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Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization

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Journal of Systems Science and Systems engineering 2024年第1期33卷 106-128页

作者： Wei Ba Baojun Chen Qi Li School of Automation and Electrical Engineering Dalian Jiaotong UniversityDalian116028China Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian116023China

Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or ***,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation *** order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this *** first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is ***,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function ***,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.24%higher than that of TOPSIS-GCA,and 6.86%higher than that of *** proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.

关键词： Data quality comprehensive evaluation particle swarm optimization grey correlation analysis traffic flow data

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MPC-Based Change Management of Supply Chain Under Disruption Risks:The Case of Battery Industry

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1896-1898页

作者： Yi Yang Chen Peng School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China IEEE

Dear Editor,The health management of battery supply chain(SC)is vital to battery-related *** letter focuses on the study of health management of battery SC under ***,a discrete-time model of battery SC is developed based on the actual industrial ***,a model predictive control-based change management(MPCCM)strategy is proposed to ensure stable manufacturing of ***,the effects of disruption are also considered in terms of the actual ***,the validity of the proposed strategy is verified by a case study in Dongsheng Electronics Co.,Ltd.

关键词： battery Battery Supply

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Friction-induced ultrafast charge transfer in van der Waals heterostructures

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Nano Research 2025年第3期18卷 429-435页

作者： Chong Wang Rui Han Yutang Wang Shihong Chen Haowen Xu Shuchun Huang Zejun Sun Huixian Liu Jianbin Luo Dameng Liu Huan Liu State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China

van der Waals heterostructures stacked by transition metal dichalcogenides and graphene provide a new opportunity for exploring ***,the further reduction of friction is limited by the unavoidable charge transfer in the *** dynamics of charge transfer occur at picosecond time scale,which cannot be detected by traditional friction instruments,making the friction mechanism of charge transfer ***,we investigate friction-induced charge transfer in WS_(2)/graphene heterostructures with ultrafast friction energy dissipation detecting *** observed friction exhibits a strong linear relationship with the dissipation rate of interlayer charge *** modulating the band structure of heterostructures,the dissipation rate of interlayer charge transfer can be efficiently tuned from 0.72 to 0.17 ps^(−1),resulting in a~35%reduction in *** work gives the direct explanation of friction-induced charge transfer,which enables the high-performance micro-electro-mechanical systems and new insight into the origin of friction from the perspective of ultrafast electron dynamics.

关键词： friction energy dissipation charge transfer ultrafast spectroscopy heterostructures

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Numerical simulation and prediction of aerodynamic noise of high-speed trains

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Noise and Vibration Worldwide 2024年第1-2期55卷 16-32页

作者： Liu, Yanong Zhang, Jun Yi, Sitong School of Rolling Stock Engineering Dalian Jiaotong University Dalian China School of Automation and Electrical Engineering Dalian Jiaotong University Dalian China

In order to improve the efficiency of high-speed train aerodynamic noise analysis and provide a feasible method for aerodynamic noise prediction, the aerodynamic noise and its influencing factors are analyzed from the perspective of the total energy (sound power) radiated to the far field per unit time by the aerodynamic fundamental noise sources (monopole, dipole and quadrupole sources). A full-scale and a 1:8 scale-down computational fluid dynamics model of a high-speed train are established. The far-field sound pressure level at several receivers and velocities is calculated by using the transient large eddy simulation and the FW-H equation. The numerical simulation results are used to predict the aerodynamic noise under specified working conditions. The research work can achieve the prediction of aerodynamic noise at other velocities using noise data at known velocities on the same noise source case, as well as the prediction of aerodynamic noise of full-scale model using data of scale-down model, and is applicable to either bogies as local noise sources or the complete vehicle as a noise source. The maximum error between the prediction and simulation result is 0.33 dBA under various working conditions, which meets the engineering calculation requirements. © The Author(s) 2023.

