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An improved neural network model for battery smarter state-of-charge estimation of energy-transportation system

Green Energy and Intelligent Transportation 2023年第2期2卷 56-65页

作者： Bingzhe Fu Wei Wang Yihuan Li Qiao Peng School of Control and Computer Engineering North China Electric Power UniversityBeijing102206China Group of Information Technology Analytics&OperationsQueen's University BelfastBelfastBT95EEUK

The safety and reliability of battery storage systems are critical to the mass roll-out of electrified transportation and new energy *** achieve safe management and optimal control of batteries,the state of charge(SOC)is one of the important *** machine-learning based SOC estimation methods of lithium-ion batteries have attracted substantial interests in recent ***,a common problem with these models is that their estimation performances are not always stable,which makes them difficult to use in practical *** address this problem,an optimized radial basis function neural network(RBF-NN)that combines the concepts of Golden Section Method(GSM)and Sparrow Search Algorithm(SSA)is proposed in this ***,GSM is used to determine the optimum number of neurons in hidden layer of the RBF-NN model,and its parameters such as radial base center,connection weights and so on are optimized by SSA,which greatly improve the performance of RBF-NN in SOC *** the experiments,data collected from different working conditions are used to demonstrate the accuracy and generalization ability of the proposed model,and the results of the experiment indicate that the maximum error of the proposed model is less than 2%.

关键词： Battery management SOC estimation Data science Neural network Golden section method Sparrow search algorithm

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Solid-Fluid Interaction Simulation System Based on SPH Unified Particle Framework

Solid-Fluid Interaction Simulation System Based on SPH Unifi...

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2022 International Conference on 3D Immersion, Interaction and Multi-Sensory Experiences, ICDIIME 2022

作者： Shao, Xuqiang Zhang, Xin Yang, Shihe Jin, Yizhong School of Control and Computer Engineering North China Electric Power University Hebei Baoding China

ISBN: (数字)9781665490092

ISBN: (纸本)9781665490092

Solid-fluid Interaction Simulation is the important research point in the field of fluid simulation. Existing researches mainly focus on the phenomena such as motion, deformation, infiltration, erosion, etc., and less attention is paid to the solid fracture caused by fluid impact. The simulation solutions used by the related researches have weakly coupling with the SPH solid-fluid interaction framework because their solid fracture methods need the geometric form for representing and processing the solid model. For the same reason, their methods have difficulty to parallelize and achieve the balance between Realism and real-time performance. To deal with these problems, a full process parallelization simulation framework is proposed for parallelize each key stage of the simulation system. The framework is based on the SPH unified particle framework and has the advantage of high parallelism of the SPH method because of the particle form of solid used to describe and solve solid field quantities. For solving the solid fracture, a physics-geometry hybrid method with the high parallelism implementation is proposed. This method is also based on particle form to solve the solid field quantities so that have strong coupling with SPH framework. In term of neighborhood particle search, a spatial three-level index sorting based on the unified grid method is proposed to optimize neighborhood search processes including solid particles. Because the spatial characteristics of the solid fracture method is considered, the two methods can be closely combined with each other. In the stage of fluid rendering, in order to avoid the communication between GPU and CPU caused by surface extraction, the Screen Space Fluid Rendering method is adopted. In SSFR, the particle data is directly input into the rendering pipeline on GPU for rendering without transfer to CPU for extracting fluid mesh. For verifying the stability of the parallelized framework, performance and Realism of the simulation

关键词： Optimization

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Design of Intelligent Epidemic Prevention Vehicle control System Based on Single-Chip Microcomputer 4

Design of Intelligent Epidemic Prevention Vehicle Control Sy...

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4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Li, Xiaolin North China Electric Power University School of Control and Computer Engineering Beijing102206 China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

Nowadays, the COVID-19 epidemic continues to repeat, and the novel coronaviruses are highly contagious. In order to solve the difficulties of information collection and cargo transportation in the process of epidemic prevention and control, and reduce the work intensity of epidemic prevention personnel. In this paper, a multi-functional intelligent epidemic prevention vehicle control system based on single-chip microcomputer is proposed to realize the goal of replacing manual control with intelligent vehicles. This design uses the stm32 single-chip microcomputer as the control core, for the work demand of the epidemic prevention site. First of all, the design realizes the intelligent vehicle tracking navigation and path planning function to realize the contactless distribution. Secondly, the function of face recognition and intelligent temperature measurement is completed, which can upload information remotely, process images, measure the temperature for diagnostics, and strengthen better interaction with the doctor terminal. At last, by wireless transmission, human-computer interaction is realized. The intelligent epidemic prevention vehicle control system can basically complete the designed function through many simulation experiments. Among them, the path planning algorithm can be completed within 5 s, and the success rate of face recognition is as high as 97 %, which achieves a good simulation effect and has a certain value in the current environment. © 2022 IEEE.

