检索结果-内蒙古大学图书馆

2023 China Automation Congress, CAC 2023

作者： Zhang, Enhao Zhu, Haibo Zhou, Fan Zhao, Jun Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350303759

The complex process mechanism of fluid catalytic cracking (FCC) and the strong nonlinearity of multi-variable coupling bring significant challenges to the model predictive control (MPC) of FCC production process models. This study presents a modeling method of FCC system based on improved extreme learning machine Hammerstein (IELM-Hammerstein). Aiming at the nonlinear characteristics of FCC process, the Hammerstein model's static nonlinear subsystem is constructed using an extreme learning machine (ELM). Considering the instability of the algorithm caused by random weights and thresholds in the ELM, the sparrow search algorithm (SSA) is adopted to calculate the parameters, then one recursive least square (RLS) method is derived from calculating the linear subsystem regression parameters of Hammerstein model. To prove the effectiveness of this method, the comparative experiments with the traditional identification method are carried out, and this method is applied to modeling and control of the fractionating system in a petroleum refinery. The experimental results indicates that the proposed method guarantees the modeling accuracy of the fractionating system, and improves the tracking control performance. © 2023 IEEE.

关键词： Fluid catalytic cracking

来源：评论

学校读者我要写书评

暂无评论

Coupling pinch analysis and rigorous process simulation for hydrogen networks with light hydrocarbon recovery

引用

Chinese Journal of Chemical Engineering 2021年第12期34卷 141-148页

作者： Minbo Yang Xiao Feng Liang Zhao Shaanxi Key Laboratory of Energy Chemical Process Intensification School of Chemical Engineering and TechnologyXi’an Jiaotong UniversityXi'an 710049China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and TechnologyMinistry of EducationShanghai 200237China

In refineries,some hydrogen-rich streams contain considerable light hydrocarbons that are important raw materials for the chemical *** hydrogen networks with light hydrocarbon recovery can enhance the reuse of both hydrogen and light *** work proposes an automated method for targeting hydrogen networks with light hydrocarbon recovery.A pinch-based algebraic method is improved to determine the minimum fresh hydrogen consumption and hydrogen sources fed into the light hydrocarbon recovery unit *** process simulation is conducted to determine the mass and energy balances of the light hydrocarbon recovery *** targeting procedures are developed through combination of the improved pinch method and rigorous process *** hybrid method is realized by coupling the Matlab and Aspen HYSYS platforms.A refinery hydrogen network is analyzed to illustrate application of the proposed *** integration of hydrogen network with light hydrocarbon recovery further reduces fresh hydrogen requirement by463.0 m^(3)·h^(-1) and recovers liquefied petroleum gas and gasoline of 1711.5 kg·h^(-1) and 643 kg·h^(-1),respectively.A payback period of 9.2 months indicates that investment in light hydrocarbon recovery is economically attractive.

关键词： Hydrogen Light hydrocarbon recovery Pinch technology Simulation Systems engineering

来源：评论

学校读者我要写书评

暂无评论

RBFNN-Based ADRC Design for Continuous-Time Systems with Unknown Nonlinear Dynamics Subject to Time-Varying Disturbance 42

RBFNN-Based ADRC Design for Continuous-Time Systems with Unk...

引用

42nd Chinese control Conference, CCC 2023

作者： Yan, Shuai Hao, Shoulin Yu, Haichen Liu, Tao Yan, Bin Gong, Yihui Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Institute of Advanced Control Technology Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

In this paper, a radial basis function neural network (RBFNN) based active disturbance rejection control (ADRC) scheme is proposed for continuous-time systems with unknown nonlinear dynamics and time-varying disturbance. By using RBFNN to online approximate the unknown nonlinear dynamics, a novel nonlinear extended state observer (ESO) is firstly designed to estimate the total disturbance consisting of time-varying external disturbance and RBFNN approximation error. Then, an anti-disturbance feedback control law together with a tracking differentiator is designed to counteract the total disturbance in a feedforward manner. The bounded convergence of the closed-loop system and ESO as well as the estimation errors of the weighting vector are rigorously analyzed based on the Lyapunov stability theory. A case study is carried out to demonstrate the effectiveness and merit of the proposed design, in contrast to the conventional ADRC. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Immoral post detection using a one-dimensional convolutional neural network-based LSTM network

引用

Multimedia Tools and Applications 2025年 1-20页

作者： Saqia, Bibi Khan, Khairullah Rahman, Atta Ur Khan, Aurangzeb Jain, Deepak Kumar Department of Computer Science University of Science and Technology Bannu28100 Pakistan Riphah Institute of Systems Engineering Riphah International University Islamabad46000 Pakistan Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China Symbiosis Institute of Technology Symbiosis International University Pune India

