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International Conference on Electric Power Equipment - Switching technology (ICEPE-ST)

作者： Ze Yang Dongsheng Cai Tianxiang Chen Qi Huang Lijun Wang College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798350388947

ISBN: (纸本)9798350388954

In this research, droplets with a diameter on the order of 100μm are studied. Their movement in the vacuum arc is simulated with the help of dynamic meshing technology. During the movement, the droplets are heated and charged by the vacuum arc. On the other hand, the feedback of droplets to the vacuum arc is also considered, including evaporation process and the ionization process of the droplet vapor. The results show that with the increase of droplet diameter, the temperature increase and the velocity of droplets decrease. The influence of the vacuum arc on the droplets can be determined by the ablation cloud of the droplets. The ionization process of the droplet vapor leads to a lower electron temperature and higher atom density around the droplets.

关键词： Heating systems Hands Clouds Interrupters Ionization Vacuum technology Switches Power systems Evaporation Vacuum arcs

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An Enhanced Data-Driven Model for Lithium-Ion Battery State-of-Health Estimation with Optimized Features and Prior Knowledge

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Automotive Innovation 2022年第2期5卷 134-145页

作者： Huanyang Huang Jinhao Meng Yuhong Wang Lei Cai Jichang Peng Ji Wu Qian Xiao Tianqi Liu Remus Teodorescu College of Electrical Engineering Sichuan UniversityChengduChina Faculty of Computer Science and Engineering Shanxi Key Laboratory for Network Computing and Security TechnologyXi’an University of TechnologyXi’anChina Smart Grid Research Institute Nanjing Institute of TechnologyNanjingChina Department of Automation University of Science and Technology of ChinaHefeiChina Key Laboratory of Smart Grid of Ministry of Education Tianjin UniversityTianjinChina Department of Energy Technology Aalborg University9220 AalborgDenmark

In the long-term prediction of battery degradation,the data-driven method has great potential with historical data recorded by the battery management *** paper proposes an enhanced data-driven model for Lithium-ion(Li-ion)battery state of health(SOH)estimation with a superior modeling procedure and optimized *** Gaussian process regression(GPR)method is adopted to establish the data-driven estimator,which enables Li-ion battery SOH estimation with the uncertainty level.A novel kernel function,with the prior knowledge of Li-ion battery degradation,is then introduced to improve the mod-eling capability of the *** for the features,a two-stage processing structure is proposed to find a suitable partial charging voltage profile with high *** the first stage,an optimal partial charging voltage is selected by the grid search;while in the second stage,the principal component analysis is conducted to increase both estimation accuracy and computing *** of the proposed method are validated on two datasets from different Li-ion batteries:Compared with other methods,the proposed method can achieve the same accuracy level in the Oxford dataset;while in Maryland dataset,the mean absolute error,the root-mean-squared error,and the maximum error are at least improved by 16.36%,32.43%,and 45.46%,respectively.

关键词： Li-ion battery State of health Gaussian process regression Kernel function Feature optimization

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A Review of Coordinated Control of DC Microgrids in PEDF Buildings

A Review of Coordinated Control of DC Microgrids in PEDF Bui...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Ziyi Ye Dongsheng Cai Shuang Luo Huanli Lu Jian Li Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Guiyang Engineering Corporation Limited Guiyang China Guiyang Engineering Corporation Limited Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

Microgrid is an important means to improve the utilization rate of distributed renewable energy, which is important for energy saving and emission reduction and realizing sustainable energy development. As DC microgrids can efficiently access energy sources such as photovoltaic and storage batteries, and DC equipment is increasing day by day, DC microgrids have a good development prospect. The application of DC microgrids in PEDF(photovoltaic, energy, DC, flexible) buildings can effectively utilize these advantages. The article firstly introduces the microgrid structure in the PEDF building. Secondly, it selects the flexible interconnection module of the microgrid, and combs the overall topology of the microgrid. Finally, it analyzes the control mode of each unit, and generalizes and summarizes the coordinated control mode of the microgrid in different working states.