关键词： Face recognition

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Construction and application of a novel WGAN-CNN-based predicting approach for dust concentration at underground coal mine working faces

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Environmental Science and Pollution Research 2024年第27期31卷 39271-39284页

作者： Zhou, Banghao Qin, Botao Zhou, Qun Sun, Daowei Chen, Pengpeng Yang, Kai Pan, Qingyan Li, Huizhen Key Laboratory of Gas and Fire Control for Coal Mines China University of Mining and Technology Ministry of Education Jiangsu Xuzhou221116 China School of Safety Engineering China University of Mining and Technology Jiangsu Xuzhou221116 China School of Computer Science & amp Technology China University of Mining and Technology Jiangsu Xuzhou221116 China

To enhance the real-time monitoring and early-warning capabilities for dust disasters in underground coal mine, this paper presents a novel WGAN-CNN-based prediction approach to predict the dust concentration at underground coal mine working faces. Dust concentration, wind speed, temperature, and methane concentration were collected as the original data due to their nonlinear relationship. The consistency between the generated and original data distributions was verified through PCA dimensionality reduction analysis. The predictive performance of this approach was assessed using five metrics (R2, EVS, MSE, RMSE, and MAE) and compared with three other algorithms (Random Forest Regressor, MLP Regressor, and LinearSVR). The findings indicate that a majority of the generated data falls within the distribution range of the real dataset, exhibiting reduced levels of volatility and dispersion. The R2 values of prediction results are all above 98%, and the MSE values are between 0.0007 and 0.0106. The proposed approach exhibits superior predictive accuracy and robust model generalization capabilities compared to alternative algorithms, thereby enhancing the real-time monitoring and early-warning level of dust disasters in underground coal mine. This will facilitate the realization of advanced prevention and control measures for dust disasters, showcasing a wide range of potential applications. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Disasters

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Semantic Feature Division Multiple Access for Digital Semantic Broadcast Channels

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IEEE Internet of Things Journal 2025年第11期12卷 17123-17136页

作者： Ma, Shuai Sun, Zhiye Shen, Bin Wu, Youlong Li, Hang Shi, Guangming Li, Shiyin Al-Dhahir, Naofal Peng Cheng Laboratory Shenzhen518066 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China ShanghaiTech University School of Information Science and Technology Shanghai201210 China Shenzhen Research Institute of Big Data Guangdong Shenzhen518172 China Xidian University School of Artificial Intelligence Shaanxi Xi'an710071 China The University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75080 United States

In this paper, we propose a digital semantic feature division multiple access (SFDMA) paradigm in multi-user broadcast (BC) networks for the inference and the image reconstruction tasks. In this SFDMA scheme, the multi-user semantic information is encoded into discrete approximately orthogonal representations, and the encoded semantic features of multiple users can be simultaneously transmitted in the same time-frequency resource. Specifically, for inference tasks, we design a SFDMA digital BC network based on robust information bottleneck (RIB), which can achieve a tradeoff between inference performance, data compression and multi-user interference. Moreover, for image reconstruction tasks, we develop a SFDMA digital BC network by utilizing a Swin Transformer, which significantly reduces multi-user interference. More importantly, SFDMA can protect the privacy of users' semantic information, in which each receiver can only decode its own semantic information. Furthermore, we establish a relationship between performance and signal to interference plus noise ratio (SINR), which is fitted by an Alpha-Beta-Gamma (ABG) function. Furthermore, an optimal power allocation method is developed for the inference and reconstruction tasks. Extensive simulations verify the effectiveness and superiority of our proposed SFDMA scheme. © 2014 IEEE.

关键词： Image reconstruction

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A Class of Perimeter Defense Strategy via Relative Time and Maximum Matching

A Class of Perimeter Defense Strategy via Relative Time and ...

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2024 China Automation Congress, CAC 2024

作者： Yang, Chengqian Du, Ziyi Lin, Lixiong Xu, Guangtong Huang, Bomin School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China Department of Precision Instrument Tsinghua University Beijing China School of Ocean Information Engineering Jimei University Xiamen China Huzhou Institute Zhejiang University Huzhou China College of Computer Engineering Jimei University Xiamen China

ISBN: (纸本)9798350368604

This paper studies a class of perimeter defense problems for large-scale multi-robot systems. A perimeter defense strategy is designed via relative time calculations and maximum matching methods. The strategy is simple, effective, and easy to implement for large-scale perimeter defense problems. Some simulations are made to verify the effectiveness of the strategy. © 2024 IEEE.