In text mining and Natural Language processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has compelled the advancement of more sophisticated methods for the automatic identification of unwanted content. The One-Dimensional Convolutional Neural Network (1D-CNN) performs best for feature extraction, while the Long Short-Term Memory Network (LSTM) is well-known for extracting sequential features and classification of textual data. This study proposes a novel solution by combining 1D-CNN with LSTM. Utilizing a context-aware model, this study aims to enhance the detection of immoral posts, including hate speech and other forms of immoral content on social media platforms. Various posts are extracted from social media, which are then processed using Glove word embedding models. It depicts the word representations in the text, which yields the form of a real-valued vector determining the words' meaning. The 1D convolution utilizes a filter window over the input time-series data to extract features. Relying on the acquired parameters of the filters, they act as feature extractors. This feature extraction technique allows the model to distinguish detailed patterns and nuances from the textual contents of posts. The sequential processing capabilities of the LSTM network enable an in-depth examination of the text, capturing temporal relationships and context, which is critical for successful content categorization. To validate the proposed model, we utilized a benchmark dataset, called the Twitter dataset. The proposed model achieved the highest accuracy of 95.37% and outperforms state-of-the-art works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Unbalanced few-shot classification based on ME-MAML framework 43

Unbalanced few-shot classification based on ME-MAML framewor...

引用

43rd Chinese control Conference, CCC 2024

作者： Liao, Zherun Lv, Zheng Sun, Qiao Zhao, Jun Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Electric Operations Control Center State Grid Dalian Power Supply Company Dalian China

ISBN: (纸本)9789887581581

Aiming at the few-shot problem of lack of sufficient samples and uneven samples, which is common in medical image classification tasks, this paper proposes a meta-learning framework ME-MAML (Medical ModelAgnostic Meta-Learning) for few-shot medical image classification tasks. The framework aims to train a set of parameters with good generalization performance for the multi-class medical image classification task by learning the base class of medical images, and complete the generalization for the new class of medical image classification task by learning a small number of new classes of medical images. ME-MAML improves the MAML (Model-Agnostic Meta-Learning) meta-learning framework from the aspects of the feature extraction network, the loss function and the algorithmic framework, which makes the framework more suitable for few-shot medical image classification tasks. The experimental results demonstrate that for few-shot medical image classification task, the framework has better classification performance compared to supervised learning frameworks as well as advanced meta-learning frameworks. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Geological modeling of coalbed methane reservoirs in the tectonically deformed coal seam group in the Dahebian block,western Guizhou,China

引用

Frontiers of Earth Science 2024年第1期18卷 44-67页

作者： Yong SHU Shuxun SANG Xiaozhi ZHOU Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process(Ministry of Education) China University of Mining and TechnologyXuzhou 221116China Carbon Neutrality Institute China University of Mining and TechnologyXuzhou 221008China School of Resources and Geosciences China University of Mining and TechnologyXuzhou 221116China Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization China University of Mining and TechnologyXuzhou 221008China

The widely spread Carboniferous-Permian coal seam group in southern China has great potential for coalbed methane resources,but the extensively developed tectonically deformed coal seriously restricts its *** the Dahebian block in western Guizhou as the study area,the geological model of coalbed methane reservoirs in the tectonically deformed coal seam group was established,and the spatial distribution pattern of model parameters was clarified by clustering algorithms and factor *** facies model suggests that the main coal body structures in Nos.1,4,and 7 coal seams are cataclastic coal and granulated coal,whereas the No.11 coal seam is dominated by granulated coal,which has larger thicknesses and spreads more *** in situ permeability of primary undeformed coal,cataclastic coal,granulated coal,and mylonitized coal reservoirs are 0.333 mD,0.931 mD,0.146 mD,and 0.099 mD,respectively,according to the production performance analysis *** property model constructed by facies-controlled modeling reveals that Nos.1,4,and 7 coal seams have a wider high-permeability area,but the gas content is lower;the high-permeability area in the No.11 coal seam is more limited,but the gas content is *** results of the self-organizing map neural network and K-means clustering indicate that the geological model can be divided into 6 clusters,the model parameter characteristics of the 6 clusters are summarized by data analysis in combination with 6 factors extracted by factor analysis,and the application of data analysis results in multi-layer coalbed methane co-development is *** study provides ideas for the geological modeling in the tectonically deformed coal seam group and its data analysis.

关键词： geological modeling tectonically deformed coal coal seam group clustering algorithm Dahebian block,western Guizhou

来源：评论

学校读者我要写书评

暂无评论

FATIGUE DAMAGE EVOLUTION ANALYSIS OF DRIVE SHAFT CONSIDERING RESIDUAL STRESS AND HARDNESS GRADIENT 10

FATIGUE DAMAGE EVOLUTION ANALYSIS OF DRIVE SHAFT CONSIDERING...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Yang, Li Wang, Liyong Li, Le Zheng, Xinhui Chang, Shuyuan Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Affiliation name of department and organisation Beijing China The Ministry of Education Key Laboratory of Modem Measurement and Control Technology Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

