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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Zhiyang Li Dongsheng Cai Shuang Luo Zhihui Yang Huanli Lu Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Guiyang Engineering Corporation Limited Guiyang China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

Photovoltaic power generation are becoming an important trend in the composition of power grid systems, and are playing an increasing role in DC distribution networks due to their environmentally friendly, easy-to-install, and easy-to-maintain characteristics. However, the difficulties in the diagnosis of DC arc faults are beginning to emerge. Compared with the reciprocating zero crossing point of the AC transmission grid, the DC circuit current has no natural zero crossing point, and when a DC arc fault occurs, it cannot be detected using traditional AC arc detection methods. For this reason, a great deal of work has been done over the years by workers in the electrical field, focusing on analyzing the characteristics of arc faults in DC power systems and their effects on the system. This technology is essential to ensure the safe operation of DC power systems, prevent equipment damage, and reduce unplanned outages. However, although there are many studies around the detection of DC arcs, the current research on real-time diagnosis and early warning systems for the development of DC arc dynamics is still insufficient. This paper introduces the DC arc fault potential hazards in DC circuits through the policy initiatives and applications of new energy technologies in various countries, and in the main part of the article, it introduces the diagnostic methods based on electromagnetic radiation, arc sound, time-domain features, and frequency-domain features, as well as the arc diagnostic techniques through artificial intelligence techniques that have emerged in recent years. At the same time, the article also describes the advantages and shortcomings of the various technical routes and predicts the possibility of combining DC arc diagnostic technology with industrial Internet of Things and other technologies in the future.

关键词： Electrical engineering Reviews Power system dynamics Signal processing algorithms Distribution networks Real-time systems Power grids

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Research Status and Prospect of Energy Storage technology in PEDF Building

Research Status and Prospect of Energy Storage Technology in...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Huanli Lu Xinglin Pan Yuhui Zhou Xiaorui Wang Qi Huang Dongsheng Cai Guiyang Engineering Corporation Limited Guiyang China School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

PEDF is an acronym for the application of the four technologies of solar photovoltaic, energy storage, direct current and flexible interaction in the field of buildings. Photovoltaic (PV) technology is gradually gaining attention as a representative of clean energy, and its ability to convert solar energy into electricity offers a viable approach to diminishing reliance on fossil fuels and decreasing carbon emissions. Energy storage technology, on the other hand, is becoming increasingly important as a key means of balancing PV output fluctuations and improving system stability. And DC distribution technology, with its high efficiency and low-loss characteristics, shows great potential in distributed PV access, microgrid construction and other fields. At the same time, flexible interaction technology realizes the friendly interaction between power grid and all kinds of distributed power sources and loads through intelligent regulation, which improves the flexibility and toughness of power system.

关键词： Photovoltaic systems Fluctuations Terminology Buildings Solar energy Microgrids Power system stability

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DC Power Distribution System Architecture of PEDF Buildings: A Comprehensive Review

DC Power Distribution System Architecture of PEDF Buildings:...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Huanli Lu Xinglin Pan Yuhui Zhou Songxiang Chen Qi Huang Dongsheng Cai Guiyang Engineering Corporation Limited Guiyang China School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

With the wide application of distributed energy resources and the rapid development of renewable energy technologies, building energy systems are gradually evolving towards high efficiency, flexibility and *** buildings (Photovoltaic Electricity Generation, Electricity Storage, direct current Distribution and Flexible Electricity Consumption), as an emerging building energy system, provide a solution for the efficient use of renewable energy and the optimization of energy consumption. While the traditional alternating current (AC) grid has problems of energy loss and instability in the transmission and distribution of energy, the direct current (DC) distribution grid can reduce energy loss and improve the efficiency of energy utilization. The DC distribution grid architecture of PEDF buildings can not only supply the DC power generated by the PV power generation system directly to the load equipment inside the building, but also store the excess power to improve the stability and reliability of the energy, and also It can realize the optimal distribution and management of energy through the intelligent energy management system, which can effectively reduce energy waste, improve energy utilization efficiency, and provide strong support for the sustainable development of the building. This paper summarizes the research progress of PEDF buildings in establishing DC distribution network architecture, which can better understand the advantages and disadvantages of the building and the challenges it faces, and aims to provide reference for researchers and practitioners in this field.

