键词： Object recognition

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Comparison of dead time estimation methods for dynamical systems

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AIP Conference Proceedings 2022年第1期2425卷

The analysis of dead time estimation problem is given. Dead time estimation method with generalized Laguerre functions is briefly presented. The results of presented method are compared with simple Laguerre functions, MATLAB Delayest and MAT-LAB Tder methods. The advantage of generalized Laguerre functions dead time estimation method is shown on data generated by MATLAB and also on real-life data generated from models of delayed dynamical systems.

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SEDNet: Substation Equipment Detection Network With an Attention Mechanism for UAV Automatic Power Inspection

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IEEE Transactions on Instrumentation and measurement 2025年 74卷

作者： Jiang Zhu Chonggao Fan Saisi Li Keheng Nie Jianqi Li Zhendong He School of Automation and Electronic Information Xiangtan University Xiangtan China Jiangxi Communication Terminal Industrial Technology Research Institute Company Ltd. Jian China Hunan Academy of Building Research Company Ltd. Changsha China Hunan Provincial Key Laboratory for Control Technology of Distributed Electric Propulsion Aircraft Changde China College of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou China

Detecting substation equipment in aerial infrared images is a critical task in automatic visual fault inspection for power systems. However, the uneven spatial distribution of objects, unmanned aerial vehicle (UAV) viewpoint variations, object scale variations, and rare computational resources pose significant challenges for substation equipment detection. This article proposes a substation equipment detection network (SEDNet) for UAV automatic power inspection. First, a long-distance feature capture (LDFC) attention is proposed to guide the network to focus on learning features in important regions and to capture the information that it is prone to miss at the border of an image. Moreover, a lightweight, GS cross-stage partial (GSCSP) structure is proposed to improve the speed of feature processing. Second, a multilayer receptive field feature enhancement module (MRFFEM) is constructed to extract diverse, fine-grained features of objects using multiple convolutional branches. Last, to effectively detect multiscale objects, we propose a concatenation and reorganization enhanced feature pyramid module (CREFPM). The experimental results demonstrate the effectiveness of SEDNet on a multiclass, substation equipment, infrared image dataset, achieving a detection accuracy of 99.2% and a real-time detection speed of 105.3 frames/s, which outperforms state-of-the-art models in terms of mAP. SEDNet successfully meets the requirements for accurate and real-time substation equipment inspection in complex scenarios.

关键词： Feature extraction Substations Autonomous aerial vehicles Inspection Accuracy Temperature measurement Attention mechanisms YOLO Semantics Insulators

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