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2018 International Conference on Manufacturing technology, Materials and Chemical engineering, MTMCE 2018

作者： Zhang, C.Y. Chen, G.Z. Miao, C.W. Zhao, Y.F. Zhong, S. College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

Aiming at the shortage of electro-hydraulic robot in terms of system fluctuation and response speed compared with electric robot. The static and dynamic characteristics of a load-sensitive electro-hydraulic robot electro-hydraulic driving system are simulated based on AMESim software in this paper. By analysing the static and dynamic characteristics of the system, the theoretical knowledge is combined with the simulation results. The factors that affect the stability of the system are emphatically explored to provide ideas for optimizing and improving the stability of the electro-hydraulic driving system of load-sensitive electro-hydraulic robots. © Published under licence by IOP Publishing Ltd.

关键词： Machine design

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Research on the Effect of Energy Consumption Structure on Carbon Emission Based on LMDI Model

Research on the Effect of Energy Consumption Structure on Ca...

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作者： Hao Ma Bin Guo Na Xiang Mingxing Gou Shiyuan Zhang College of Management Science Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu University of Technology College of Business Chengdu University of Technology College of Environment and Civil Engineering Chengdu University of Technology College of Geosciences Chengdu University of Technology

The long-term and extensive economic development mode has a great impact on the environment of Sichuan Province, and the sustainable development of the economy is limited.A prominent problem in the economic development of Sichuan Province is that coal consumption is still high, and energy conservation and emission reduction work faces severe challenges. Adjusting the energy structure plays an important role in reducing carbon emissions and developing a low-carbon *** paper mainly studies the carbon emission coefficient, the per capita carbon emissions of Sichuan Province and the influencing factors of carbon emissions, analyzes the current situation of carbon emissions in Sichuan Province, and calculates the per capita carbon emissions based on the resident population data of Sichuan Province, and then the per capita carbon emissions in Sichuan Province. The quantity is the research object, and the LMDI model is established to comprehensively analyze the effect of energy consumption structure on carbon emissions in Sichuan Province.

关键词： Carbon Emissions Energy Structure LMDI Model

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Study on the influence of the gas superficial velocity on the radon adsorption of activated carbon

Study on the influence of the gas superficial velocity on th...

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作者： Meng Wang Yi Gu Fei Li Liangquan Ge Heng Lu Liang Luo College of Nuclear Technology and Automation Engineering Chengdu University of Technology Key Laboratory of Applied Nuclear Techniques in Geosciences Sichuan Chengdu University of Technology Chongqing Jian an Instrument Co Ltd

In order to improve the radon adsorption efficiency of activated carbon and provide a reference for reducing the cost of radon purification,the radon adsorption experiment of activated carbon under different gas superficial velocities under the active adsorption mode was studied to measure the radon adsorption quantity of activated *** radon adsorption quantity of apricot shell activated carbon and coal-based activated carbon did not change significantly with the increase of the gas superficial *** the gas superficial velocity increased from 0.9 cm/s to 2.0 cm/s in turn,the radon adsorption quantity of coconut shell activated carbon did not change *** radon adsorption quantity of coconut shell activated carbon increased first and then decreased when the gas superficial velocity increased from 2.0 cm/s to 3.1 cm/*** the gas superficial velocity was about 2.7 cm/s,the radon adsorption quantity of coconut shell activated carbon reached its peak value.2.7 cm/s can be selected as the optimum gas superficial velocity for the radon adsorption of coconut shell activated carbon.

关键词： net Study on the influence of the gas superficial velocity on the radon adsorption of activated carbon

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Empirical Analysis of the Impact of Energy Consumption on Industrial Structure-Take Sichuan Province, China as an example

Empirical Analysis of the Impact of Energy Consumption on In...

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作者： Shiyuan Zhang Mingxing Gou Na Xiang Bin Guo Hao Ma College of Geosciences Chengdu University of Technology College of Business Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu University of Technology College of Environment and Civil Engineering Chengdu University of Technology College of Management Science Chengdu University of Technology

In recent years, the growth rate of GDP in Sichuan Province has continued to exceed the national average, and its economic aggregate has also achieved leapfrog development. This paper combines the data of total energy consumption in Sichuan Province to conduct an empirical analysis of the impact of energy and industrial structure in Sichuan Province, and finally gives policy recommendations. The study found that the continuous increase of carbon emissions in Sichuan Province in recent years is mainly caused by the excessive dependence on coal-based fossil energy development economy. By increasing the ratio of oil and natural gas, the increase of carbon emissions can be effectively reduced.

