检索结果-内蒙古大学图书馆

Chinese control and Decision Conference, CCDC

作者： Zhuang Li Jianqi An Yunpeng Guo Guoyu Zhao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Wuhan China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

The gas utilization ratio (GUR) in a blast furnace is directly linked to the efficiency, cost-effectiveness and environmental impact on the blast furnace ironmaking process. However, The stability of the published GUR time series prediction models need to be improved. This paper presents an improved particle swarm optimization (PSO) incorporating linearly decreasing inertia weights (LDIW) to optimize the kernel-based extreme learning machine (KELM) for single-step prediction. This paper uses singular spectrum analysis (SSA) to preprocess the data and extract the key components from the GUR time series to solve the problem of high volatility of the GUR time series. In addition, this paper introduces LDIW to improve the optimization ability of particle swarm optimization algorithm, which enhances the stability of a single-step prediction model. Then this paper uses the improved PSO algorithm to extract the optimal parameters of KELM, and establishes a single-step GUR prediction model based on the improved PSO-KELM. Finally, this paper uses the actual production process data of blast furnace to verify the prediction model. The results show that the prediction accuracy of GUR and the overall stability of the model are significantly improved, providing important guidance for the blast furnace ironmaking process.

关键词： Extreme learning machines Time series analysis Production Predictive models Blast furnaces Prediction algorithms Stability analysis

来源：评论

学校读者我要写书评

暂无评论

An Informer Based Alarm Early Prediction Method Over Consecutive Alarm Monitoring Periods

An Informer Based Alarm Early Prediction Method Over Consecu...

引用

IEEE International Conference on Industrial Informatics (INDIN)

作者： Wenbin Jiang Wenkai Hu Zhe Liu Fei Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China SINOPEC-SK (WUHAN) Petrochemical Company Limited Wuhan China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Alarm systems serve as the first layer of protection for modern process industries to monitor industrial processes and ensure operational safety. However, the presence of alarm floods is common in alarm systems and may distract operators from critical alarms. To provide decision supports to operators during alarm flood situations, alarm prediction becomes a potential effective solution. The difficulty of alarm prediction lies in how to achieve high prediction accuracy over long-term consecutive alarm monitoring periods, including situations with either high or low alarm rates. Consequently, this paper presents an industrial alarm prediction method for both alarm flood periods and non-alarm flood periods. Specifically, a strategy of combining fixed-length and fixed-time sliding windows is designed. Further, an alarm prediction model based on Informer is proposed for alarm prediction under different alarm rates. A case study is presented to prove the validity of the proposed alarm prediction method.

关键词： Industries Adaptation models Analytical models Accuracy Predictive models Alarm systems Floods Protection Informatics Monitoring

来源：评论

学校读者我要写书评

暂无评论

Causality Analysis and Modeling of Fuel Ratio Influencing Factors in Blast Furnace Ironmaking Process

Causality Analysis and Modeling of Fuel Ratio Influencing Fa...

引用

Asian control Conference

作者： Binjie Qian Weihua Cao Qifu Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Wuhan China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Blast furnace ironmaking is a key process in iron and steel production, and the fuel ratio has an important impact on the smelting efficiency, cost and environmental impact of the blast furnace. This study aims to provide new ideas and method-ological support for the optimized management and control of the blast furnace ironmaking process by exploring the effects of different factors on the fuel ratio. We firstly sorted out the factors affecting the fuel ratio based on the blast furnace process mechanism, and then deeply analyzed the causal relationship of each parameter on the fuel ratio based on the transfer entropy value, and screened out the parameters that did not have a significant effect on the fuel ratio. Taking the remaining key parameters as inputs, the LSTM and GRU models, which can capture time series information, are used to predict the mean and variance of the fuel ratio, respectively, and the two are combined to compute the final fuel ratio, which overcomes the problem of poor model generalization brought by small fluctuations in the training data of fuel ratio. The experimental results show that the convergence speed of the model is significantly improved after parameter screening, and the fuel ratio can be effectively predicted within a certain error range.

