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Altering the Residual Stress in High-Carbon Steel through Promoted Dislocation Movement and Accelerated Carbon Diffusion by Pulsed Electric Current

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Acta Metallurgica Sinica(English Letters) 2023年第9期36卷 1511-1522页

作者： Kun Yi Siqi Xiang Mengcheng Zhou Xinfang Zhang Furui Du School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China State Key Laboratory of Automatic Control Technology for Mining and Metallurgy Process Beijing102628China

Residual stress in high-carbon steel affects the dimensional accuracy, structural stability, and integrity of components. Although the evolution of residual stress under an electric field has received extensive attention, its elimination mechanism has not been fully clarified. In this study, it was found that the residual stress of high-carbon steel could be effectively relieved within a few minutes through the application of a low density pulse current. The difference between the current pulse treatment and traditional heat treatment in reducing residual stress is that the electric pulse provides additional Gibbs free energy for the system, which promotes dislocation annihilation and carbon atom diffusion to form carbides, thus reducing the free energy of the system. The electroplastic and thermal effects of the pulse current promoted the movement of dislocations under the electric field, thus eliminating the internal stress caused by dislocation entanglement. The precipitation of carbides reduced the carbon content of the steel matrix and lattice shrinkage, thereby reducing the residual tensile stress. Considering that a pulsed current has the advantages of small size, small power requirement, continuous output, and continuously controllable parameters, it has broad application prospects for eliminating residual stress.

关键词： Residual stress Pulsed electric current Carbide precipitation

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Detection of healthy and pathological heartbeat dynamics in ECG signals using multivariate recurrence networks with multiple scale factors

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Chinese Physics B 2023年第10期32卷 273-282页

作者：马璐陈梅辉何爱军程德强杨小冬 School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Suzhou Vocational and Technical College Suzhou 234000China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China

The electrocardiogram(ECG)is one of the physiological signals applied in medical clinics to determine health *** physiological complexity of the cardiac system is related to age,disease,*** the investigation of the effects of age and cardiovascular disease on the cardiac system,we then construct multivariate recurrence networks with multiple scale factors from multivariate time *** propose a new concept of cross-clustering coefficient entropy to construct a weighted network,and calculate the average weighted path length and the graph energy of the weighted network to quantitatively probe the topological *** obtained results suggest that these two network measures show distinct changes between different *** is because,with aging or cardiovascular disease,a reduction in the conductivity or structural changes in the myocardium of the heart contributes to a reduction in the complexity of the cardiac ***,the complexity of the cardiac system is *** that,the support vector machine(SVM)classifier is adopted to evaluate the performance of the proposed *** of 94.1%and 95.58%between healthy and myocardial infarction is achieved on two ***,this method can be adopted for the development of a noninvasive and low-cost clinical prognostic system to identify heart-related diseases and detect hidden state changes in the cardiac system.

关键词： electrocardiogram signals multivariate recurrence networks cross-clustering coefficient entropy multiscale analysis

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Scheduling Optimization of Flexible Job Shop Problem 7

Scheduling Optimization of Flexible Job Shop Problem

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7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Chan, Gu Di, Zou Shaanxi University of Science and Technology School of Electrical and Control Engineering Xi'an China

ISBN: (纸本)9798350334197

Flexible job shop scheduling (FJSP) is an important problem in manufacturing systems, and many researchers have used the non-dominated sorting genetic algorithm (NSGA-II) to solve this problem. However, NSGA-II has been criticized for its slow convergence speed and low search efficiency. To address these issues, this paper proposes an optimization algorithm that combines automata with NSGA-II. By using automata, the constraints and limitations of the job shop system can be accurately, intuitively described. By using a self-locking algorithm, the generated automata model is screened for better results, which can be the initial population for NSGA-II. Thus, convergence speed and solution quality are improved. The feasibility of the proposed algorithm is verified by simulating the MK04 example in the Brandimarte benchmark dataset. © 2023 IEEE.

关键词： Job shop scheduling

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Virtual Machining System of Reflow Welding Machine Based on Digital Twin 42

Virtual Machining System of Reflow Welding Machine Based on ...