关键词： Energy Consumption Industrial Structure Empirical Analysis

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Exploring the Influence of IP on Cultural Creative Art Design from the Perspective of Cultural Sociology

Exploring the Influence of IP on Cultural Creative Art Desig...

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作者： Shuai Li Shanshan Yi Department of Industrial Design The College of Nuclear Technology and Automation Engineering Chengdu University of Technology

Cultural sociology has important theoretical guiding significance for cultural creative art design and *** China's society entering the important period of innovation-driven development,IP development with certain scale of fans and huge market potential sets off a wave of frenzy in cultural industry,but also spawns countless excellent cultural creative *** paper briefly summarizes the concept of cultural sociology and the relationship between cultural sociology and cultural industry,and analyzes the impact of IP on cultural creative design and the significance and value of cultural sociology in cultural creative art design in combination with some practical cases to provide somewhat basis for relevant researches made in the future.

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Signal response model in PandaX-4T

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Physical Review D 2024年第2期110卷 023029-023029页

作者： Yunyang Luo Zihao Bo Shibo Zhang Abdusalam Abdukerim Wei Chen Xun Chen Chen Cheng Zhaokan Cheng Xiangyi Cui Yingjie Fan Deqing Fang Lisheng Geng Karl Giboni Xuyuan Guo Chencheng Han Ke Han Changda He Jinrong He Di Huang Junting Huang Zhou Huang Ruquan Hou Yu Hou Xiangdong Ji Yonglin Ju Chenxiang Li Jiafu Li Mingchuan Li Shuaijie Li Tao Li Qing Lin Jianglai Liu Congcong Lu Xiaoying Lu Lingyin Luo Wenbo Ma Yugang Ma Yajun Mao Yue Meng Xuyang Ning Binyu Pang Ningchun Qi Zhicheng Qian Xiangxiang Ren Nasir Shaheed Xiaofeng Shang Xiyuan Shao Guofang Shen Lin Si Wenliang Sun Andi Tan Yi Tao Anqing Wang Meng Wang Qiuhong Wang Shaobo Wang Siguang Wang Wei Wang Xiuli Wang Xu Wang Zhou Wang Yuehuan Wei Mengmeng Wu Weihao Wu Yuan Wu Mengjiao Xiao Xiang Xiao Binbin Yan Xiyu Yan Yong Yang Chunxu Yu Ying Yuan Zhe Yuan Youhui Yun Xinning Zeng Minzhen Zhang Peng Zhang Shu Zhang Tao Zhang Wei Zhang Yang Zhang Yingxin Zhang Yuanyuan Zhang Li Zhao Jifang Zhou Ning Zhou Xiaopeng Zhou Yong Zhou Yubo Zhou Zhizhen Zhou Department of Modern Physics University of Science and Technology of China Hefei 230026 China School of Physics and Astronomy Shanghai Jiao Tong University Key Laboratory for Particle Astrophysics and Cosmology (MoE) Shanghai Key Laboratory for Particle Physics and Cosmology Shanghai 200240 China Shanghai Jiao Tong University Sichuan Research Institute Chengdu 610213 China School of Physics Sun Yat-Sen University Guangzhou 510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-Sen University Zhuhai 519082 China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Department of Physics Yantai University Yantai 264005 China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern Physics Fudan University Shanghai 200433 China School of Physics Beihang University Beijing 102206 China International Research Center for Nuclei and Particles in the Cosmos and Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang University Beijing 100191 China School of Physics and Microelectronics Zhengzhou University Zhengzhou Henan 450001 China Yalong River Hydropower Development Company Ltd. 288 Shuanglin Road Chengdu 610051 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China Department of Physics University of Maryland College Park Maryland 20742 USA State Key Laboratory of Particle Detection and Electronics New Cornerstone Science Laboratory Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Research Center for Particle Science and Technology Institute of Frontier and Interdisciplinary Science Shandong University Qingdao 266237 Shandong China Key Laboratory of Particle Physics and Particle Irradiation of Ministry of Education Shandong University Qingdao 266237 Shandong China School of Physics Peking University Beijing 100871 China School of Physics Nankai University Tianjin 300071 China SJTU Paris Elite Insti

PandaX-4T experiment is a deep-underground dark matter direct search experiment that employs a dual-phase time projection chamber with a sensitive volume containing 3.7 tonne of liquid xenon. The detector of PandaX-4T is capable of simultaneously collecting the primary scintillation and ionization signals, utilizing their ratio to discriminate dark matter signals from background sources such as gamma rays and beta particles. The signal response model plays a crucial role in interpreting the data obtained by PandaX-4T. It describes the conversion from the deposited energy by dark matter interactions to the detectable signals within the detector. The signal response model is utilized in various PandaX-4T results. This work provides a comprehensive description of the procedures involved in constructing and parameter-fitting the signal response model for the energy range of approximately 1 keV to 25 keV for electronic recoils and 6 keV to 90 keV for nuclear recoils. It also covers the signal reconstruction, selection, and correction methods, which are crucial components integrated into the signal response model.