关键词： Large eddy simulation

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Identification algorithm of low-count energy spectra under short-duration measurement based on heterogeneous sample transfer

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Nuclear Science and Techniques 2025年第3期36卷 12-26页

作者： Hao-Lin Liu Hai-Bo Ji Jiang-Mei Zhang Jing Lu School of Information Engineering Southwest University of Science and TechnologyMianyang 621010China Department of Automation University of Science and Technology of ChinaHefei 230026China Fundamental Science on Nuclear Wastes and Environment Safety Laboratory Southwest University of Science and TechnologyMianyang 621010China School of Automation and Information Engineering Sichuan University of Science and EngineeringZigong 643000China

In scenarios such as vehicle radiation monitoring and unmanned aerial vehicle radiation detection,rapid measurements using a NaI(Tl)detector often result in low photon counts,weak characteristic peaks,and significant statistical *** issues can lead to potential failures in peak-searching-based identification *** address the low precision associated with short-duration measurements of radionuclides,this paper proposes an identification algorithm that leverages heterogeneous spectral transfer to develop a low-count energy spectral identification *** experiments demonstrated that transferring samples from 26 classes of simulated heterogeneous gamma spectra aids in creating a reliable model for measured gamma *** only 10%of target domain samples used for training,the accuracy on real low-count spectral samples was 95.56%.This performance shows a significant improvement over widely employed full-spectrum analysis methods trained on target domain *** proposed method also exhibits strong generalization capabilities,effectively mitigating overfitting issues in low-count energy spectral classification under short-duration measurements.

关键词： Radionuclide identification Low-count Gamma energy spectral analysis Heterogeneous Transfer learning

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Review of condition monitoring and defect inspection methods for composited cable terminals

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High Voltage 2023年第3期8卷 431-444页

作者： Shuaibing Li Binglei Cao Jin Li Yi Cui Yongqiang Kang Guangning Wu School of New Energy and Power Engineering Lanzhou Jiaotong UniversityLanzhouChina School of Electrical Engineering and Automation Tianjin UniversityTianjinChina School of Engineering University of Southern QueenslandBrisbaneAustralia School of Electrical Engineering Southwest Jiaotong UniversityChengduChina

Composited cable terminals are critical for reliable power delivery of traditional and traction power supply *** its operation,the cable terminal continually undergoes complex circumstances where humidity,temperature,field strength,mechanical stress and other factors continuously change at different *** extreme cases,defects or even failures may occur in the cable terminals,leading to catastrophic *** makes the condition monitoring and defect detection of composited cable terminals become an imperative need for the power ***“state-of-the-art”technology of cable terminal condition assessment is focussed and a systematic review of the current research progress of cable terminal condition assessment from the operation circumstances to failure mechanisms is *** covers both online/offline condition monitoring methods and defects detection *** addition,challenges and future research directions for cable terminal condition assessment are also *** is concluded that the non-destructive and non-intrusive methods like terahertz imaging and ultrasonic testing,and multi-source information fusion methods as well as the digital twin technology have been gaining popularity for cable terminal defect *** is expected the presented work can provide a global field of vision for further advancement of both scholars and industrial engineers in this field.

关键词： defect condition composite

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Strong-Robustness Sliding Mode Torque Observer with Frequency Adaptive Filter Integrated for PMSMs

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IEEE Transactions on Power Electronics 2025年第8期40卷 11206-11217页

作者： Sun, Junhang Wang, Yalin Cheng, He Gong, Chao Yi, Lizhi Liu, Chenliang Central South University School of Automation Changsha410083 China China University of Mining and Technology School of Electrical Engineering Xuzhou221116 China Northwestern Polytechnical University School of Automation Xian710072 China Hunan Vocational College of Engineering Department of Information Engineering Changsha410151 China

Accurate estimation of load torque is critical for optimizing the control performance of permanent-magnet synchronous motor (PMSM) drives. This paper first establishes a mathematical model of the PMSM using coordinate transformation theory. Then, a non-singular terminal sliding mode load torque observer (NTSMLO) is developed to precisely estimate load torque during motor operation, taking advantage of the non-singular terminal sliding mode to achieve rapid response times and minimize chattering effects. However, traditional low-pass filters have problems with phase distortion and low roll-off rates, which limits their adaptability in dealing with external disturbances and time-varying parameters. To improve observation accuracy and enhance robustness, a frequency adaptive observer (FAO) is integrated into the NTSMLO, forming the adaptive non-singular terminal sliding mode load torque observer. Finally, the effectiveness of the proposed observer is validated through numerical simulations and experimental tests. Experimental results demonstrate significant improvements in both speed and parameter robustness over traditional sliding mode observers. © 1986-2012 IEEE.

