检索结果-内蒙古大学图书馆

Influence of deformation on the corrosion behavior of LZ91 Mg-Li alloy

International Journal of Minerals,Metallurgy and Materials 2023年第1期30卷 72-81页

作者： Xueqin Liu Xuejian Wang Enyu Guo Zongning Chen Huijun Kang Tongmin Wang Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) School of Materials Science and EngineeringDalian University of TechnologyDalian 116024China Ningbo Institute of Dalian University of Technology Ningbo 315000China

The effect of rolling and forging on the microstructure and corrosion behavior of LZ91 alloy was investigated using an electron probe micro-analyzer,immersion and electrochemical *** showed that the area fraction of theβ-Li phase remained unchanged,and the grain size of theβ-Li phase decreased after *** as-rolled forged alloy(FR-LZ91)exhibited the highest area fraction of theβ-Li phase and the longest *** corrosion resistance of the forged LZ91 alloy increased due to grain refinement that prevented further corrosion during the immersion *** the experimental alloys,FR-LZ91 showed the highest resistance of corrosion film and charge transfer resistance values due to its protective film caused by the high area fraction of theβ-Li phase.

关键词： magnesium lithium alloy deformation electrochemical test corrosion behavior

来源：评论

学校读者我要写书评

暂无评论

Modulating surface cation vacancies of nickel-cobalt oxides as efficient catalysts for lithium-oxygen batteries

引用

Journal of Materials science & Technology 2023年第8期139卷 147-155页

作者： Yuan Yang Linna Dai Jianwei Qiu Zhibiao Hu Peng Wang Yongtao Zhao Huanhuan Guo Pengchao Si Rui Song Center for Robotics School of Control Science and EngineeringShandong UniversityJinan 250061China Research Center for Carbon Nanomaterials Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education)School of Materials Science and EngineeringShandong UniversityJinan 250061China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China College of Chemistry and Chemical Engineering Xingtai UniversityXingtai 054001China

Rechargeable lithium-oxygen batteries(LOBs)have received incremental attention owing to their high energy density and applicability to mobile devices and electric ***,the lack of robust,low-cost,and environmentally benign bifunctional catalysts is a major impediment to the commercial *** introduction of vacancies is one of the effective strategies to enhance the performance of cathode catalysts for lithium-oxygen batteries,but the preparation is *** this work,needle-like microsphere cathode catalysts of nickel-cobalt oxide containing cationic vacancies are constructed by controlling the annealing *** is demonstrated that the presence of cationic vacancies can modulate the electronic structure of the catalyst,reduce the energy barrier for the oxygen electrode re-action,meanwhile enhance the bifunctional catalytic ***,the nickel-cobalt oxide-based LOB with cationic vacancies exhibits large specific capacity(12,205 mAh g^(-1)at 200 mA g^(-1))and good *** work provides worthwhile insight into the formation and catalytic enhancement mech-anism of transition metal oxide catalysts with cationic vacancies,and to some extent,the creation of efficient and low-cost oxygen electrocatalysts for LOBs.

关键词： Li-O_(2)batteries Metal oxides Cation vacancies Catalytic kinetic

来源：评论

学校读者我要写书评

暂无评论

Deep Neural Networks for Gait Cycle Percentage Prediction in Frail Older Adults Using a Foot-Mounted IMU

Deep Neural Networks for Gait Cycle Percentage Prediction in...

引用

2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Wang, Jiachen Guan, Zeyang Cai, Jinghao Li, Xiang Wu, Chuanyan Ma, Xin Li, Yibin Song, Rui Zhang, Huanghe Center for Robotics School of Control Science and Engineering Shandong University Jinan Shandong250100 China School of Intelligent Engineering Shandong Management University Jinan Shandong250357 China

ISBN: (纸本)9781665481090

Accurate gait phase prediction is crucial for effective gait training interventions, which are essential for preventing falls in the elderly. This study introduces a novel gait cycle percentage prediction method using end-to-end deep learning networks (DNNs) through a foot-mounted inertial measurement unit (IMU). The model is trained and tested on the GSTRIDE database, comprising data from 158 frail older adults with a total of 176,470 recorded strides. Utilizing 10-fold cross-validation, the model demonstrates a mean absolute error (MAE) of 0.04 and a root mean square error (RMSE) of 0.11. The proposed architecture enables real-time prediction, analyzing each stride in under 0.007 seconds. This demonstrates its potential for integration into wearable devices, allowing continuous monitoring and feedback for gait training. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