关键词： Renewable energy sources Energy loss Reviews Electricity Architecture Buildings Systems architecture

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A nonlinear wave coupling algorithm and its programing and application in plasma turbulences

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Chinese Physics B 2022年第6期31卷 541-548页

作者： Yong Shen Yu-Hang Shen Jia-Qi Dong Kai-Jun Zhao Zhong-Bing Shi Ji-Quan Li Southwestern Institute of Physics Chengdu 610041China School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Institute for Fusion Theory and Simulation Zhejiang UniversityHangzhou 310013China College of Nuclear Science and Engineer East China University of TechnologyNanchang 330013China

The fully developed turbulence can be regarded as a nonlinear system,with wave coupling inside,which causes the nonlinear energy to transfer,and drives the turbulence to develop further or be *** analysis is one of the most effective methods to study turbulence *** order to apply it to the study of the nonlinear wave coupling process of edge plasma turbulence,an efficient algorithm based on spectral analysis technology is proposed to solve the nonlinear wave coupling *** algorithm is based on a mandatory temporal static condition with the nonideal spectra separated from the ideal *** realization idea and programing flow are *** to the characteristics of plasma turbulence,the simulation data are constructed and used to verify the algorithm and its implementation *** simulation results and experimental results show the accuracy of the algorithm and the corresponding program,which can play a great role in the studying the energy transfer in edge plasma *** an application,the energy cascade analysis of typical edge plasma turbulence is carried out by using the results of a case ***,a physical picture of the energy transfer in a kind of fully developed turbulence is constructed,which confirms that the energy transfer in this turbulent system develops from lower-frequency region to higher-frequency region and from linear growing wave to damping wave.

关键词： bispectral analysis wave coupling algorithm plasma turbulence energy cascade

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A High-Precision Parameter Identification Method Based on Improved DFT for Sub-Super Synchronous Oscillations

A High-Precision Parameter Identification Method Based on Im...

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IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)

作者： Feiyu Sun Dongsheng Cai Zhengyuan Zhang Qi Huang The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (数字)9798350352290

ISBN: (纸本)9798350352306

Wind energy has been employed extensively as a renewable energy source with the aim of carbon neutrality. The power system also makes extensive use of power electronic properties and lead to the sub/super-synchronous oscillation (Sub/Sup-SO) issue, which damages equipment and jeopardizes the power system's ability to operate safely and steadily. To improve the frequency band estimation range to 100 Hz, this research use Phasor Measurement Unit (PMU) instantaneous value data to determine the Sub/Sup-SO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the Sub/Sup-SO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple Sub/Sup-SO modes. The simulation results show that the proposed method has high discrimination bandwidth, high discrimination accuracy and strong flexibility.

关键词： Damping Accuracy Simulation Discrete Fourier transforms Noise Frequency estimation Phasor measurement units Mathematical models Power systems Oscillators

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Intra-Graph-Based Few-Shot Link Prediction in Knowledge Graph 6

Intra-Graph-Based Few-Shot Link Prediction in Knowledge Grap...

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6th IEEE Conference on Energy Internet and Energy System Integration, EI2 2022

作者： Jonathan, Anto Leoba Bamisile, Olusola Cai, Dongsheng Joseph, Ejiyi Chukwuebuka Junior Nkou Nkou, Joseph Huang, Qi Chengdu University of Technology School of Nuclear and Automation Engineering Chengdu China Chengdu University of Technology Sichuan Indust. Internet Intelligent Monitoring and Applic. Engineering Technology Research Center Chengdu China University of Electronic Science and Technology of China School of Information and Software Engineering Chengdu China

ISBN: (纸本)9798350347159

Knowledge graphs (KG) that express the structure of relations between entities have become an increasingly attractive area in research into cognition and intelligence at the human level. One of the most known challenges in KG, which is the fact that a large number of training examples are required for every relation to predict a new triple, has sparked increasing interest in the few-shot link prediction method. Existing work on few-shot link prediction does not fully exploit entity information such as symmetry. In this work, we made a prediction of new triples about relations by observing only a few associative triples. In order to make new predictions of triples, we concentrated on the transfer of the most important common information and the reconciliation of the entity between the set and query set support by using Intra-Graph. Our experiment are lead on two datasets and demonstrated that our results achieved the state-of-the-art in few-shot link prediction. © 2022 IEEE.

关键词： Knowledge graph

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XVAE-mViT: Explinable Hybrid Artificial Intelligence Framework for Predicting COVID-19 from Chest X-Ray and CT Scans 7

XVAE-mViT: Explinable Hybrid Artificial Intelligence Framewo...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Addo, Daniel Al-Antari, Mugahed A. Zhou, Shijie Sarpong, Kwabena Butun, Ertan Talo, Muhammed Abualkebash, Humam Ukwuoma, Chiagoziem C. School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Sejong University DaeyangAI Center Department of Artificial Intelligence Seoul Korea Republic of Firat University Department of Computer Engineering Elaziǧ Turkey Firat University Department of Software Engineering Elazig Turkey Kocaeli University Department of Mechatronics Engineering Kocaeli Turkey The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan China

ISBN: (纸本)9798350342154

The COVID-19 virus has rapidly spread as a global pandemic, causing significant impacts on public health, economies, and daily life worldwide. Accurately and quickly predicting COVID-19 is crucial to maintaining stronger healthcare systems. This paper introduces a novel hybrid model of artificial intelligence that combines the benefits of the Variational Auto-Encoder (VAE) with the attention mechanism based on the Vision Transformer (ViT). The novel encoder network is structured with four sequential blocks, each involving residual connections of two multiscale kernel depth-wise separable convolution (MKnDSC) modules. The mobile ViT is coupled with the V AE to serve as the classification head for predicting COVID- 19 using chest X-ray (CXR) and computed tomography (CT) scan modalities. We achieved promising classification results with overall accuracies of 96.16% and 95.42% using CXR and CT images, respectively. The proposed hybrid AI framework appears to be a practical solution, especially considering its lightweight structure of 2.15 million parameters and 0.68 FLOPs. © 2023 IEEE.

