检索结果-内蒙古大学图书馆

Mesoporous molecular sieve-based materials for catalytic oxidation of VOC: A review

Journal of Environmental sciences 2023年第3期125卷 112-134页

作者： Wei Gao Xiaolong Tang Honghong Yi Shanxue Jiang Qingjun Yu Xizhou Xie Ruijie Zhuang Department of Environmental Science and Engineering School of Energy and Environmental EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Environmental Protection Key Laboratory of Food Chain Pollution Control Beijing Technology and Business UniversityBeijing 100048China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants Beijing 100083China

As the main contributor of the formation of particulate matter as well as ozone, volatile organic compounds(VOCs) greatly affect human health and the environmental quality. Catalytic combustion/oxidation has been viewed as an efficient, economically feasible and environmentally friendly way for the elimination of VOCs. Supported metal catalyst is the preferred type of catalysts applied for VOCs catalytic combustion because of the synergy between active components and support as well as its flexibility in the composition. The presence of support not only plays the role of keeping the catalyst with good stability and mechanical strength, but also provides a large specific surface for the good dispersion of active components, which could effectively improve the performance of catalyst as well as decrease the usage of active components, especially the noble metal amount. Mesoporous molecular sieves, owing to their large surface area, unique porous structures, large pore size as well as uniform pore-size distribution, were viewed as superior support for dispersing active components. This review focuses on the recent development of mesoporous molecular sieve supported metal catalysts and their application in catalytic oxidation of VOCs. The effect of active component types, support structure, preparation method, precursors, etc. on the valence state, dispersion as well as the loading of active species were also discussed and summarized. Moreover, the corresponding conversion route of VOCs was also *** review aims to provide some enlightment for designing the supported metal catalysts with superior activity and stability for VOCs removal.

关键词： Volatile organic compound Mesoporous molecular sieves Supported catalyst Catalytic oxidation Reaction mechanism Influencing factors

来源：评论

学校读者我要写书评

暂无评论

A Neural Additive Domain Adaptation Network with Interpretability for Fault Detection in Various Operating Conditions 25

A Neural Additive Domain Adaptation Network with Interpretab...

引用

25th IEEE International Conference on industrial technology, ICIT 2024

作者： Su, Cheng Zhong, Weimin Yang, Dan Li, Linlin Peng, Xin East China University Of Science And Technology State Key Laboratory Of Industrial Control Technology Shanghai China East China University Of Science And Technology Key Laboratory Of Smart Manufacturing In Energy Chemical Process Shanghai China University Of Science And Technology Beijing Department Of Control Science And Engineering Beijing China

ISBN: (纸本)9798350340266

Domain adaptation (DA) can be used for fault detection under multiple operating conditions. However, the lack of interpretability of DA models prevents potential users from understanding the decisions made by models. To give a solution, a neural additive domain adaptation network (NADAN) is proposed, which is constructed based on a neural additive model (NAM). Benefiting from the structural advantages of NAM, the predictions of NADAN are interpretable. Specifically, NADAN is able to explain how each feature affects the decision of the model. In addition, NADAN consists of two modules, feature learning (FL) and domain adaptation (DA), and achieves domain alignment through the combination of FL and DA. The FL module is pretrained to learn high-order features. The DA module takes learned features as input and achieves domain alignment based on multi-kernel maximum mean discrepancy (MK-MMD). Compared to the raw data, the learned features are more task-relevant, which helps to improve the performance of NADAN on DA. Furthermore, NADAN augments the feature dimensions during DA to measure the inter-domain differences in detail, which in turn achieves better domain alignment. Experiments on datasets generated from wastewater treatment simulation model demonstrate the effectiveness of the proposed NADAN. © 2024 IEEE.

关键词： Additives

来源：评论

学校读者我要写书评

暂无评论

ZSEE: A Dataset based on Zeolite Synthesis Event Extraction for Automated Synthesis Platform

ZSEE: A Dataset based on Zeolite Synthesis Event Extraction ...

引用

2024 Findings of the Association for Computational Linguistics: NAACL 2024

作者： He, Song Peng, Xin Cai, Yihan Li, Xin Yuan, Zhiqing Du, Wenli Yang, Weimin State Key Laboratory of Industrial Control Technology East China University of Science and Technology China State Key Laboratory of Green Chemical Engineering and Industrial Catalysis Sinopec Shanghai Research Institute of Petrochemical Technology China

ISBN: (纸本)9798891761193

Automated synthesis of zeolite, one of the most important catalysts in chemical industries, holds great significance for attaining economic and environmental benefits. Structural synthesis data extracted through NLP technologies from zeolite experimental procedures can significantly expedite automated synthesis owing to its machine readability. However, the utilization of NLP technologies in information extraction of zeolite synthesis remains restricted due to the lack of annotated datasets. In this paper, we formulate an event extraction task to mine structural synthesis actions from experimental narratives for modular automated synthesis. Furthermore, we introduce ZSEE, a novel dataset containing fine-grained event annotations of zeolite synthesis actions. Our dataset features 16 event types and 13 argument roles which cover all the experimental operational steps of zeolite synthesis. We explore current state-of-the-art event extraction methods on ZSEE, perform error analysis based on the experimental results, and summarize the challenges and corresponding research directions to further facilitate the automated synthesis of zeolites. The code is publicly available at https://***/Hi-0317/ZSEE. © 2024 Association for Computational Linguistics.

