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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

作者： Cheypoca, Thepjit Promphanich, Wiboon Thway, Aung Ye Hankae, Angelina Phimpissada Jeenmuang, Siwakorn Pattanadech, Norasage School of Engineering King Mongkut's Institute of Technology Ladkrabang Instrumentation and Control Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Computer Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Electrical Engineering Dept. Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Mechatronics Engineering Dept. Bangkok Thailand

ISBN: (纸本)9798350374605

This paper introduces a novel approach for classifying with the 1D Convolutional Neural Network model for partial discharge patterns, that consists of corona discharge, surface discharge and internal discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The Artificial Neural Network for the classification model was constructed. Moreover, 2×1D CNN feature extraction was utilized to reduce the curse of dimensionality in the dense layer of the proposed PD classification model. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed. © 2024 IEEE.

关键词： Convolutional neural networks

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Vehicle Route Planning Using A∗ Algorithm in Real-world Roads 4

Vehicle Route Planning Using A∗ Algorithm in Real-world Roa...

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2022 4th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2022

作者： Liu, Xingyu School of Control and Computer Engineering North China Electric Power University Beijing100096 China

With the technical progress in the fields of robotics as well as artificial intelligence, many intelligent algorithms which focus on robot path planning problems have been developed so far. A∗ algorithm is an efficient and technically mature path planning algorithm that can efficiently solve robot path planning problems. In this context, this paper proposes an improved A∗ algorithm to plan roads for automobiles in urban areas, introduce time factors into the cost function, select an urban area, use grid map modeling, and simulate in the MATLAB environment. The final result shows that this kind of algorithm can efficiently solve the problem of automobile road planning. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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Clarity Method of Low-illumination and Dusty Coal Mine Images Based on Improved AMEF

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Informatica (Slovenia) 2023年第7期47卷 51-62页

作者： Su, Chang Li, Ziqiang Wei, Zhongliang Xu, Naizhong Yuan, Quan State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine Anhui University of Science and Technology Huainan China School of Mechanical Engineering Anhui University of Science and Technology Huainan China School of Computer Science and Engineering Anhui University of Science and Technology Huainan China School of Mining Anhui University of Science and Technology Huainan China

The existing image processing methods based on physical models can have a significant impact on defogging performance due to inaccurate estimation of the depth of field information. These methods often encounter problems such as low brightness, invisible color distortion, and loss of detail when processing images with poor lighting conditions, such as those taken in coal mines. To address these issues, this paper proposes a new algorithm based on artificial multi-exposure image fusion. The proposed method performs global exposure on images with uneven illumination by combining S-type functions and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm in the Hue-Saturation-Value (HSV) color space. This reduces the spatial dependence of brightness during processing and avoids color distortion problems that may arise in the Red-Green-Blue (RGB) color space. To mitigate the issue of detail loss, a gradient-domain guided filter is used to preserve fine structures in images, while an improved homomorphic filtering algorithm is introduced during the Laplacian pyramid decomposition process to reduce image content loss arising from large dark areas. This paper also conducted subjective, objective, and computational time comparisons to evaluate performance, providing reliable results regarding speed, quality, and reliability in processing hazy images. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Luminance

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Power grid cloud resource status data compression method based on deep-learning

Recent Advances in Computer Science and Communications

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Recent Advances in computer Science and Communications 2021年第3期14卷 941-951页

作者： Liang, Weixuan Zhu, Youchan Li, Guoliang School of Control and Computer Engineering North China Electric Power University Baoding China

Background: As the "three-type two-net, world-class" strategy is proposed, the key issues to be addressed are that the number of cloud resources in power grid continues to grow and there is a large amount of data to be filed every day. The long-term preservation of data, using backup data for the operation and maintenance, fault recovery, fault drill and tracking of cloud platform are essential. The traditional compression algorithm faces severe challenges. Methods: In this case, this paper proposes the deep-learning method for data compression. First, a more accurate and complete grid cloud resource status data is gathered through data cleaning, correction, and standardization, the preprocessed data is then compressed by SaDE-MSAE. Results: Experiments show that the SaDE-MSAE method can compress data faster. The data compression ratio based on neural network is basically between 45% and 60%, which is relatively stable and stronger than the traditional compression algorithm. Conclusion: The paper can compress the data quickly and efficiently in a large amount of power data. Improve the speed and accuracy of the algorithm while ensuring that the data is correct and complete, and improve the compression time and efficiency through the neural network. It gives better compression schemes and cloud resource data grid. © 2021 Bentham Science Publishers.

关键词： Electric power transmission networks

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Error-Based Active Disturbance Rejection control for Maximum Power Point Tracking in Photovoltaic System 17th

Error-Based Active Disturbance Rejection Control for Maximum...

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17th Chinese Intelligent Systems Conference, CISC 2021

作者： Ke, Yin Hou, Guolian School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789811663239

With the recent focus marked on conversion efficiency and renewable energy, more research is being devoted to the high-performance maximum power point tracking technology for photovoltaic applications. However, the intermittence and naturalness of solar energy bring a series of severe challenges to photovoltaic system, such as overload and overvoltage. In addition, photovoltaic system is faced with various parameter uncertainties and disturbances from irradiance. Traditional maximum power point tracking methods, such as perturb & observe and incremental conductance, are limited to tracking speed and tracking accuracy. To this end, a novel maximum power point tracking scheme based on the error-based active disturbance rejection control approach and perturb & observe method is proposed to obtain higher efficiency. In the face of various irradiance changes, disturbances can be eliminated rapidly. Finally, the superior performance of proposed scheme is validated by extensive simulation results. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Errors

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Distributed Power Sharing control of AC Microgrid Based on State Observer Approach

Distributed Power Sharing Control of AC Microgrid Based on S...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Zhang, Yanjing Yu, Mei Wei, Bo Xiao, Feng School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789811581540

This paper proposes a consensus-based distributed algorithm to solve both active and reactive sharing problems, which involves alternative current (AC) microgrids and spatially concentrated dispatchable distributed generators (DDGs). The output feedback control method and the leader-follower scheme are designed for each generator to achieve the consistency of the output proportion. Compared with other control strategies, the controller based on state observer only uses local output information and a set of dynamic communicated compensator. In addition, the protocol can solve the proportional consistency with different parameters, which also meets the balance of supply and demand in power system. Numerical examples verify the effectiveness of this method. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Numerical methods

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

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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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Partial Discharge Classification with Transformer Neural Networks 14

Partial Discharge Classification with Transformer Neural Net...

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14th International Conference on the Properties and Applications of Dielectric Materials, ICPADM 2024

ISBN: (纸本)9798350374605

This paper introduces an approach with the Transformer Neural Networks model for partial discharge patterns classification, that consists of corona discharge, internal discharge and surface discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The phase value will be encoded into the charge array and Transformer Neural Network is constructed using Positional Embedding and Transformer Encoder Layer. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed © 2024 IEEE.

关键词： Electric corona

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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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