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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Zhang, Guoqing Sun, Hongbo Liu, Xin Liu, Lei Yantai University School of Computer and Control Engineering Shandong China Shandong University Shandong China

ISBN: (纸本)9798350331684

Surface defect detection is important in the industrial field. Most factories use the difference method to solve the problem of defect detection. However, difference method can't solve misjudgments caused by shooting angle and location. In this paper, using the information entropy to solve the problem of the misjudgment for qualified products caused by product position and camera Angle. At the same time, 30 experiments were carried out to determine the threshold, and then 100 experiments were carried out to compare the accuracy of information entropy and difference methods, including the images of qualified products and unqualified products. Finally, the information entropy method is better than the difference method, and its detection accuracy is 97%. © 2023 IEEE.

关键词： Image processing

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Assessment and Enhancement of FRC of Power Systems Considering Thermal Power Dynamic Conditions

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1371-1383页

作者： Feng Hong Yalei Pang Weiming Ji Lu Liang Fang Fang Junhong Hao Jizhen Liu State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources and School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources School of Energy Power and Mechanical EngineeringNorth China Electric Power UniversityBeijing 102206China

Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power *** contrast,the proportion of traditional thermal power units decreases during the decarbonization transformation process,resulting in poor frequency *** paper aims to explore the potential of frequency regulation support,dynamic assessment,and capacity promotion of thermal power plants in the transition *** the dynamic characteristics of the main steam working fluid under different working conditions,a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree *** real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid.A dynamic adaptive modification for primary frequency control(PFC)of power systems,including wind power and thermal power,is proposed and *** power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio,and the frequency modulation capability of the system is improved by more than 11%under extreme ***,through the Monte Carlo simulation of unit states of the system under various working conditions,the promotion of the frequency regulation capacity with high wind power penetration(WPP)is verified.

关键词： Dynamic evaluation frequency regulation power system predictive modeling wind penetration

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Attention Based Temporal Convolutional Networks for Short-Term Wind Power Forecasting 19th

Attention Based Temporal Convolutional Networks for Short-T...

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19th Chinese Intelligent Systems Conference, CISC 2023

作者： Li, Qingwei Hou, Guolian Yu, Qi School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819968855

As wind is characterized by its inherent stochasticity and volatility, accurate wind power forecasting has become increasingly crucial for efficient operation of the power system. In this paper, we propose a deep learning method combining temporal convolutional networks (TCNs) and attention mechanism for wind power forecasting. Temporal convolutional networks are employed for extracting features, and then attention mechanism is utilized to concentrate on the important timesteps. In data preprocessing part, we adopt sliding windows approach to generate training samples from the normalized data, which facilitates processing and learning for the model. The comparison results demonstrate that the proposed model outperforms the comparison models, indicating the effectiveness of the proposed model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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Robust Car-Following control of Connected and Autonomous Vehicles: A Stochastic Model Predictive control Approach

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Zhang, Peiyu Tian, Daxin Zhou, Jianshan Chang, Mai Duan, Xuting Zhao, Dezong Cao, Dongpu Leung, Vicor C.M. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China James Watt School of Engineering University of Glasgow Glasgow U.K Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Computer Science and Software Engineering Shenzhen University Shenzhen China

Vehicle platooning has attracted growing attention for its potential to enhance traffic capacity and road safety. This paper proposes an innovative distributed Stochastic Model Predictive control (SMPC) for a vehicle platoon system to enhance the robustness and safety of the vehicles in uncertain traffic environments. In particular, considering the similarity between the acceleration or deceleration behaviour of neighbouring vehicles and the spring-scale properties, we use a two-mass spring system for the first time to construct an uncertain dynamic model of a formation system. In the presence of uncertain perturbations with known distributional attributes (expectation, variance), we propose an objective function in the form of expectation along with probabilistic chance constraints. Subsequently, a state feedback control mechanism is devised accordingly. Under the cumulative probability distribution function of stochastic perturbations, we theoretically derive a computationally tractable equivalent of the SMPC model. Finally, simulation experiments are designed to validate the control performance of the SMPC platoon controllers, along with an analysis of the stability performance under varying probabilities. The experimental findings demonstrate that the model can be efficiently solved in real-time with appropriately chosen prediction horizon lengths, ensuring robust and safe longitudinal vehicle formation control. IEEE