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42nd Chinese control Conference, CCC 2023

作者： Guo, Rui Pan, Xuejun Zhang, Liyong Lu, Wei School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

This paper designs a virtual control system of reflow soldering based on digital twin and neural network. Aiming at the problems of high cost and low efficiency in production prediction of reflow soldering machine, low transparency and lack of model in operation management, this paper builds a virtual control system of reflow soldering based on neural network and digital twin technology using unity 3D, which can effectively solve these problems. Firstly, 3D virtual modeling of reflow soldering is carried out by using digital twin technology to realize the data mapping relationship between reflow soldering machine and virtual model. Then a neural network model of reflow soldering is constructed to predict the production temperature curve of reflow soldering machine. Finally, the neural network model is applied to the virtual control system of reflow soldering to realize the overall system development. The system can monitor the real-time production parameters in three-dimensional dynamic form and predict the welding temperature curve, which is of great significance to the intelligent reflow welding process of the enterprise. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Welding machines

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A Metro Cloud Platform Based on Real-Time Processing of Heterogeneous Concurrent Data 42

A Metro Cloud Platform Based on Real-Time Processing of Hete...

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42nd Chinese control Conference, CCC 2023

作者： Ren, Chengyuan Li, Zhuohan Zheng, Danchen Zhuang, Yan Shao, Cheng School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

With the rapid development of urban transportation, the metro has become a vital means for daily communication. However, during the operation of the metro, a large amount of operational data from various equipment is constantly generated and transmitted to the ground control center, leading to high bandwidth load and poor real-time processing performance of the ground monitoring system. Inspired by the idea of big data processing system, this paper proposes a metro cloud platform for processing large, concurrent, and heterogeneous data generated by metros. We first designed the software structure of the platform according to the overall requirements, including both front-end and back-end systems, and then divided them into several modules with different functions. We employed technologies such as Netty, Kafka, Redis, and TimescaleDB to efficiently handle and store the vast amounts of data generated by metros, and implemented an online playback feature for video stream captured by onboard cameras, which have been processed by deep learning models. Moreover, a data-sending simulator was designed for simulation experiments, and the experimental results verified the functionality and performance of the metro cloud platform. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Data visualization

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2D Human Pose Estimation with Residual Upsampling and Spatial Feature Enhancement 43

2D Human Pose Estimation with Residual Upsampling and Spatia...

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43rd Chinese control Conference, CCC 2024

作者： Li, Shanbin Zheng, Xishan South China University of Technology School of Automation Science and Engineering Guangzhou China Changji University School of Energy and Control Engineering Xinjiang China

ISBN: (纸本)9789887581581

Computer vision, which has been extensively used in intelligent monitoring, self-driving, medical assistance, sports analysis, and other fields, includes human pose estimation as a key component. Human pose estimation algorithms have been appearing nonstop in recent years, and as they get more complex and structured, it becomes harder to analyze and actually implement the algorithms. SBL network is surprisingly efficient for such a simple design. This study makes several modifications based on SBL to further enhance its performance. In order to fuse rich features from the feature extraction stage to the upsampling phase, we first introduce the residual upsampling module (RUSM). This guarantees that more detailed, high-resolution information can be utilized to upsampling features, significantly increasing the accuracy of joint recognition in the human body. Additionally, we present the spatial feature enhancement module (SFEM), which utilizes the spatial attention mechanism with the residual structure. It is employed to boost spatial features of the upsampling phase and further increase the detection precision of the network. Lastly, we conduct numerous experiments on the LSP dataset, which amply illustrates the enhanced functionality of the extra modules and the better performance of our suggested network. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Image enhancement

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Predictive Vehicle control at Intersections with Look-Ahead Driving Approach

Predictive Vehicle Control at Intersections with Look-Ahead ...

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2025 SICE International Symposium on control Systems, SICE ISCS 2025

作者： Magzhan, Atykhan Hossain, Md Delowar Bakibillah, A.S.M. Kamal, Md Abdus Samad Yamada, Kou Graduate School of Science and Technology Gunma University Kiryu Japan Institute of Science Tokyo Department of Systems and Control Engineering Tokyo Japan

ISBN: (纸本)9784907764852

This paper presents a look-ahead vehicle control scheme for efficient traffic management at signalized intersections. The proposed scheme predicts future driving states with a look-ahead approach as an extended adaptive cruise control (ACC) model. It maintains car-following behavior similar to human driving while predicting future states of traffic flow to minimize intersection clearing time and aggressive braking independently, similar to model predictive control (MPC) approaches. In contrast to MPC models that are computationally demanding and have limited practical applications due to real-time constraints, the proposed scheme uses a modified Intelligent Driver Model (IDM) with predictive adjustments. The efficiency of the control scheme is evaluated through simulations with multiple vehicles in intersection traffic scenarios, focusing on maintaining safe time headway within a traffic flow and ensuring efficient flows with higher intersection throughput. Comparative results indicate improvements in intersection clearance, human-like vehicle headway management, and enhanced traffic flow performance. © 2025 The Society of Instrument and control Engineers.

