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IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Yinping An Xiangping Meng Hui Wang Qi Yao Chunhui Liang Changchun University of Technology College of Electrical and Electronic Engineering Changchun China National Local Joint Engineering Research Center for Intelligent Distribution Network Measurement and control with Safety Operation Technology School of Electrical Engineering and Information Technology Changchun China Changchun Institute of Technology School of Electrical Engineering and Information Technology Changchun China

ISBN: (纸本)9781728137216

Aiming at the problem of large overshoot and long response time of bidirectional DC/DC in the energy storage part of DC micro-grid, a fuzzy self-tuning PI controller is designed in this paper to realize online setting of control parameters and achieve the purpose of optimizing traditional PI control. The results show that fuzzy self-tuning PI control can effectively solve the problem of slow tracking voltage and fluctuation in dc micro-grid.

关键词： Voltage control Batteries Supercapacitors PI control Photovoltaic systems

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Preface

EAI/Springer Innovations in Communication and Computing

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EAI/Springer Innovations in communication and Computing 2021年 vii-viii页

作者： Srivastava, Smriti Khari, Manju Crespo, Ruben Gonzalez Chaudhary, Gopal Arora, Parul Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi Delhi India Department of Computer Science and Technology Universidad Internacional de La Rioja Logroño La Rioja Spain Department of Electronics and Communication Engineering Jaypee Institute of Information Technology Noida India School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi Delhi India Department of Electronics and Communication Engineering Bharati Vidyapeeth’s College of Engineering New Delhi Delhi India

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An IoT Based Safe Assembly Point Alert System

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Journal of Physics: Conference Series 2021年第7期1964卷

作者： T Mangayarkarasi K Umapathy A Sivagami D Subitha Department of Instrumentation and Control Engineering Sri Sairam Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya University (Deemed University) Kanchipuram Tamil Nadu India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Chennai Tamil Nadu India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India

A large population depends on many industries for its livelihood like electrical, embedded, software product sectors. An IoT environment includes feedback phones that use smart devices, such as MCU (microcontroller unit), sensors and different sensors, collect, distribute, and act on messages they collect from their environment. IoT systems share the sensory data they receive when data has been either sent to the cloud for global applications or analysis by linking to an IoT gateway or other edge device. For the electrical maintenance occur in the industries will need a specific alert signal. The loss of manufacturing workers/workers may be controlled by a specific, minor accident. Therefore, it is essential to provide an emergency device able to detect the non-safety state of coal and produce an alarm to reduce the possibility of risks in the system. We are proposing an IoT-based alert system via mobile phones, as smartphones' general usage is very common in the industries rather than using a walkie-talkie.

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Research on Risk Indicator System of Smart Distribution Grid Based on LVQ Neural Network

Research on Risk Indicator System of Smart Distribution Grid...

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Chinese Automation Congress (CAC)

作者： Xiu Ji Dongping Bai Jiayu Xu Shaorui Liu Shuangshuang Shan National Local Joint Engineering Research Center for Smart Distribution Grid Measurement and Control with Safety Operation Technology ChangChun Institute Of Technology Changchun China Jilin Profit Technology Co. Ltd. Changchun China

This paper analyzes the self-healing function of smart distribution grid, and considers the impact of DG energy access and natural disasters on the smart distribution *** the analysis of several common risk prediction methods, and in combination with the practical situation of indicators of risk prediction, LVQ neural network was selected as the basic analysis method of risk indicator prediction in this paper, and the core analysis of this paper was realized by improving LVQ neural *** to the demand of actual risk indicator prediction,the risk indicator system of smart distribution grid is established, and the method of this paper is verified and analyzed with an actual example. By comparing with BP neural network, the improved LVQ neural network is proved to be more advantageous than BP neural network.

关键词： Neural networks Neurons Smart grids Training Cognition Predictive models

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Influence of elasticity modulus on the natural frequency in hemispherical resonator

Influence of elasticity modulus on the natural frequency in ...

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DGON Inertial Sensors and Systems Symposium

作者： Z. Xu G. Yi H. Fang Y. Cao L. Hu G. Zhang Department of Control Science and Engineering Harbin Institute of Technology (HIT) 150080 Harbin CHINA China Electronic Technology Group Corporation 26th Research Institute 400060 Chongqing CHINA Beijing Orient Institute of Measurement and Test 100086 Beijing CHINA

ISBN: (纸本)9781728119366

For any Coriolis vibratory gyroscopes, symmetrically perfect resonator is their core component. In order to analyze the influence of non-uniform elasticity modulus on the natural frequency in resonator, the finite element model of hemispherical resonator is established by using finite element analysis software (ANSYS). The second-order natural frequency of ideal resonator and resonator with elastic modulus non-uniform is analyzed. The relationship between elasticity modulus and natural frequency is established. The first fourth harmonics of elasticity modulus along the circumferential direction in resonator are mainly investigated that dominates mainly the amplitude of uneven elasticity modulus. The influence of the first fourth harmonic of non-uniform elastic modulus on the natural frequency is deeply analyzed, which will cause the natural frequency difference. The influence of the first four harmonics on the frequency difference is almost the same, which will bring approximately equal frequency difference. In order to reduce the influence of elasticity modulus non-uniform on the precision and performance of the HRG, the relative values of first fourth harmonics of elasticity modulus should be less than 1×10 -7 , which provides a theoretical basis for the manufacturing design and error analysis of resonator.