关键词： Particle dark matter Particle data analysis

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Determination of responses of liquid xenon to low energy electron and nuclear recoils using a PandaX-Ⅱ detector

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Chinese Physics C 2021年第7期45卷 273-282页

作者： Binbin Yan Abdusalam Abdukerim Wei Chen Xun Chen Yunhua Chen Chen Cheng Xiangyi Cui Yingjie Fan Deqing Fang Changbo Fu Mengting Fu Lisheng Geng Karl Giboni Linhui Gu Xuyuan Guo Ke Han Changda He Di Huang Peiyao Huang Yan Huang Yanlin Huang Zhou Huang Xiangdong Ji Yonglin Ju Shuaijie Li Jianglai Liu Zhuoqun Lei Wenbo Ma Yugang Ma Yajun Mao Yue Meng Kaixiang Ni Jinhua Ning Xuyang Ning Xiangxiang Ren Changsong Shang Lin Si Guofang Shen Andi Tan Anqing Wang Hongwei Wang Meng Wang Qiuhong Wang Siguang Wang Wei Wang Xiuli Wang Zhou Wang Mengmeng Wu Shiyong Wu Weihao Wu Jingkai Xia Mengjiao Xiao Pengwei Xie Rui Yan Jijun Yang Yong Yang Chunxu Yu Jumin Yuan Ying Yuan Jianfeng Yue Xinning Zeng Dan Zhang Tao Zhang Li Zhao Qibin Zheng Jifang Zhou Ning Zhou Xiaopeng Zhou School of Physics and Astronomy Shanghai Jiao Tong UniversityMOE Key Laboratory for Particle Astrophysics and CosmologyShanghai Key Laboratory for Particle Physics and CosmologyShanghai 200240China Shanghai Institute of Applied Physics Chinese Academy of SciencesShanghai 201800China Key Laboratory of Nuclear Physics and Ion-beam Application(MOE) Institute of Modern PhysicsFudan UniversityShanghai 200433China Shanghai Jiao Tong University Sichuan Research Institute Chengdu 610213China Yalong River Hydropower Development Company Ltd.288 Shuanglin RoadChengdu 610051China School of Physics Sun Yat-Sen UniversityGuangzhou 510275China Tsung-Dao Lee Institute Shanghai 200240China School of Physics Nankai UniversityTianjin 300071China School of Physics Peking UniversityBeijing 100871China School of Physics Beihang UniversityBeijing 100191China International Research Center for Nuclei and Particles in the Cosmos&Beijing Key Laboratory of Advanced Nuclear Materials and Physics Beihang UniversityBeijing 100191China School of Medical Instrument and Food Engineering University of Shanghai for Science and TechnologyShanghai 200093China Department of Physics University of MarylandCollege ParkMaryland 20742USA School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Physics and Key Laboratory of Particle Physics and Particle Irradiation(MOE) Shandong UniversityJinan 250100China Shanghai Advanced Research Institute Chinese Academy of SciencesShanghai 201210China Center for High Energy Physics Peking UniversityBeijing 100871China

We present a systematic determination of the responses of PandaX-Ⅱ,a dual phase xenon time projection chamber detector,to low energy *** electron recoil(ER) and nuclear recoil(NR) responses are calibrated,respectively,with injected tritiated methane or 220Rn source,and with 241Am-Be neutron source,in an energy range from 1-25 keV(ER) and 4-80 keV(NR),under the two drift fields,400 and 317 V/*** empirical model is used to fit the light yield and charge yield for both types of *** best fit models can describe the calibration data *** systematic uncertainties of the fitted models are obtained via statistical comparison to the data.

