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第41届中国控制会议

作者： Xiaoyu Qu Tao Liu Yang Wu Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Institute of Advanced Control Technology Dalian University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

For in-situ measurement of biochemical process variables such as the multi-component concentrations of a fermentation process via near-infrared spectroscopy,an improved spectral calibration model building method is proposed in this paper,based on the support vector regression(SVR) in combination with a grey wolf optimizer for parameter *** address the nonlinear properties and high-dimensional problem of infrared spectral variables,the Gaussian kernel function is adopted to establish an SVR based spectral calibration model so as to improve fitting accuracy with respect to the training ***,a grey wolf optimization algorithm is given to determine the model parameters for obtaining good prediction *** application to a fluidized bed drying(FBD) process for prediction of moisture content and another lactic acid fermentation process for multi-component prediction are performed,well demonstrating the effectiveness and superiority of the proposed modelling method over the traditional partial least-squares modeling algorithms.

关键词： spectral calibration model near-infrared spectroscopy in-situ measurement support vector regression(SVR) grey wolf optimizer multi-component prediction

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Wireless power transmission system with CC and CV output based on hybrid LCC-S/P topology 5

Wireless power transmission system with CC and CV output bas...

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5th International Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2023

作者： Li, Kun Gong, Zheng Meng, Jiaheng Liu, Qing Tianjin University of Technology Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin China Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China

ISBN: (纸本)9798350328660

Wireless Power Transfer (WPT) technology provides a convenient and efficient power supply solution for mobile devices. The utilization of constant current (CC) and constant voltage (CV) control in WPT systems proves valuable for charging battery applications. This paper presents a novel WPT system with CC and CV output characteristics, employing a switching topology. Specifically, the LCC-S and LCC-P topologies are applied and rigorously simulated. The proposed MCR-WPT system's output characteristics in both CC and CV modes are meticulously validated using Saber software. The simulation results distinctly demonstrate the system's capability to achieve CC and CV outputs within a varying load resistance range of 5Ω to 30Ω, thus conclusively establishing the efficacy of the topology switching technology. © 2023 IEEE.

关键词： Topology

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Time-synchronous-averaging-spectrum based on super-resolution analysis and application in bearing fault signal identification

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2024年第7期25卷 573-585页

作者： Zengle REN Yuan WANG Huiyue TANG Xin'an CHEN Wei FENG Guangdong Provincial Key Laboratory of Construction Robotics and Intelligent Construction Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Shenzhen EBORAIL Technology Co. Ltd.Shenzhen518038China National Supercomputing Center in Shenzhen Shenzhen518055China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China University of Chinese Academy of Sciences Beijing100190China Shenzhen University of Advanced Technology Shenzhen518107China

Time-synchronous-averaging(TSA)is based on the idea of denoising by averaging,and it extracts the periodic components of a quasiperiodic signal and keeps the extracted waveform *** paper studies the mathematical properties of TSA,where three propositions are given to reveal the nature of *** paper also proposes a TSA-spectrum based on super-resolution analysis and it decomposes a signal without using any base *** contrast to discrete Fourier transform spectrum(DFT-spectrum),which is a spectrum in frequency domain,TSA-spectrum is a period-based spectrum,which can present more details of the cross effects between different periodic components of a quasiperiodic ***,a case study is carried out using bearing fault analysis to illustrate the performance of TSA-spectrum,where the rotation speed fluctuation of the shaft is estimated,which is about 0.12 ms *** extracted fault signals are presented and some insights are *** believe that this paper can provide new motivation for TSA-spectrum to be widely used in applications involving quasiperiodic signal processing(QSP).

关键词： Time-synchronous-averaging(TSA) Spectrum Quasiperiodic signal processing(QSP) Super-resolution analysis Bearingfaultdetection

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Research on the Influencing Factors and Crime Prediction of Drug Crimes Based on Decision Tree Algorithm 5

Research on the Influencing Factors and Crime Prediction of ...