关键词： Random processes

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Intelligent Predetermination of Generator Tripping Scheme: Knowledge Fusion-based Deep Reinforcement Learning Framework

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 66-75页

作者： Lingkang Zeng Wei Yao Ze Hu Hang Shuai Zhouping Li Jinyu Wen Shijie Cheng State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronics EngineeringHuazhong University of Science and TechnologyWuhan 430074China Dispatching and Control Center Central China Branch of State Grid Corporation of ChinaWuhan 430077China. Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN 37996USA

Generator tripping scheme(GTS)is the most commonly used scheme to prevent power systems from losing safety and ***,GTS is composed of offline predetermination and real-time scenario ***,it is extremely time-consuming and labor-intensive for manual predetermination for a large-scale modern power *** improve efficiency of predetermination,this paper proposes a framework of knowledge fusion-based deep reinforcement learning(KF-DRL)for intelligent predetermination of ***,the Markov Decision Process(MDP)for GTS problem is formulated based on transient instability ***,linear action space is developed to reduce dimensionality of action space for multiple controllable ***,KF-DRL leverages domain knowledge about GTS to mask invalid actions during the decision-making *** can enhance the efficiency and learning ***,the graph convolutional network(GCN)is introduced to the policy network for enhanced learning *** simulation results obtained on New England power system demonstrate superiority of the proposed KF-DRL framework for GTS over the purely data-driven DRL method.

关键词： Deep reinforcement learning generator tripping scheme graph convolutional network invalid action masking knowledgefusion

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Development of High Accurate Family-use Digital Refractometer Based on CMOS

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Instrumentation 2023年第3期10卷 12-22页

作者： WANG Zhenxing JIA Zhenyuan School of Computer and Information Engineering Shanghai Polytechnic UniversityShanghai 201209China School of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic UniversityShanghai 201209China

This study aims to develop a low-cost refractometer for measuring the sucrose content of fruit juice,which is an important factor affecting human *** laboratory-grade refractometers are expensive and unsuitable for personal use,existing low-cost commercial options lack stability and *** address this gap,we propose a refractometer that replaces the expensive CCD sensor and light source with a conventional LED and a reasonably priced CMOS *** analyzing the output waveform pattern of the CMOS sensor,we achieve high precision with a personal-use-appropriate accuracy of 0.1%.We tested the proposed refractometer by conducting 100 repeated measurements on various fruit juice samples,and the results demonstrate its reliability and *** on a 48 MHz ARM processor,the algorithm can acquire data within 0.2 *** low-cost refractometer is suitable for personal health management and small-scale production,providing an affordable and reliable method for measuring sucrose concentration in fruit *** improves upon the existing low-cost options by offering better stability and *** accessible tool has potential applications in optimizing the sucrose content of fruit juice for better health and quality control.

关键词： Brix Meter High-precision Refractometer Oversampling 1D CMOS Sensor

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Transmission Line Fault Diagnosis Method Based on SDA-ISSA-XGBoost under Meteorological Factors 3

Transmission Line Fault Diagnosis Method Based on SDA-ISSA-X...

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2023 3rd International Conference on Electrical engineering and computer Technology, ICEECT 2023

作者： Zhang, Kun North China Electric Power University School of Control and Computer Engineering Beijing102206 China

Transmission lines are directly exposed to the natural environment and are prone to failure due to meteorological factors. A novel approach for diagnosing transmission line faults under various meteorological conditions has been introduced. This method, known as SDA-ISSA-XGBoost, combines the power of Stacked Denoising Autoencoder (SDA), an improved Sparrow Search Algorithm (ISSA) enhanced with chaotic mapping sequences, adaptive weights, improved iterative local search, and a random differential mutation strategy, and eXtreme Gradient Boosting (XGBoost). The process begins with SDA, which extracts essential features from the initial meteorological data. Subsequently, ISSA is applied to optimize the parameters of the XGBoost model. This results in the ISSA-XGBoost fault diagnosis model. The performance of this model is compared to PSO-XGBoost and SSA-XGBoost. The experimental findings demonstrate that the ISSA-XGBoost model achieves an impressive fault diagnosis accuracy of 94.39%, surpassing both PSO-XGBoost and SSA-XGBoost by 6.54% and 3.74%, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Failure analysis