关键词： Resonant frequency Elasticity Finite element analysis Electrodes Shafts Gyroscopes Harmonic analysis

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Coherent H ∞ control for Markovian jump linear quantum systems

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IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

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measurement and analysis of motor-noise in underwater glider

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IOP Conference Series: Earth and Environmental Science 2021年第1期725卷

作者： Qing Zhou Yihao Zhao Maofa Wang Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033 China No.36 Research Institute of CETC Jiaxing 314033 China Ocean Engineering Research Center Hangzhou Dianzi University Hangzhou 310018 China

Self-noise is a very disadvantageous factor for underwater glider to observe ocean ambient noise, in which the noise caused by motor is very significant. In order to grasp the characteristics of the motor-noise and its influence on the measurement of ocean ambient noise, a long-term sea trial was conducted in the South China Sea in May 2020, and the self-noise data of underwater glider under different working conditions are obtained. By analyzing the noise level and spectrum level of the motor noise, we obtained the self-noise spectrum characteristics and know that the influence of control motor noise on the noise measurement of head and tail hydrophone is mainly below 5 kHz band, and the influence of full-frequency noise level brought by motor is within 10dB and 5dB respectively. The results lay an important foundation for further analysis of ocean ambient noise measured by underwater glider.

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Retrospective motion correction for Fast Spin Echo based on conditional GAN with entropy loss

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Journal of Physics: Conference Series 2021年第1期1848卷

作者： Yalei Chen Pingan Li Kewen Liu Qingjia Bao Zhao Li Xiaojun Li Information and Communication Engineering Wuhan University of Technology Wuhan Hubei 430070 China Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology 430070 Wuhan China Department of Chemical and Biological Physics Weizmann Institute of Science Rehovot Israel State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Center for Magnetic Resonance Wuhan Institute of Physics and Mathematics Innovation Academy for Precision Measurement Science and Technology 430071Wuhan China

We proposed a new end-to-end motion correction method based on conditional generative adversarial network (GAN) and minimum entropy of MRI images for Fast Spin Echo (FSE) sequence. The network contains an encoder-decoder generator to generate the motion-corrected images and a PatchGAN discriminator to classify an image as either real (motion-free) or fake(motion-corrected). Moreover, the image's entropy is set as one loss item in the cGAN's loss as the entropy increases monotonically with the motion amplitude, indicating that entropy is a good criterion for motion. The results show that the proposed method can effectively reduce the artifacts and obtain high-quality motion-corrected images from the motion-affected images in both pre-clinical and clinical datasets.

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Utilization of mems accelerometers in vibrodi-agnostics 25

Utilization of mems accelerometers in vibrodi-agnostics

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25th International Congress on Sound and Vibration 2018: Hiroshima Calling, ICSV 2018

作者： Doseděl, Martin Havránek, Zdeněk Beneš, Petr Krejčí, Jakub Central European Institute of Technology Brno University of Technology Faculty of Electrical Engineering and Communication Brno Czech Republic Brno University of Technology Department of Control and Instrumentation Brno Czech Republic

ISBN: (纸本)9781510868458

In the present time traditional piezoelectric accelerometers are mostly used in the industrial environment. Mechanical size and relatively higher price of the sensors can impede their mass application in the diagnostics of machines. In the past, MEMS sensors were inappropriate for small signals measurement due to their own, relatively high, output noise level. But the development of MEMS structures is improving. Main parameters, such as price, frequency range, dynamic range, but mainly ultralow noise density represent significant role in the potential mass usage of the MEMS accelerometers in the vi-brodiagnostics field. Ultralow noise MEMS accelerometers manufactured by Analog Devices, Colibrys and Silicon Designs were selected and output noise was measured. Rough data from accelerometer were re-scaled and integrated from acceleration to velocity domain and filtered – from wide-band range to ISO range. Based on the results, comparison with traditional piezoelectric industrial accelerometers was done. The noise of measured MEMS accelerometers is from 0.0029 mm/s to 0.022 mm/s, which is comparable to the piezo sensors noise level. MEMS sensors are useful for measuring of the machines under the conditions defined in standard ISO 10816. © 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling. All rights reserved.

关键词： Accelerometers

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School violence detection based on multi-sensor fusion and improved relief-F algorithms 1st

School violence detection based on multi-sensor fusion and i...

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1st EAI International Conference on Artificial Intelligence for communications and Networks, AICON 2019

作者： Ye, Liang Shi, Jifu Ferdinando, Hany Seppänen, Tapio Alasaarela, Esko Department of Information and Communication Engineering Harbin Institute of Technology No. 2 Yikuang Street Harbin150080 China Health and Wellness Measurement Research Group OPEM Unit University of Oulu Pentti Kaiteran katu 1 Oulu90014 Finland Department of Electrical Engineering Petra Christian University Siwalankerto 121-131 Surabaya60236 Indonesia Physiological Signal Analysis Team University of Oulu Pentti Kaiteran katu 1 Oulu90014 Finland

ISBN: (纸本)9783030229702

School bullying is a common social problem around the world, and school violence is considered to be the most harmful form of school bullying. This paper proposes a school violence detecting method based on multi-sensor fusion and improved Relief-F algorithms. Data are gathered with two movement sensors by role playing of school violence and daily-life activities. Altogether 9 kinds of activities are recorded. Time domain features and frequency domain features are extracted and filtered by an improved Relief-F algorithm. Then the authors build a two-level classifier. The first level is a Decision Tree classifier which separates the activity of jump from the others, and the second level is a Radial Basis Function neural network which classifies the remainder 8 kinds of activities. Finally a decision layer fusion algorithm combines the recognition results of the two sensors together. The average recognition accuracy of school violence reaches 84.4%, and that of daily-life reaches 97.3%. © ICST institute for Computer Sciences, Social Informatics and Telecommunications engineering 2019 Published by Springer Nature Switzerland AG 2019. All Rights Reserved.

关键词： Pattern recognition

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