关键词： Computational modeling Time series analysis Smelting Process control Training data Predictive models Blast furnaces

来源：评论

学校读者我要写书评

暂无评论

Interfacial Thermal Transport and Energy Dissipation in Multilayer PdSe2 Field Effect Transistors

引用

Advanced Materials 2025年第0期 e2503264页

作者： Xie, Jiaqiu Yu, Zehao Sun, Yuanchen Gan, Qikang Liu, Chenhan Wang, Lei Zhang, Lifa Zhao, Yunshan Phonon Engineering Research Center of Jiangsu Province Ministry of Education Key Laboratory of NSLSCS Center for Quantum Transport and Thermal Energy Science Institute of Physics Frontiers and Interdisciplinary Sciences School of Physics and Technology Nanjing Normal University Nanjing210023 China National Laboratory of Solid-State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China Micro- and Nano-scale Thermal Measurement and Thermal Management Laboratory Jiangsu Key Laboratory for Numerical Simulation of Large-Scale Complex Systems School of Energy and Mechanical Engineering Nanjing Normal University Nanjing210046 China

The continuous miniaturization of 2D electronic circuits results in increased power density during device operation, leading to heat localization and placing higher demands on their performance thresholds. The risk to thermal breakdown and subsequent damage, due to the energy dissipation in the 2D semiconductor field-effect transistors (FETs) supported on the bulk substrates, represents a significant challenge in maintaining their optimal performance. Herein, this study investigates energy dissipation behavior in multilayer PdSe2 FETs for the first time. The high-field breakdown behavior is firstly studied in multilayer PdSe2 FETs on SiO2/Si substrates, where a maximum current density of ≈2.74 MA cm−2 is observed, which is comparable to that of multilayer black phosphorus FET and significantly higher—by about five times—than that of multilayer MoS2 FET. Additionally, the thermal boundary conductance (TBC) of PdSe2/SiO2 interface is measured at room temperature using Raman thermometry. The TBC is found to be ≈12–13 MW m−2 K−1, which is relatively low compared to the other known solid–solid interfaces, indicating that enhancing the performance of PdSe2 FETs can be possible by optimizing the TBC at the PdSe2/SiO2 interface. These findings provide valuable insights for design of high-quality and high-performance PdSe2 electronic and optoelectronic devices. © 2025 Wiley-VCH GmbH.

关键词： Multilayers

来源：评论

学校读者我要写书评

暂无评论

Additive manufacturing of silicon carbide microwave-absorbing metamaterials

引用

Additive Manufacturing Frontiers 2025年第1期4卷

作者： Zhao, Hanqing Liao, Qingwei Li, Yinghao Chu, Xiangcheng Yuan, Songmei Qin, Lei Key Laboratory of Sensors Beijing Information Science and Technology University Beijing 100192 China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing 100192 China State Key Laboratory of New Ceramics and Fine Processing School of Material Science and Engineering Tsinghua University Beijing 100084 China School of Mechanical Engineering and Automation Beihang University Beijing 100191 China

SiC is a wave-absorbing material with good dielectric properties, high-temperature resistance, and corrosion resistance, which has great potential for development in the field of high-temperature wave-absorbing. However, SiC is limited by its low impedance-matching performance and single wave-absorbing mechanism. Therefore, compatible metamaterial technologies are required to enhance its wave-absorbing performance further. The electromagnetic wave (EMW) absorbing metamaterials can realize perfect absorption of EMWs in specific frequency bands and precise regulation of EMW phase, propagation mode, and absorption frequency bands through structural changes. However, the traditional molding methods for manufacturing complex geometric shapes require expensive molds, involve process complexity, and have poor molding accuracy and other limitations. Therefore, additive manufacturing (AM) technology, through material layered stacking to achieve the processing of materials, is a comprehensive multidisciplinary advanced manufacturing technology and has become the core technology for manufacturing metamaterials. This review introduces the principles and applications of different AM technologies for SiC and related materials, discusses the current status and development trends of various AM technologies for fabricating silicon–carbon-based wave-absorbing metamaterials, summarizes the limitations and technological shortcomings of existing AM technologies for fabricating silicon–carbon-based wave-absorbing metamaterials, and provides an outlook for the future development of related AM technologies. © 2024 The Author(s)

关键词： Additive manufacturing Electromagnetic absorption Metamaterials SiC

来源：评论

学校读者我要写书评

暂无评论

A new result for H∞ performance analysis of sampled-data systems via looped-functionals

A new result for H∞ performance analysis of sampled-data sy...

引用

第41届中国控制会议

作者： Du Xiong Wen-Hu Chen Yong-He Lao Yu-Long Fan Chuan-Ke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

This paper is concerned with H performance analysis of aperiodic sampled-data systems by employing the input delay ***,a novel augmented looped-functional（ALF） is presented under the double-side looped-functional technique,which considers coupled relationships among state vectors more fully than the current ***,by using the BesselLegendre inequality to estimate the derivative of the ALF,a stability criterion is derived in the form of linear matrix ***,a numerical example demonstrates the effectiveness and the advantages of the proposed criterion by comparing it with the existing ones.