关键词： Adaptive cruise control

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Detection of EEG signals in normal and epileptic seizures with multiscale multifractal analysis approach via weighted horizontal visibility graph

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Chinese Physics B 2023年第11期32卷 401-407页

作者：马璐任彦霖何爱军程德强杨小冬 School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Suzhou Vocational and Technical College Suzhou 234000China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China

Electroencephalogram(EEG) signals contain important information about the regulation of brain system. Thus, automatic detection of epilepsy by analyzing the characteristics obtained from EEG signals has important research implications in the field of clinical medicine. In this paper, the horizontal visibility graph(HVG) algorithm is used to map multifractal EEG signals into complex networks. Then, we study the structure of the networks and explore the nonlinear dynamics properties of the EEG signals inherited from these networks. In order to better describe complex brain behaviors, we use the angle between two connected nodes as the edge weight of the network and construct the weighted horizontal visibility graph(WHVG). In our studies, fractality and multifractality of WHVG are innovatively used to analyze the structure of related networks. However, these methods only analyze the reconstructed dynamical system in general characterizations,they are not sufficient to describe the complex behavior and cannot provide a comprehensive picture of the system. To this effect, we propose an improved multiscale multifractal analysis(MMA) for network, which extends the description of the network dynamics features by focusing on the relationship between the multifractality and the measured scale-free ***, neural networks are applied to train the above-mentioned parameters for the classification and identification of three kinds of EEG signals, i.e., health, interictal phase, and ictal phase. By evaluating our experimental results, the classification accuracy is 99.0%, reflecting the effectiveness of the WHVG algorithm in extracting the potential dynamic characteristics of EEG signals.

关键词： epilepsy EEG signal horizontal visibility graph complex network

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Event-Triggered Iterative Learning for Constrained UAV Attitude control

Event-Triggered Iterative Learning for Constrained UAV Attit...

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2023 China Automation Congress, CAC 2023

作者： Liang, Chen Yang, Kaijun Ouyang, Lingcong School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an China

ISBN: (纸本)9798350303759

This paper addresses the attitude control of quadrotor unmanned aerial vehicles (UAVs) with state constraints. We propose an event-triggered iterative learning control (ILC) scheme for quadrotor UAVs. The scheme effectively handles both parameter and non-parameter uncertainties in the UAV system through iterative learning laws. Additionally, an event-triggering mechanism is incorporated into the ILC design to reduce the update frequency of the final control signals, thereby reducing the signal transmission burden and control costs of the system. A barrier Lyapunov function is adopted to design the attitude control of the UAVs with state constraints. The convergence of the tracking error is analyzed using a constructed barrier composite energy function, ensuring that the prescribed constraints are not violated at each iteration. Simulation results demonstrate that the proposed control scheme achieves accurate tracking performance and effectively alleviates the system burden, thereby verifying its effectiveness and feasibility. © 2023 IEEE.

关键词： Attitude control

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An Improved ORB Feature Point Extraction Algorithm based on Image Enhancement and Adaptive Threshold 7

An Improved ORB Feature Point Extraction Algorithm based on ...

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7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Jiang, Tao Xue, Yuchen Shaanxi University of Science & Technology School of Electrical Control Engineering Shaanxi China

ISBN: (纸本)9798350334197

In scenes with varying illumination, there can be poor quality of the captured images, resulting in feature points not being extracted or not being extracted in sufficient quantity when using the fixed-threshold ORB algorithm to extract feature points. To address this problem, an improved ORB feature point extraction algorithm is proposed. The image quality is improved using the adaptive gamma transform. According to the greyscale distribution of the image, the brightness change of the image is judged and the image is divided into three types of images: no obvious brightness change overall, brightness change overall and local brightness change. The feature point extraction is completed by adopting a global adaptive threshold or global adaptive threshold combined with a local adaptive threshold for different image types respectively. The experimental results show that the improved ORB feature point extraction algorithm can significantly increase the number of image feature points extracted with good robustness in lighting change scenes. © 2023 IEEE.

关键词： Image enhancement

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