关键词： Permanent magnets

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Modeling Method of the Calculation Model of Frequency-Conversion Magnetic Acceleration Noise of the Space Inertial Sensors

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IEEE Sensors Journal 2025年第11期25卷 19367-19375页

作者： Li, Pengxuan Wang, Lei Zhang, Xiaoyuan Wang, Jing Sun, Zhiyin Li, Liyi Harbin Institute of Technology School of Instrumentation Science and Engineering Harbin150001 China Harbin Institute of Technology School of Electrical Engineering and Automation Harbin150001 China

The disturbing force exerted by the magnetic field on the test mass (TM) constitutes a significant source of the acceleration noise in space inertial sensors. The frequency-conversion magnetic acceleration noise (FCMAN) induced by the frequency-conversion effect and falling into the target frequency band is an indispensable part of the noise index system. Currently, the formation mechanism of this noise has been clarified, but the research on the calculation model of it is not in-depth enough. The existing calculation model is established for a specific TM, and it is not universal and not suitable for the evaluation within the entire target frequency band. In this study, by integrating the analytical method and the Finite Element Method (FEM), a calculation model for the FCMAN is constructed on the basis of the frequency-domain circular convolution theorem. Building upon the modeling process, a generalized method for formulating the calculation model of the FCMAN is proposed and experimentally validated. Moreover, it holds significant potential for application in the real-time evaluation of the FCMAN during future on-orbit experiments. © 2001-2012 IEEE.

关键词： Frequency domain analysis

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Progress in Fabric Defect Detection Based on Machine Learning

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Journal of Shanghai Jiaotong University (Science) 2025年 1-19页

作者： Wu, Ying Li, Donghui Guo, Peiyao Liu, Yanping School of Electrical Automation and Information Engineering Tianjin University Tianjin300072 China School of Fashion Design & Engineering Zhejiang University of Technology Hangzhou310018 China

This paper presents a comprehensive review of the latest advancements in fabric defect detection leveraging machine learning techniques. It introduces the characteristics of textile defects and public datasets, and encapsulates the challenges encountered in defect detection. A total of 2 000 references spanning diverse time periods are utilized to cluster keywords, revealing that machine learning and deep learning have emerged as the top two. By employing the systematic literature review methodology, it explores the research question, search progress, inclusion and exclusion criteria, and eligibility standards on the basis of the two keywords (machine learning and deep learning). Machine learning algorithms are classified into traditional machine learning and deep learning. The selected references are systematically subdivided into supervised, unsupervised, and semisupervised methods in accordance with the labeled dataset. A thorough analysis of classical network architectures is conducted using public datasets and other datasets, and each network type is accompanied with illustrative examples. The methods are further evaluated on the basis of key metrics in terms of detection success rate, datasets used, detection methodologies, time efficiency, and hardware. This comprehensive evaluation highlights the strengths and limitations of machine learning, particularly deep learning, in textile defect detection. Potential future developments and research directions in this field are explored, offering valuable insights for researchers and engineers working in textile defect detection. © Shanghai Jiao Tong University 2025.

关键词： Deep learning

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Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

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Science China(Technological Sciences) 2024年第1期67卷 209-220页

作者： ZHU GuoLiang LIU KeXin GU HaiBo LÜJinHu School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100094China

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear *** achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system *** proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for *** proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno *** analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

关键词： formation control neural network adaptive control event-triggered communication multi-agent systems

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