关键词： dark matter liquid xenon time projection chamber calibration electron recoil nucleon recoil NEST2.0

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Cyclicalnet: Modeling Temporal Dependencies with 2d Shifts for Exploring Underlying Patterns in Sequential Vibration Signals

SSRN

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SSRN 2023年

作者： Xu, Chaojun Chen, Peng Li, Zheng Ma, Zhigang Zhou, Chengning College of Engineering Shantou University 243 Daxue Road Jingping District Guangdong Shantou515063 China Key Laboratory of Intelligent Manufacturing Technology Ministry of Education 243 Daxue Road Jingping District Guangdong Shantou515063 China Business School The University of Sydney Abercrombie Building H70 Corner Abercrombie Street and Codrington St Darlington SydneyNSW2006 Australia Nuclear Power Institute of China 328 Changshun Road Shuangliu District Chengdu610213 China

Planetary gearboxes are vital parts of wind turbines, but they are vulnerable to failure from problems such as complex vibrations caused by changing loads, harsh operating environments, contamination, and other factors. As a result, developing effective fault diagnosis methods for planetary gearboxes is crucial. Deep learning models, especially artificial general architectures like Transformers, ResNets, DenseNets, and GANs, have shown promise in capturing intricate patterns in time series data to achieve fault diagnosis tasks. However, one-dimensional convolution kernels have limited scope, as they can only capture patterns from neighboring time series points. Moreover, attention mechanisms-based methods also face difficulties in identifying consistent dependencies among sparse points hidden within complex patterns. To address these challenges, this paper proposes a novel architecture, Cyclicalnet, designed to capture the inherent cyclicity and complex temporal fluctuations within vibration signals, thus enhancing fault diagnosis and predictive maintenance strategies. The proposed architecture leverages cyclical components, embeddings, and a densely connected manner. First, it takes the top amplitude-frequency components from vibration signals as input to cyclical blocks, unlike traditional methods. Then, position and token embeddings are incorporated to capture and encode the sequential nature of the vibration signals. The position embeddings help comprehend the various locations and sequential structure, while the token embeddings focus on conveying the different components or tokens within the signal. By combining token and position embeddings, the embedding block generates a comprehensive representation of the sequence, benefiting downstream tasks relying on this input. Next, a reshape operation that facilitates subsequent 2D-Net feature extraction transforms the 1D sequential representation into 2D maps. Furthermore, dense connections between blocks explore un

关键词： Failure analysis

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Extraction of offshore navigation characteristics based on crossing-line analysis

Extraction of offshore navigation characteristics based on c...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Wanbing Song Yongjie Zhu Yi Zuo Tieshan Li C.L. Philip Chen Navigation College Dalian Maritime University Dalian China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

The offshore channel is an important stage of preparation for the docking because it exists a higher frequency of ship traffic accidents. The analysis of channel is a critical premise for ship risk assessment and an indispensable part for improving the efficiency of shipping management. A channel analysis based on crossing-line has been widely used in inland channel research, but it is seldom in offshore one. In order to reasonably analyze the navigation characteristics of offshore ships and provide a basis for an effective simulation of offshore navigation traffic model, a modified crossing-line analysis for offshore channel based on Automatic identification system (AIS) data is proposed. Our method is applied to the offshore channel analysis of Dalian Port, and its results show that this method has smaller statistical error in the analysis of curved channel and sector channel, which is effective to analyze the navigation characteristics of offshore channel. The proposed method could be used to simulate the ship speed model on the offshore curved channel and establish an intelligent channel system to optimize the ship tracking path.

关键词： Analytical models Navigation Statistical analysis Data models Risk management Marine vehicles Artificial intelligence

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Predicting Ship Fuel Consumption based on LSTM Neural Network

Predicting Ship Fuel Consumption based on LSTM Neural Networ...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yongjie Zhu Yi Zuo Tieshan Li Navigation College Dalian Maritime University Dalian China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728162461

ISBN: (纸本)9781665419352

With the rapid development of marine trade and transportation, a large number of ships sail at sea. The ship energy conservation and environment protection are becoming public interested problems. Precise prediction of ship fuel consumption is vital for controlling emissions from ships. Some scholars used regression analysis to interpret the relations between fuel consumption and its influence factors. However, considering that there are a large amount of influence factors affecting ship fuel consumption, such as pitch, ship speed, wind and wave, some machine learning models are employed. While, ship fuel consumption data is time-related. A time series problem arises. The regression analysis and machine learning models cannot capture the time series characteristics. Therefore, LSTM neural network is applied in this paper. Experimentally, we compared LSTM with three traditional machine learning models, namely linear regression (LR), support vector regression (SVR), and artificial neural network (ANN). It found that the prediction accuracy can be improved with 11.8% compared with artificial neural network. The LSTM model can catch the time series characteristics of fuel consumption data and get a higher accuracy.

关键词： Computational modeling Time series analysis Machine learning Predictive models Data models Fuels Marine vehicles

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