关键词： Zeolites

来源：评论

学校读者我要写书评

暂无评论

Design of recognition algorithm for multiclass digital display instrument based on convolution neural network

引用

Biomimetic Intelligence & Robotics 2023年第3期3卷 67-74页

作者： Xuanzhang Wen Yuxia Wang Qiuguo Zhu Jun Wu Rong Xiong Anhuan Xie Polytechnic Institute Zhejiang UniversityHangzhou 310015China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Industrial Control and Technology Zhejiang UniversityHangzhou 310027China Zhejiang Lab Hangzhou 311121China

Digital display instrument identification is a crucial approach for automating the collection of digital display *** this study,we propose a digital display area detection CTPNpro algorithm to address the problem of recognizing multiclass digital display *** developed a multiclass digital display instrument recognition algorithm by combining the character recognition network constructed using a convolutional neural network and bidirectional variable-length long short-term memory(LSTM).First,the digital display region detection CTPNpro network framework was designed based on the CTPN network architecture by introducing feature fusion and residual ***,the digital display instrument identification network was constructed based on a convolutional neural network using twoway LSTM and Connectionist temporal classification(CTC)of indefinite ***,an automatic calibration system for digital display instruments was built,and a multiclass digital display instrument dataset was constructed by sampling in the *** compared the performance of the CTPNpro algorithm with other methods using this dataset to validate the effectiveness and robustness of the proposed algorithm.

关键词： Multiclass display instrument Digital display area detection Character recognition Convolutional neural network Characteristics of the fusion

来源：评论

学校读者我要写书评

暂无评论

RoG-SAM: A Language-Driven Framework for Instance-Level Robotic Grasping Detection

引用

IEEE Transactions on Multimedia 2025年 27卷 3057-3068页

作者： Mei, Yunpeng Sun, Jian Peng, Zhihong Deng, Fang Wang, Gang Chen, Jie Beijing Institute of Technology State Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Tongji University Department of Control Science and Engineering Shanghai201804 China

Robotic grasping is a crucial topic in robotics and computer vision, with broad applications in industrial production and intelligent manufacturing. Although some methods have begun addressing instance-level grasping, most remain limited to predefined instances and categories, lacking flexibility for open-vocabulary grasp prediction based on user-specified instructions. To address this, we propose RoG-SAM, a language-driven, instance-level grasp detection framework built on Segment Anything Model (SAM). RoG-SAM utilizes open-vocabulary prompts for object localization and grasp pose prediction, adapting SAM through transfer learning with encoder adapters and multi-head decoders to extend its segmentation capabilities to grasp pose estimation. Experimental results show that RoG-SAM achieves competitive performance on single-object datasets (Cornell and Jacquard) and cluttered datasets (GraspNet-1Billion and OCID), with instance-level accuracies of 91.2% and 90.1%, respectively, while using only 28.3% of SAM's trainable parameters. The effectiveness of RoG-SAM was also validated in real-world environments. © 1999-2012 IEEE.

关键词： Robot vision

来源：评论

学校读者我要写书评

暂无评论

A Novel Point Cloud Deep Learning Method for Predicting Variable Airfoil Flow Fields 43

A Novel Point Cloud Deep Learning Method for Predicting Vari...

引用

43rd Chinese control Conference, CCC 2024

作者： Zhang, Xinyao Cao, Junzhe Dalian University of Technology Control Science and Engineering Dalian116024 China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China

ISBN: (纸本)9789887581581

Airfoil flow field is of great significance to the design optimization of aircraft shape. Convolutional Neural Networks (CNNs) have been applied in flow field prediction studies, which greatly reduce the cost of computation time in traditional Computational Fluid Dynamics (CFD) methods. However, such CNN-based approaches normally bring extra errors due to the procedure of interpolating irregular grid data into Cartesian grids, which may lead to underperforming prediction accuracy. In this paper, an improved PointNet++ point cloud deep learning method was proposed for the airfoil flow field prediction. The unstructured grid vertices in the CFD domain were treated as point cloud as well as the input of neural network, and only the original information of the data was adopted to avoid interpolation. Neighborhood relationship features were defined and spliced with neighborhood point features, and the features were integrated by simultaneously solving for the maximum, minimum, sum, and average values to extract the local or global features of the system to enhance the performance of deep network for extracting the information. Finally, the proposed network was trained and tested by using 549 sets of flow field data formed by 61 airfoils under 9 angle-of-attack conditions, and further predicted for an additional 32 datasets with different airfoils and conditions. The simulation results show that the method proposed in this study gets lower prediction errors in terms of pressure, Mach number, x-direction velocity, and y-direction velocity than the two other current point cloud deep networks, PointNet and PointNet++. At the same time, the computation speed of this method is about 14 times faster than the traditional CFD method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Computational fluid dynamics

来源：评论

学校读者我要写书评

暂无评论

Scheduling Optimization of Coal Washing Process Based on Two-Stage Fuzzy Heuristic Algorithm 13

Scheduling Optimization of Coal Washing Process Based on Two...