关键词： Nanorobots

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A Strengthened Primal-Dual Decomposition Algorithm for Solving Electricity Market Pricing With Revenue-Adequacy and FFR Constraints

IEEE Transactions on Energy Markets, Policy and Regulation

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IEEE Transactions on Energy Markets, Policy and Regulation 2024年第3期2卷 379-391页

作者： Goudarzi, Hamed Hesamzadeh, Mohammad Reza Bunn, Derek Fotuhi-Firuzabad, Mahmud Shahidehpour, Mohammad Sharif University of Technology Center of Excellence in Power System Management and Control Tehran11365-11155 Iran Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm10044 Sweden London Business School Department of Management Science and Operations LondonNW1 4SA United Kingdom Illinois Institute of Technology Electrical and Computer Engineering Department ChicagoIL60616 United States

This paper develops a new decomposition algorithm for solving Electricity Market Pricing (EMP) problem, taking into account both revenue-adequacy and Fast Frequency Reserve (FFR) constraints. Due to revenue-adequacy constraint, a bilevel model of the EMP problem is introduced (BL-EMP). The upper level of the BL-EMP model represents the non-convex unit commitment (UC) decisions as well as the revenue-adequacy constraints of the market participants (generators, loads, and battery-storage owner). The lower level is a convex economic dispatch model with FFR constraint. To tackle the computational complexity of the considered BL-EMP model, this paper develops, tests, and proposes a Strengthened Primal-Dual Decomposition (SPDD) algorithm, which takes benefits from both Benders-like and Lagrange Dual-like algorithms. The new SPDD algorithm has a series of interesting computational properties, which are theoretically discussed in the paper. The SPDD algorithm has better computational performance than standard Benders decomposition algorithm and it also does not need tuning of the Big-M (or disjunctive) parameters for solving the proposed BL-EMP problem. Results from the modified IEEE 24-bus, the IEEE 118-bus, and the IEEE 300-bus system show the superiority of proposed SPDD algorithm over the classic Benders algorithm. © 2023 IEEE.

关键词： Power markets

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Data-driven Diagnostic Method of Zero-point Drifting of Wind Turbine Yaw Angle

Data-driven Diagnostic Method of Zero-point Drifting of Wind...

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第43届中国控制会议

作者： Qiankun Hu Ketao Dong Yali Zhao Peng Guo School of Control and Computer Engineering North China Electric Power University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In order to eliminate the zero-point drifting of wind turbine yaw angle,a diagnosis method based on hypothesis test is *** determining the sensitive wind speed interval of the wind turbine and detecting the power distribution,the yaw angle interval where the yaw angle zero-point drifting is located is determined,and the diagnosis is *** effectiveness of the proposed method is verified by taking the operation data of two wind turbine SCADA systems as an *** results show that the proposed method can accurately quantify the data distribution differences of different yaw error intervals and has high accuracy in the diagnosis of yaw angle zero-point drifting.

关键词： Wind Turbine SCADA System Yaw Angle Zero-point Drifting Hypothesis Test

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Wind Turbine Tower Abnormal Monitoring Based on Cloud Model

Wind Turbine Tower Abnormal Monitoring Based on Cloud Model

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第43届中国控制会议

作者： Yali Zhao Qiankun Hu Ketao Dong Peng Guo School of Control and Computer Engineering North China Electric Power University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Real-time monitoring of wind turbine output can find the problems in time and ensure the economic benefits of wind farms to the greatest *** power main belt formed by the normal operation data in the two-dimensional coordinate system of wind speed and power can accurately reflect the the power generation performance of a wind ***,Mahalanobis distance is used to calculate the deterioration degree of ***,Mahalanobis distance of monitoring data is analyzed and transformed by sliding window,and the unit state is visually presented by cloud model by specifying fuzzy comment set,and the classification information of normal,early warning and alarm are *** results show that the method can react the operating state of unit in a real,objective,quantitative and qualitative way,also can provide reasonable guidance for the follow-up maintenance work.

关键词： supervisory control and data acquisition(SCADA) abnormal monitoring cloud model wind turbine tower

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Multi-step Image Enhancement for Incinerator Flame Recognition

Multi-step Image Enhancement for Incinerator Flame Recogniti...

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第43届中国控制会议

作者： Lu Ye Zhao Zheng Zhou Ziyu Wang Haojie Zhao Dongzhuo School of Control and Computer Engineering North China Electric Power University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In order to address the issue of low segmentation accuracy in the weak flame region of waste incineration flame images and the potential loss of texture details at the flame edge, this study proposes an algorithm for segmenting incinerator flame images based on multi-step image enhancement. The algorithm consists of several steps. Firstly, a single-scale Retinex algorithm is employed to enhance the details of the noise-reduced image. Subsequently, an adaptive gamma correction method based on the inverse color transform is proposed to enhance the contrast between the image foreground and background, in conjunction with the inverse color transform algorithm. Finally, a 2D-Otsu algorithm is utilized to segment the image and extract the target flame region. Experimental results demonstrate that the proposed incinerator flame image segmentation algorithm based on multi-step image enhancement achieves superior segmentation performance, effectively preserving more detailed information in the weak flame region.

关键词： Image enhancement Retinex Image segmentation 2D-Otsu

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