A Review of Unmanned Aerial Vehicle Swarm Task Assignment

A Review of Unmanned Aerial Vehicle Swarm Task Assignment

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Li, Qingyu Xiong, Hui Ding, Yaozu Song, Jinlong Liu, Jinzhen Chen, Yunjun School of Control Science and Engineering Tiangong University Tianjin300387 China Key Laboratory of Intelligent Control of Electrical Equipment Tiangong University Tianjin300387 China

ISBN: (纸本)9789811966125

Task assignment of unmanned aerial vehicle (UAV) swarm is to coordinate the matching relationship of multiple tasks between UAVs under many constraints such as flight performance and task load capacity, and to achieve a reasonable assignment of resources to complete the set tasks, while maximizing the balance efficiency and profitability. As the core part of mission planning, task assignment is an important guarantee for UAV swarms to complete military missions and through the entire process of UAV operations. Firstly, the typical task assignment model of UAV and its improvement are described. Secondly, the centralized, distributed, and central-distributed solving methods of the model are systematically sorted out, and the applications of typical algorithms are summarized and analyzed. Finally, based on the existing research, the development directions of UAV swarm task assignment field are discussed from four aspects of the establishment of realistic models, task assignment under uncertain conditions, dynamic real-time task assignment, and task assignment based on artificial intelligence methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Honeycomb-like biochar framework coupled with Fe_(3)O_(4)/FeS nanoparticles as efficient heterogeneous Fenton catalyst for phenol degradation

引用

Journal of Environmental sciences 2024年第2期136卷 390-399页

作者： Aihua Cheng Yi He Xiaohe Liu Chi He Department of Environmental Engineering College of Geology and EnvironmentXi’an University of Science and TechnologyXi’an 710054China State Key Laboratory of Multiphase Flow in Power Engineering School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’an 710049China National Engineering Laboratory for VOCs Pollution Control Material and Technology University of Chinese Academy of SciencesBeijing 101408China

Achieving an efficient and stable heterogeneous Fenton reaction over a wide pH range is of great significance for wastewater ***,a pollen-derived biochar catalyst with a unique honeycomb-like structure,coupled with the dispersion of magnetic Fe_(3)O_(4)/FeS(Fe/S)nanoparticles,was synthesized by simple impregnation precursor,followed by *** prepared Fe/S-biochar catalyst demonstrated outstanding phenol degradation efficiency across a wide pH range,with 98%of which eliminated even under neutral conditions(pH 7.0).The high catalytic activity was due to the multilevel porous structure of pollenderived biochar provided enough active sites and allowed for better electron transfer,then increases oxidation ability to promote the ***,the acid microenvironment formed by SO_(4)^(2-)group from Fe/S composite extended the pH range for Fenton reaction,and S^(2-)facilitated the conversion of≡Fe^(3+)to≡Fe^(2+),resulting in remarkable degradation ***,biochar can effectively promote cycling stability by limiting Fe *** work may provide a general strategy for designing 3D framework biochar-based Fe/S catalysts with excellent performance for heterogeneous Fenton reactions.

关键词： Biomass Biochar Fenton reaction Fe_(3)O_(4)/FeS(Fe/S) Phenol degradation

来源：评论

学校读者我要写书评

暂无评论

Research Advancements in Artificial Intelligence for Space Situational Awareness 13

Research Advancements in Artificial Intelligence for Space S...

引用

13th International Conference on Information science and Technology, ICIST 2023

作者： Hou, Pengrong Wang, Zhelong Jiang, Yu Zhu, Jun Chu, Qinghao Li, Jiaxi School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Astronautic Dynamics Xi'an Satellite Control Center Xi'an China

ISBN: (纸本)9798350313925

The increasing of satellite launch missions, collisions and disintegration events of space objects, and the vast number of near-Earth asteroids pose significant challenges to space traffic management. Space situational awareness aims to detect, track, classify, and characterize space objects, as well as assess space events, playing a crucial role in space traffic management. The application of artificial intelligence in space situational awareness has unique advantages, especially in enhancing comprehensive abilities such as knowledge, analysis, and decision-making. Its outstanding abilities in transfer learning and lifelong learning can rapidly address complex and dynamic space detection problems. This paper reviews and analyzes the research progress of AI in space situational awareness in the past five years, focusing on data collection, situational awareness, and decision-making. While discussing the advantages and limitations of technical applications, it addresses the feasibility of applying emerging technologies such as distributed machine learning, knowledge graphs, and multi-agent game theory to future space situational awareness research, considering the characteristics of space data and new requirements. This paper points out the effectiveness and necessity of artificial intelligence in space situational awareness, which can provide reference for strengthening space environmental understanding and promoting relevant research in space traffic management. © 2023 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Effluent water quality prediction method based on no-inflected point neural network

Effluent water quality prediction method based on no-inflect...