关键词： Photovoltaic systems Renewable energy sources Reviews Electricity Buildings Microgrids Stability analysis

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Integration of 3D Attention Mechanism and Atrous Convolution for Lung Nodule Segmentation

Integration of 3D Attention Mechanism and Atrous Convolution...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Weixuan Tang Jun Wang Rui Shi Guang Yang School of Computer Science and Engineering Sichuan University of Science & Engineering YiBin China ChongQing University Fuling Hospital China School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Lung nodules, as an initial symptomatic indication of lung cancer, have been a significant concern for human health and well-being. In order to achieve more accurate segmentation of lung nodules in CT images, a 3D U-net segmentation method is proposed that incorporates the attention mechanism and dense cavity convolution to address the incomplete acquisition of spatial features of lung nodules by the U-net network. Firstly, a 3D Convolutional Block Attention Module is added after the jump connection to avoid the loss of spatial dimensional information due to the sequence-dependent channel attention by optimizing the parallel channel and spatial attention modules, and to improve the attention of the model to the key features, which helps the network focus on important lung nodule characteristics. Second, by adding the Residual-Atrous Spatial Pyramid Pooling block at the bottleneck of the network, the network can improve the receptive field while maintaining high resolution, and capture more information between layers of CT slices. In this paper, Luna16 and a case dataset from a hospital in Southwest China are used, and the experimental results show that the four metrics of Dice, Recall, Precision, and Jaccard have been improved by 3.14%, 2.06%, 1.67%, and 1.69%, respectively, and the segmentation results of the model in this paper are also closer to the gold standard compared to other mainstream methods.

关键词： Solid modeling Image segmentation Three-dimensional displays Attention mechanisms Convolution Lungs Computational modeling Computed tomography Lung cancer Spatial resolution

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Research on Radioisotope Identification of nuclear Pulse Sequence Based on CNN-BiLSTM

Research on Radioisotope Identification of Nuclear Pulse Seq...

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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Yanan Shang Rui Shi Shuxin Zeng Guang Yang School of Computer Science and Engineering Sichuan University of Science & Engineering YiBin China School of Nuclear Technology and Automation Engineering Chengdu University of Technolog Chengdu China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Aiming at the statistical limitations of isotope identification Methods by gamma spectroscopy, this paper studies a method of isotope recognition based on improved Hilbert-Huang Transform (HHT) combined with convolutional bidirectional long short-term memory neural network (CNN-BiLSTM), which does not require spectrum formation and directly analyzes nuclear pulse sequences. Results show that the model can achieve 96.98 per cent recognition accuracy. In addition, the model shows a good recognition effect in different pulse number and pulse sequence time, which further verifies the feasibility of isotope recognition based on nuclear pulse sequence, and provides a new idea and method for radioisotope recognition technology.

关键词： Radioactive materials Spectroscopy Accuracy Convolution Frequency-domain analysis Computational modeling Neural networks Time series analysis Transforms Isotopes

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DYNAMIC CORRELATION AMONG PERFORMANCE SHAPING FACTORS - CURRENT AND FUTURE DEVELOPMENT TRENDS 30

DYNAMIC CORRELATION AMONG PERFORMANCE SHAPING FACTORS - CURR...

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30th International Conference on nuclear engineering, ICONE 2023

作者： Xu, Zhihui Zhang, Yuxin Li, Fengxi Wang, Jipu Yang, Ming Institute for Advanced Study in Nuclear Energy & Safety College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China Mechanical and Electronic Engineering Department Heilongjiang Institute of Technology Harbin150030 China School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9784888982566

Many human reliability analysis (HRA) methods have been developed to evaluate the reliability of Main Control Room (MCR) of nuclear Power Plants (NPP). Performance Shaping Factors (PSFs) were used in most of them to depict the contextual factors with the combination of different dimension, and to qualitatively and quantitatively evaluate the human reliability. The correlations among PSFs were one of the most important challenges for the improvement of HRA analysis quality, while most of existing HRA methods consider PSFs independently. Based on the analysis of some of the existing HRA methods and literature review of published research in this field, this paper presents a report on techniques for identifying the correlations among PSFs and some insights for future research on revealing their actual correlations. © 2023 by JSME.

关键词： nuclear power plants

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A Survey of Carbon Emission Forecasting Methods Based on Neural Networks

A Survey of Carbon Emission Forecasting Methods Based on Neu...

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IEEE Asia Power and Energy engineering Conference (APEEC)

作者： Wei Liu Dongsheng Cai Joseph Nkou Nkou Qi Huang School of Nuclear Technology and Automation Chengdu University of Technology Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

The emission of a large amount of carbon dioxide has led to the greenhouse effect. With further research into the hazards of the greenhouse effect, the world’s major economies have started implementing energy-saving and emission-reduction plans. Predicting carbon emissions is important for the formulation of effective energy-saving and emission-reduction policies. This paper mainly introduces methods for predicting carbon emissions by using BP neural networks, recurrent neural networks, and a combination of traditional forecasting models with neural networks. Firstly, the characteristics of different neural networks are compared for carbon emission prediction. Secondly, the LSTM network is used for carbon emission prediction, and the evaluation results show the effect of the LSTM network. Finally, conclusion is drawn that BP and recurrent neural network are not ideal for long sequences. Joseph Junior NKOU NKOU

关键词： Solid modeling Recurrent neural networks Greenhouse effect Biological system modeling Neural networks Carbon dioxide Predictive models

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Research on microstrain loading device and strain detection method based on SWCNT strain sensor 9

Research on microstrain loading device and strain detection ...