关键词： COVID-19

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New Method for Sourceless Efficiency Calibration for Internal Irradiation Dose Calculation Based on Coupled Cfpd and Mc Simulations

SSRN

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SSRN 2024年

作者： Dong, Lang Wang, Ming Deng, Qingyang Dai, Wei Liao, Sheng Xie, Guoyu Sun, Tiantian College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province Chengdu University of Technology Chengdu610059 China School of Clinical Medicine The First Affiliated Hospital of Chengdu Medical College Chengdu610500 China

Improving the accuracy of the internal irradiation detector sourceless efficiency calibration is critical to ensuring the safety of special personnel. Computational fluid-particle dynamics (CFPD) has proven to be a reliable tool for calculating aerosol transport properties in the respiratory tract, while Monte Carlo (MC) can accurately model ray-matter interactions. This paper combines CFPD and MC to investigate the internal irradiation detector sourceless efficiency calibration based on the radiation produced during the radioactive aerosol particle decay deposited in the respiratory tract. First, this paper establishes a physiologically structured respiratory tract model containing the nose-lungs based on computed tomography (CT) and International Commission on Radiological Protection (ICRP) 66 Report;Secondly, the distribution of inhaled radioactive aerosol particles containing Co-60 and Cs-137 deposited on the lining of the respiratory tract was systematically analyzed in humans under specific respiration;Finally, the coupled respiratory model and the deposition data of the particles are used to perform sourceless efficiency calibration calculations for high purity germanium (HPGe) detectors. The results show that the particle deposition in the respiratory tract is mainly affected by the particle size, the particle size is larger, the more likely to be affected by the inertial collision deposited in the nasal cavity. There are differences in the distribution of different particles deposited in the respiratory tract, when the particle density is higher, it is more likely to be aggregate deposited in the nasal cavity. When performing sourceless efficiency calibration, the particle deposition distribution in the respiratory tract affects the efficiency and accuracy of the detector, and removing particle deposition data from the non-detector detection region can effectively improve the efficiency and accuracy of sourceless efficiency calibration. This study can effec

关键词： Particle size

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Multi-Dimensional Hybrid Quantitative Analysis of Teaching Evaluation by Big Data technology: A Case Study on Chinese Universities

Multi-Dimensional Hybrid Quantitative Analysis of Teaching E...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Laiying Long Yingzi Wen Fei Li Muhao Zhang College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Department of Physics Universitat Politècnica de Catalunya Barcelona Spain

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Students' feedback is adopted as a common method of evaluating teaching quality, which is crucial in monitoring teaching quality in colleges and universities. However, various factors such as area, gender, and age of the students can influence the model, content, and subjective bias of teaching quality evaluation. Therefore, we conducted a questionnaire survey for students at 90 universities in China and analyzed the data using Tableau and SPSS. The current teaching evaluation system lacks model diversity, discipline specificity, and objective standardization. Thus, improvement considering the relationship between students' cognition, attitude, and participation is proposed to provide a significant reference on the higher education reform system based on the result.

关键词： Surveys Statistical analysis Education Evaluation models Standardization Receivers Big Data

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Research on Neutron and Gamma Discrimination Method Based on Anti-Aliasing Pulse Shaping

SSRN

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SSRN 2023年

作者： Zhao, Yang Wang, Min Hu, Biao Tan, Liang Liang, Zhiyang Chen, Fengli Liang, Jiangtao Liu, Xianghe Faculty of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

The detectors commonly used in neutron measurement are sensitive to both neutrons and gamma, so it is necessary to distinguish neutrons from gamma rays. Traditional pulse shape discriminators (PSD) include charge comparison method and pulse gradient analysis method, which are representative and need less calculation. In addition, there are digital PSD techniques based on pulse shaping. In this paper, the anti-aliasing shaping method based on Z transform is presented, and the method is applied to the neutron and gamma pulses obtained from simulation and experiment, and the anti-aliasing shaping method is realized, which proves the correctness of the anti-aliasing shaping method. In addition, neutron and gamma pulses are simulated, and the discrimination of neutron and gamma is realized by pulse shaping ratio method, which further verifies the feasibility of the shaping method. At last, the neutron and gamma pulses from Am-Be neutron source detected by EJ276 are analyzed, and the discrimination effects of the three methods are compared: (1) charge comparison method, (2) pulsed gradient analysis method, (3) pulse shaping ratio method. The experimental results show that the pulse shaping ratio method is superior to the charge comparison method and the pulse gradient method. © 2023, The Authors. All rights reserved.

关键词： Neutrons

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