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A Machine Vision-based Deep Learning Method in Hemodialysis Filter Defects Detection 26

A Machine Vision-based Deep Learning Method in Hemodialysis ...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Liu, Xin Sun, Hongbo Zhang, Guoqing Liu, Lei Yantai University School of Computer and Control Engineering Shandong China Shandong University Shandong China

ISBN: (纸本)9798350331684

Hemodialysis filters are widely used in the treatment of kidney diseases. In order to reduce the occurrence of medical accidents, they need to go through a strict inspection process before being put into use to avoid defective products from entering the market, so it is crucial to locate and classify hemodialysis filters defects. In this paper, a deep learning method based on machine vision is proposed to solve the problem that the background of the inspected products is very similar to the defects and difficult to distinguish them. First, image denoising is performed, then the center of the product is located and the circle is expanded into a rectangle, the edge is extracted using a firstorder difference operator to distinguish the background from the defects, and finally the image after the extended channel is provided to the lightweight U-Net for training by online sample sampling. The test results show that the proposed method have achieved 0.78 mean IoU, 4.67% false detection rate and 0.67% missing rate on the hemodialysis filter dataset, which demonstrates the effectiveness of the proposed method. © 2023 IEEE.

关键词： Defects

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Ethereum Eclipse Attack Detection Based on Multi-Head Attention Mechanism with Bi-LSTM

Ethereum Eclipse Attack Detection Based on Multi-Head Attent...

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2023 International Conference on Intelligent Communication and Networking, ICN 2023

作者： Cheng, Na Liang, Yin Li, Shike Li, Jianbin School of Control and Computer Engineering North China Electric Power University BeiJing102206 China

ISBN: (纸本)9798350357677

The rapid development of blockchain technology and the rise of Ethereum as its representative platform has triggered a wide range of research and applications. However, this development is also accompanied by new security challenges, among which the Eclipse attack is one of the significant security threats currently facing Ethereum networks. In response to these challenges, we propose an Ethereum Eclipse attack detection method based on a multi-head attention mechanism with Bi-LSTM. This approach utilizes the Bi-LSTM model and multi-head attention mechanism to process time-series data, capturing and focusing on the features most relevant to the Eclipse attack for accurate identification. Additionally, we employ PCA and UMAP dimensionality reduction techniques in data preprocessing to enhance processing efficiency. Experimental results demonstrate that this method distinguishes regular traffic from attack traffic more accurately. Compared to the existing random forest method, our detection approach based on a multi-head attention mechanism with Bi-LSTM achieves a higher detection rate and lower false alarm rate, highlighting its effectiveness in addressing Ethereum network security. © 2023 IEEE.

关键词： Blockchain

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Adaptive dynamic surface control for quadrotor-slung load transportation system with uncertainties

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Science China(Technological Sciences) 2023年第10期66卷 2917-2929页

作者： DING Feng HUANG Jian SUN Chong AI Yong XU WenXia YANG ChenGuang School of Computer Science South-Central Minzu UniversityWuhan 430074China Key Laboratory of Ministryof EducationforImage Processing and Intelligent ControlHubei Key Laboratoryof Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Engineering Wuhan Institute of TechnologyWuhan 430205China Key Laboratory of Ministry of Education for Autonomous Systems and Networked Control Guangdong Engineering Technology Research Center of Control of Intelligent SystemsCollege of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Quadrotors play a significant role in our lives and are transforming our *** cable-suspended loads is an unavoidable quadrotor application trend and a hot research topic in the control ***,the load swing and unpredictability pose significant challenges to the quadrotor's *** this paper,an anti-swing controller with an inner-outer control strategy for the quadrotor-slung load transportation system is *** facilitate the controller design,the outer position dynamics are restructured in the form of ***,a virtual controller is created to force the underactuated states to the dynamic surface to ensure the position subsystem's *** improve robustness,an adaptive law is used to eliminate the effects of uncertain cable ***,a dynamic surface controller for the inner attitude subsystem is presented to drive the actual force to the virtual *** is demonstrated that the control strategy can stabilize the quadrotor despite mass and cable length *** results are provided to demonstrate the efficacy and durability of the proposed method.

关键词： quadrotor-slung load transportation system dynamic surface control adaptive law cascade system model uncertainties

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