引用

2022 International Conference on Internet of Things and Machine Learning, IoTML 2022

作者： Xue, Tonglai Gao, Tianyu Zhou, Meng Han, Fei Liu, Chun School of Electrical and Control Engineering North China University of Technology China School of Environmental Science and Engineering Hebei University of Science and Technology Shijiazhuang050018 China

ISBN: (纸本)9781510664913

In practice, the effluent quality is the most important indicator to measure the performance of wastewater treatment. However, most existing sensing technology are difficult to maintain the real-time accurate of online monitoring. In his paper, a novel no-inflection point neural network (NI-BP) with adaptive learning rate is proposed for wastewater quality indicators prediction. The proposed algorithm updates the weight parameters by an adaptive learning rate method when some inflection points are detected, it can increase the weight iteration step size and make the network converge quickly. In the simulation examples, the data from Benchmark simulation model NO.1 (BSM1) are used to demonstrate the effectiveness of the proposed method. The results show that the proposed NI-BP can significantly accelerate the model training efficiency and the prediction accuracy, simultaneously. © 2023 SPIE.

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Droop control for Microgrids with Variable Inverter Outputs: A Virtual Impedance-Based Adaptive Strategy

Droop Control for Microgrids with Variable Inverter Outputs:...

引用

2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Zhang, Hualin Wang, Shuwang Zhang, Baicheng Kong, Guanqiao School of Electrical and Control Engineering Liaoning Technical University Huludao China School of Cyber Science and Engineering Southeast University Nanjing China CSSC Systems Engineering Research Institute Beijing China

ISBN: (纸本)9798350384185

With the widespread application of renewable energy sources (RES) in islanded microgrids, the system instability caused by the intermittency of RES generation has also increased. To maintain stability during RES fluctuations, a n ovel adaptive droop control strategy utilizing adaptive virtual impedance is proposed in this study. This strategy allows the droop coefficients and virtual impedance to adaptively change based on the actual capacity of the inverters, thereby automatically adjusting the inverter output voltage and ensuring proper power sharing even as inverter capacity changes. Moreover, this strategy ensures appropriate power sharing under different load conditions and microgrid configurations. F inally, t he p roposed s trategy i s validated through MATLAB/Simulink simulations, showcasing its advantages over traditional droop control. © 2024 IEEE.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

引用

Computers, Materials & Continua 2023年第4期75卷 1157-1177页

作者： Guo-Wen Sun Gang Xiang Wei He Kai Tang Zi-Yi Wang Hai-Long Zhu School of Computer Science and Information Engineering Harbin Normal UniversitySongbei DistrictHarbin150025China Beihang University School of Automation Science and Electrical Engineering Beijing100191China Beijing Aerospace Automatic Control Institute Beijing100074China Rocket Force University of Engineering Xi’anShaanxi Province710025China

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

关键词： Self-adaptive quality factor belief rule base wireless sensor networks fault diagnosis

来源：评论

学校读者我要写书评

暂无评论

Deep learning-based end-to-end depth estimation from a single-frame fringe pattern with the FDSUNet++ network

引用

Optoelectronics Letters 2025年

作者： ZHU Xinjun ZHANG Jialei SONG Limei WANG Hongyi TIAN Ruiqin School of Artificial Intelligence， Tiangong University School of Control Science and Engineering， Tiangong University

Recently the depth estimation methods based on deep learning (DL) retains challenging to estimate high-precision in fringe projection structured light three-dimensional (3D) measurement with limited information from a single-frame fringe pattern. In this letter， we proposed a FDSUNet++ convolutional neural network， which consists of a UNet++ base model， an improved squeeze-and-excitation (ISE) block， a Fourier transform (FT) data preprocessing block， and a discrete wavelet transform (DWT) block. The proposed ISE block can improve the ability of feature extraction and the designed FT data preprocessing block preserves the key features of the fringe pattern by Fourier transform. The introduced DWT block reduces the complexity and training cost of the model. By integrating these three blocks into the UNet++ network， it can better achieve depth estimation. Experimental results from two structured light datasets demonstrate that the proposed FDSUNet++ outperforms the state-of-art networks such as UNet， SUNet， R2U-Net， PCTNet and MSUNet++， achieving the best performance in both qualitative and quantitative evaluation.

关键词：

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：