引用

13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Zhou, Hui Wang, Zhiyuan Han, Zhongyang Wang, Linqing Zhao, Jun Wang, Wei Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9798350361674

Coal washing and sorting plays a vital role for coal production. Reasonable scheduling of washing and sorting equipment, crushers and various coal silos in the coal washing and sorting process can effectively increase the total value of product coal and reduce the total energy consumption of equipment. In this paper, a multi-constrained nonlinear mixed integer programming model considering the start and stop of each equipment in the washing process is established to realize the specific regulation of the washing process. In order to overcome the problem such as local convergence when solving high-dimensional space problems, a two-stage fuzzy heuristic algorithm is proposed in this paper. In the first stage, a variety of population genetic algorithms based on fuzzy adaptive strategy control are designed for global search to establish an elite population bank to preserve high-quality individuals produced by various groups. In the second stage, an improved simulated annealing algorithm is used to perform a local search with a backtracking process on specific neighbors of individuals in the elite population bank, which can improve the stability of the algorithm and reduce the situation of falling into local convergence. Then the real data of a Chinese coal mining company was used for experiments, where the proposed algorithm is compared with other commonly used methods. The experimental results demonstrate that the proposed algorithm can increase the total coal value of the washed product by at least 1.7% compared to other algorithms, and the average total number of starts and stops of the equipment is reduced by about 7.3%, which are effectively beneficial for the related enterprise. © 2024 IEEE.

关键词： Coal mines

来源：评论

学校读者我要写书评

暂无评论

Modeling and Prediction of Fatigue Properties of Additively Manufactured Metals

引用

Acta Mechanica Solida Sinica 2023年第2期36卷 181-213页

作者： Wei Tang Ziming Tang Wenjun Lu Shuai Wang Min Yi State Key Lab of Mechanics and Control of Mechanical Structures&Institute for Frontier Science&Key Lab for Intelligent Nano Materials and Devices of Ministry of Education&College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics(NUAA)Nanjing 210016China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055China

Additive manufacturing(AM)has emerged as an advanced technique for the fabrication of complex near-net shaped and lightweight metallic parts with acceptable mechanical *** strength of AM metals has been confirmed comparable or even superior to that of metals manufactured by conventional processes,but the fatigue performance is still a knotty issue that may hinder the substitution of currently used metallic components by AM counterparts when the cyclic loading and thus fatigue failure *** essential complements to high-cost and time-consuming experimental fatigue tests of AM metals,models for fatigue performance prediction are highly *** this review,different models for predicting the fatigue properties of AM metals are summarized in terms of fatigue life,fatigue limit and fatigue crack growth,with a focus on the incorporation of AM characteristics such as AM defect and processing parameters into the *** predicting the fatigue life of AM metals,empirical models and theoretical models(including local characteristic model,continuum damage mechanics model and probabilistic method)are *** terms of fatigue limit,the introduced models involve the Kitagawa–Takahashi model,the Murakami model,the El-Haddad model,*** modeling the fatigue crack growth of AM metals,the summarized methodologies include the Paris equation,the Hartman-Schijve equation,the NASGRO equation,the small-crack growth model,and numerical *** of these models for AM metals are similar to those for conventionally processed materials,but are modified and pay more attention to the AM ***,an outlook for possible directions of the modeling and prediction of fatigue properties of AM metals is provided.

关键词： Additive manufacturing Fatigue properties Metals Modeling and prediction Microstructure

来源：评论

学校读者我要写书评

暂无评论

Distributed Data Recovery Against False Data Injection Attacks in DC Microgrids

Distributed Data Recovery Against False Data Injection Attac...

引用

2022 IEEE International Conference on Communications, control, and Computing Technologies for Smart Grids, SmartGridComm 2022

作者： Jin, Zexuan Liu, Mengxiang Deng, Ruilong Cheng, Peng College of Control Science and Engineering Zhejiang University State Key Lab. of Industrial Control Technology Hangzhou China

ISBN: (数字)9781665432542

ISBN: (纸本)9781665432542

With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments. © 2022 IEEE.

关键词： Recovery

来源：评论

学校读者我要写书评

暂无评论

An adaptive large neighborhood search for the multi-point dynamic aggregation problem

引用

control Theory and technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collaborate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collaboration

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：