关键词： Aperiodic sampled-data systems Stability analysis Input delay approach H_∞ performance Bessel-Legendre inequality

来源：评论

学校读者我要写书评

暂无评论

Surface Defect Detection of Sanitary Ceramic Product Utilizing High-resolution Image on Two Different Scales

Surface Defect Detection of Sanitary Ceramic Product Utilizi...

引用

第34届中国控制与决策会议

作者： Xing-ao Wang Jianqi An Yisheng Mei Xin Chen Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Surface defect detection of sanitary ceramic products is an important part of the production *** deep learning method is the mainstream research direction in the field of defect *** there are many small defects on the surface of sanitary ceramic products,it is an effective means to use a high-resolution camera to obtain *** detection speed of high-resolution pictures and the interference of background are the difficult problems in ***,this paper designs a two-scale detection framework to detect and locate defects of sanitary ceramics utilizing high-resolution *** two-scale detection framework speeds up the detection of high-resolution images and weakens the interference of the background by dividing the defect detection task into two parts,a workpiece region recognition task on large scale and a defect detection task on small *** experiments show that the two-scale detection method has a better detection speed and accuracy rate compared with the single-scale method,which proves the superiority of the proposed method.

关键词： Defect detection Two-scale detection Deep learning

来源：评论

学校读者我要写书评

暂无评论

Design of a Novel Autonomous Docking System With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Huijie Dong Chunyang Zhao Tiezhu Qiao Jian Wang Di Chen Yan Meng Junzhi Yu Ministry of Education Key Laboratory of Advanced Transducers and Intelligent Control System Taiyuan University of Technology Taiyuan China Institute of Automation Laboratory of Cognitive and Decision Intelligence for Complex System Chinese Academy of Sciences Beijing China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China College of Electronics and Information Engineering Guangdong Ocean University Zhanjiang China

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named ‘CourierFish’. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Revealing the structure and distribution changes of corn stalk lignin during the Organosolv Pretreatment

引用

Industrial Crops and Products 2023年第1期201卷

作者： Li, Xu Xia, Ying Hu, Xiaohong Liu, Qiying Li, Wenzhi Yan, Long Ma, Longlong Department of Thermal Science and Energy Engineering University of Science and Technology of China Hefei230026 China Key Laboratory of Energy Thermal Conversion and Process Measurement and Control of Ministry of Education School of Energy and Environment Southeast University Jiangsu Nanjing210096 China CAS Key Laboratory of Renewable Energy Guangzhou Institute of Energy Conversion Chinese Academy of Sciences Guangzhou510640 China

During the pretreatment of biomass, the research on the migration process of lignin in the cell wall and the change of chemical structure is very important for improving pretreatment and subsequent lignin upgrading. Hence, corn stalk lignin was extracted by 1, 4-dioxane organosolv system under mild conditions with varying pretreatment time and 0.1 M hydrochloric acid as catalyst. The heterogeneity of lignin removal in the different morphological areas of the cell wall was revealed by advanced imaging techniques. Results indicated that during the pretreatment with dioxane organosolv, the removal of lignin started from the secondary wall of the cell wall, and gradually developed outward to the compound middle lamella. Meanwhile, the resulting lignin obtained through different pretreatment times was characterized by two-dimensional heteronuclear single quantum coherence spectroscopy (2D-HSQC) and gel permeation chromatography (GPC). These characterization results indicated that there were more syringyl (S) units in the lignin that were removed first, and the proportion of guaiacyl (G) units was increased as the pretreatment continued. All the evidence supports the idea that the main reason for the significant differences in lignin structures at various periods of the lignin removal process is that the lignin come from different cell wall regions. © 2023

关键词： Lignin

来源：评论

学校读者我要写书评

暂无评论

A Multi-feature Extraction-based Image Identification Method for Rock Debris in The Drilling Process

A Multi-feature Extraction-based Image Identification Method...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Xu, Pengju Gan, Chao Wang, Luzhao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China No.3 Exploration Institute of Geology and Mineral Resources of Shandong Province Yantai264000 China

ISBN: (纸本)9781665465335

In this paper, a multi-feature extraction-based image identification method for rock debris in the drilling process is proposed, involving three main parts (trainable feature extractor, strong feature extraction, and classification). In trainable feature extractor, abstract features are obtained by extracting the full connection layer of Convolutional Neural Network (CNN). In strong feature extraction, the method uses Gray-Level Co-occurrence Matrix (GLCM) and Color Coherence Vector (CCV) to get the strong feature. In classification, the extracted abstract features and strong features are concatenated and fed into the Support Vector Machine (SVM). Comparison results with two well-known methods indicated the effectiveness of the proposed method. © 2022 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：