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5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Wu, Shaobing Wang, Changmei Institute of Information Security Yunnan Police College Yunnan Police College Key Laboratory of Intelligent Drug Control Kunming China Yunnan Normal University Educ. Ministry Key Laboratory of Advanced Technology and Preparation for Renewable Energy Materials Kunming China

ISBN: (纸本)9798331528911

This research aims to design and develop a decision tree model to achieve drug crime prediction in border ethnic minority areas. This study will build on previous research by examining the extent to which four different types of factors - occupation, permanent population, age, and education level - can explain drug crimes in border ethnic minority areas in 2014 and 2021. The data comes from a sample of 1,856 drug crimes. This study uses the decision tree method to reveal that drug crimes are related to occupation, permanent population, age, and education level, while ethnic identity in border ethnic minority areas is not the only factor related to drug crimes. These results show that the new framework model introduced in this study can better explain drug crimes. The research findings have important practical implications, as they show that targeting these four factors in anti-drug crime policies is crucial. © 2024 IEEE.

关键词： Prediction models

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Finite-Time Synchronization of Flux-controlled Complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

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Self-powered sensor based on compressible ionic gel electrolyte for simultaneous determination of temperature and pressure

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InfoMat 2024年第7期6卷 62-75页

作者： Junjie Zou Yanan Ma Chenxu Liu Yimei Xie Xingyao Dai Xinhui Li Shuxuan Li Shaohui Peng Yang Yue Shuo Wang Ce-Wen Nan Xin Zhang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center of Smart Materials and Devices&International School of Materials Science and EngineeringWuhan University of TechnologyWuhanthe People's Republic of China Hubei Key Laboratory of Energy Storage and Power Battery School of MathematicsPhysics and Optoelectronic EngineeringHubei University of Automotive TechnologyShiyanthe People's Republic of China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information TechnologyAnhui UniversityHefeithe People's Republic of China State Key Lab of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijingthe People's Republic of China

The simultaneous detection of multiple stimuli,such as pressure and temperature,has long been a persistent challenge for developing electronic skin(eskin)to emulate the functionality of human ***,the demand for integrated power supply units is an additional pressing concern to achieve its lightweightness and ***,we propose a self-powered dual temperature–pressure(SPDM)sensor,which utilizes a compressible ionic gel electrolyte driven by the potential difference between MXene and Al *** SPDM sensor exhibits a rapid and timely response to changes in pressure-induced deformation,while exhibiting a slow and hysteretic response to temperature *** distinct response characteristics enable the differentiation of current signals generated by different stimuli through machine learning,resulting in an impressive accuracy rate of 99.1%.Furthermore,the developed SPDM sensor exhibits a wide pressure detection range of 0–800 kPa and a broad temperature detection range of 5–75C,encompassing the environmental conditions encountered in daily human *** dual-mode coupled strategy by machine learning provides an effective approach for temperature and pressure detection and discrimination,showcasing its potential applications in wearable electronics,intelligent robots,human–machine interactions,and so on.

关键词： e-skin gel electrolyte machine learning self-powered dual-mode sensor

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Design and vibration characteristics of sandwich constrained damping gasket for diaphragm air pump 8

Design and vibration characteristics of sandwich constrained...

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2023 8th International Seminar on Computer Technology, Mechanical and Electrical Engineering, ISCME 2023

作者： Hao, Yukai Chen, Wei Wang, Wei Liu, Zhien Zhang, Dashuai Hu, Yongbo Hubei Key Laboratory of Advanced Technology for Automotive Components Wuhan University of Technology Hubei Wuhan430070 China Hubei Collaborative Innovation Center for Automotive Components Technology Hubei Wuhan430070 China School of Automobile Engineering Wuhan University of Technology Hubei Wuhan430070 China Hubei Engineering Technology Center for New Energy and Intelligent Connected Vehicles Wuhan430070 China

There are certain problems of vibration reduction and isolation relevant to the working stability of diaphragm air pumps. To make the diaphragm air pump meet the use requirements, a sandwich-constrained damping gasket is designed and prepared in this paper. The research focuses on examining the impact of varying damping layer thickness on the efficacy of damping gaskets in reducing and isolating vibrations. Meanwhile, with the increase of the damping layer thickness, the total vibration severity of the diaphragm air pump body continues to increase, indicating a weakened performance of vibration reduction, while the vibration isolation performance is gradually improved. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Damping

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Graphene and boron nitride foams for smart functional applications