The service environment of the transmission shaft is complex, and it is frequently subjected to impact load. Impact fatigue is the main cause of its fatigue failure. In this study, a fatigue damage evolution analysis method of transmission shaft considering residual stress and hardness gradient is proposed under the framework of damage irreversible thermodynamics. Firstly, combined with the wave theory, the wave effect of impact stress wave is analyzed, the evolution equation of stress wave fluctuation behavior is established, and the evolution law of stress and strain field under the action of stress wave is analyzed. Then, based on the irreversible thermodynamic framework of damage, the thermodynamic state potential and dissipation potential of the damage process are studied, and the coupling characteristics of the damage evolution dynamic response and the intrinsic damage dissipation of the damaged material are analyzed. The damage evolution model of fatigue performance degradation considering residual stress and hardness gradient is established to identify the critical condition of intrinsic damage dissipation and describe the fatigue damage failure behavior. Finally, the cohesive element of the coupled damage constitutive is defined to simulate the damage evolution behavior of the substructure, and the influence of residual stress and hardness gradient on the damage evolution is explored. The results show that different initial crack forms have an important influence on the stress wave propagation behavior. The existence of residual tensile stress accelerates the process of fatigue damage accumulation, and the improvement of surface hardness can improve the fatigue resistance of the body. © The Institution of Engineering & technology 2024.

关键词： Fatigue damage

来源：评论

学校读者我要写书评

暂无评论

Two-Degree-of-Freedom control with Linear Extended State Observer for PMSM Drive System 41

Two-Degree-of-Freedom Control with Linear Extended State Obs...

引用

第41届中国控制会议

作者： Kai Lin Ping Lin Bin Yang School of Control Science and Engineering Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In permanent magnet synchronous motors(PMSM) drive system,it is difficult to achieve the optimal performance of command tracking and disturbance rejection simultaneously when the speed loop designed with the conventional one-degree-of-freedom(1-DOF) PI *** solve this problem,this paper proposes a speed control structure of two-degree-of-freedom(2-DOF) P-PI controller with linear extended state observer(LESO).There are two sets of parameters that can be designed independently in the controller,which improves the command tracking performance without degrading the disturbance rejection *** addition,a linear extended state observer(LESO) is designed to estimate the total disturbance in the speed *** to the estimated value,the output of the 2-DOF P-PI controller is compensated feedforward equivalently,which further enhances the disturbance rejection ***,simulations verify the effectiveness of the proposed control strategy.

关键词： permanent magnet synchronous motors(PMSM) two-degree-of-freedom(2-DOF)P-PI linear extended state observer(LESO) disturbance compensation

来源：评论

学校读者我要写书评

暂无评论

A Production Plan and Error Feedback DBN-DNN based prediction method for LDG Generation in steel industry 41

A Production Plan and Error Feedback DBN-DNN based predictio...

引用

第41届中国控制会议

作者： Xu Han Feng Jin Jun Zhao Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment (Dalian University of Technology) Ministry of Education School of Control Science and Engineering Dalian University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Linz Donawiz converter Gas(LDG) is a kind of important secondary energy source in iron and steel *** prediction of LDG generation may provide guidance for scheduling *** this paper,a two-stage method for predicting LDG generation is *** to the characteristics of LDG generation data,an improved k-means clustering integrating dynamic time warping is proposed to divide the time series data into typical characteristic ***,an error feedback deep belief network(EF-DBN-DNN) model is established to predict the starting time of LDG generation by considering the relationship between production plan and the actual performance,Actual data of LDG system in an iron and steel enterprise are employed to verify the effectiveness of the proposed method,and the results show that the prediction accuracy of the proposed one is suitable for practical application.

关键词： LDG generation production plan improved k-means clustering error feedback DBN-DNN

来源：评论

学校读者我要写书评

暂无评论

Transcriptome analysis and functional gene identification reveals potential mechanisms of heat stress response of Lactiplantibacillus plantarum CGMCC8198

引用

Food Bioscience 2023年第1期51卷 152-158页

作者： Jia-Yi Da Mao-Sheng Xi Han-Lu Li Min-Min Liu Cheng-Hui Zhou Zhong-Yuan Li Ya-Jian Song Sa Zhou Tong-Cun Zhang Xue-Gang Luo Key Laboratory of Industrial Fermentation Microbiology of the Ministry of Education and Tianjin Key Laboratory of Industrial Microbiology College of BiotechnologyTianjin University of Science and TechnologyTianjin300457China Tianjin Engineering Research Center of Microbial Metabolism and Fermentation Process Control Tianjin300457China

Lactiplantibacillus plantarum is an important probiotic bacterium and extensively applied to functional *** survival is strongly affected by the heat-shock process during *** is thought to be able to enhance bacteria resistance to heat *** this study,the results of transcriptomics and bioinformatics analysis showed that alcohol dehydrogenase adhE-like,phosphoribose-ATP pyrophosphatase hisE,flavodoxin ykuN,and dihydropterin aldolase folB might be related with heat resistance of *** ***,after these genes were expressed in Escherichia coli,survival rate,hydrophobicity and membrane integrity of the recombinant bacteria under high temperature were also significantly ***,by screening the strains after multiple rounds of acclimation,a strain(XH)with better heat tolerance was obtained,and the results of qRT-PCR showed that these four genes,especially hisE,were upregulated in the acclimated strain when it was treated with high *** findings indicated that adhE-like and some other potential genes could improve the heat resistance of lactic acid bacteria,and might be used as indicators for screening of heat-tolerant probiotics strains.

关键词： Probiotic Heat stress Functional genes Acclimation

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：