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9th International Symposium on Sensors, Mechatronics, and automation System, ISSMAS 2023

作者： He, Huajun Zheng, Fuzhong Zhang, Jie Sun, Shaohua Tang, Zhichao Cao, Qiang School of Automation Chengdu University of Information Technology Chengdu610225 China Intelligent Manufacturing and Automobile School Chongqing College of Electronic Engineering Chongqing401331 China NO.7 Oil Production Plant PetroChina Changqing Oilfield Company Qingyang745708 China

ISBN: (纸本)9781510672802

Monitoring the microstrain on the surface of equipment is of great significance for its health monitoring and daily maintenance. A microstrain detection method is researched in this article based on the photoluminescence characteristics of SWCNT materials. The detection of microstrain can be achieved by using the SWCNT strain sensing film pasted on the surface of the tested equipment. A standard strain gauge can also be pasted on the back of the corresponding position where the SWCNT strain sensing film is pasted to check the detection accuracy of the SWCNT strain sensing film. A microstrain loading device is designed in this paper. Then, a simulation study on the stress distribution of components with different shapes and sizes is conducted. Simulation results indicate that the geometric shape of the tested component has a significant impact on the stress distribution. © 2024 SPIE.

关键词： Sensors Signal processing Design and modelling Humidity Photoluminescence Safety equipment Analog to digital converters Scientific research Speckle interferometry Thin films

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Research on Microseismic Triggered Image Acquisition System for Landslide Monotoring 5

Research on Microseismic Triggered Image Acquisition System ...

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5th IEEE Information technology, Networking, Electronic and automation Control Conference, ITNEC 2021

作者： Yang, Liu Zhu, Xing Xi, Hewei He, Zhaoqing Zhu, Qingsong Chengdu University of Technology State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu610059 China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu610059 China

ISBN: (纸本)9781665415989

The previous landslide image acquisition system adopts a continuous image acquisition and transmission method, which has high consumption and produces many redundant data. Therefore, a new landslide image acquisition system is developed in this paper. The system adopts seismic geophone to gain landslide motion data, and then the dual limit comparator filters out the landslide motion data and forms a trigger signal to wake up the system. In the end, after being awakened, the embedded micro-controller collects and transmits the image. With the intermittent image acquisition and transmission method, the equipment keeps in a low-power consumption for a long time when the landslide movement is not severe. The equipment will be awakened only when the landslide movement is violent. It turns out that compared with the continuous acquisition method, the power consumption of the system can be reduced by about 66%, and the data amount can be reduced by about 60KB when the system is triggered only once in a minute. © 2021 IEEE.

关键词： Landslides

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Monte Carlo Modeling and Verification of 6 MV Linear Accelerator

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World Journal of engineering and technology 2022年第2期10卷 213-223页

作者： Shixiong Lu Haijun Deng College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Department of Oncology Sichuan Mianyang 404 Hospital Mianyang China

Purpose: To model the ELEKTA COMPACT accelerator head by using EGSnrc/BEAMnrc/DOSXYZnrc and to validatethe simulation according to the depth-dose and lateral profiles of different radiation fields measured by the water phantom. Methods: IBA Blue Water Phantom2 and CC13 Ionization Chamber were used to measure the depth-dose curves at 10 cm × 10 cm field and profile curves at 10 cm depth underwater. In BEAMnrc, the main components of accelerator head and the initial electron beam are established based on the specifications file, and the phase space file containing the photon beam information is generated. In DOXYZnrc, phase space files were used to irradiate a homogeneous water phantom of the same size as the IBA water phantom, and the simulated percentage depth dose curves and lateral profiles were outputted. The accuracy of the model was evaluated by mean square error (MSE) compared with the measured data. PDD curves are used to determine the energy of the initial electron beam. Dose profile curves are used to adjust the flattening filter. The penumbra on lateral profiles is used to adjust the full-width half-maximum (FWHM) of the electron source. Result: The electron energy of 5.8 MeV was considered the best match after comparing the PDD curves of 5.6 - 6.2 MeV electron beams. The flattening filter can only be adjusted by trial. In the final result, the maximum fluctuation of profile curve within 80% of the maximum field size is less than 3%, which meets the requirements of field flatness. The optimum FWHM for different fields is not consistent due to the Transmission penumbra. But a match can be approached by adjusting the FWHM every 10 cm field size.

关键词： EGSnrc/BEAMnrc/DOSXYZnrc Linear Accelerator Initial Electron Beam PDD Lateral Profiles

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