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SmartMat 2023年第4期4卷 59-84页

作者： Chiwei Xu Jinjue Zeng Yue Wang Xiangfen Jiang Xuebin Wang National Laboratory of Solid State Microstructures(NLSSM) Jiangsu Key Laboratory of Artificial Functional MaterialsCollaborative Innovation Center of Advanced MicrostructuresCollege of Engineering and Applied SciencesNanjing UniversityNanjingChina State Key Laboratory of Mechanics and Control of Mechanical Structures Key Laboratory for Intelligent Nano Materials and Devices of the Ministry of EducationCollege of Material Science and EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina

Graphene and boron nitride(BN)foams,as two types of three-dimensional(3D)nanomaterials consisting of two-dimensional(2D)nanosheets,can inherit a series of excellent properties of the 2D *** internal 3D network can prevent aggregation or restacking between isolated graphene or BN nanosheets,and provide a highway for phonon/electron ***,the interconnected porous structure creates a continual channel for the mass exchange of exotic *** light-element graphene and BN foams can thus possess the characteristics of low density,high porosity,high surface area,and excellent mechanical,thermal,and electrical *** from these advantages,they show a wide range of *** usual synthesis methods and the recent functional applications of graphene and BN foams are reviewed herein,including their applications as supporting materials,elastic materials,acoustic shielding materials,thermal interface materials,electromagnetic shielding materials,adsorption materials,electrocatalysis and thermal catalyses materials,electrochemical energy storage,and thermal energy storage *** challenges and outlooks are additionally discussed.

关键词： adsorption boron nitride foam electrochemistry graphene foam thermal management

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Gravitational wave search by time-scale-recursive denoising and matched filtering

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Science China(Physics,Mechanics & Astronomy) 2024年第12期67卷 166-182页

作者： Cunliang Ma Chenyang Ma Zhoujian Cao Mingzhen Jia School of Information Engineering Jiangxi University of Science and TechnologyGanzhou341000China Institute for Frontiers in Astronomy and Astrophysics Beijing Normal UniversityBeijing102206China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced StudyUCASHangzhou310024China Jiangxi Provincial Key Laboratory of Multidimensional Intelligent Perception and Control Ganzhou341000China

In our previous work [Physical Review D,2024,109(4):043009],we introduced MSNRnet,a framework integrating deep learning and matched filtering methods for gravitational wave(GW) *** with end-to-end classification methods,MSNRnet is physically *** denoising models and astrophysical discrimination models corresponding to different parameter space were operated independently for the template prediction and *** the MSNRnet has a lot of computational *** this study,we propose a new framework for template prediction,which significantly improves our previous *** new framework consists of the recursive application of denoising models and waveform classification models,which solve the problem of computational *** waveform classification network categorizes the denoised output based on the signal's time *** enhance the denoising performance for long-time-scale data,we upgrade the denoising model by incorporating Transformer and ResNet ***,we introduce a novel training approach that allows for the simultaneous training of the denoising network and waveform classification network,eliminating the need for manual annotation of the waveform dataset required in our previous ***-data analysis results demonstrate that our new method decreases the false alarm rate by approximately 25%,boosts the detection rate by roughly 5%,and slashes the computational cost by around 90%.The new method holds potential for future application in online GW data processing.

关键词： gravitational wave matched filtering deep learning

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Motion Analysis and Experiment of Sheet Small Magnetron Soft Robot 8

Motion Analysis and Experiment of Sheet Small Magnetron Soft...

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8th International Conference on control Science and Systems Engineering, ICCSSE 2022

作者： Ma, Haoyun Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Hubei Wuhan430 074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Wuhan430074 China

ISBN: (纸本)9781665484138

In the past, most robots used rigid structures. With the development of intelligent materials, more and more soft materials began to be used in the manufacture of robots. Magnetic-driven soft robot is one of its important branches. Because of the flexibility of magnetoelastic composite robots and the harmlessness of magnetic field to human body, a magnetically-controlled soft robot has broad application prospects in medical fields such as disease diagnosis and treatment in human body. A small lamellate magnetic soft robot is designed in this paper with the advantages of small volume, light weight, high deformation, fast and simple manufacture. And it can be driven without wire under the control of the magnetic field formed by the three-dimensional Helmholtz coil. The robot can walk and crawl on the surface of magnetically-controlled. The motion characteristics of the magnetic soft robot such as crawling step length and bending height are analyzed. The data are collected through experiments to analyze the relationship between the control signal and the motion characteristics. © 2022 IEEE.

关键词： Motion analysis

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