检索结果-内蒙古大学图书馆

Non-covalent interaction of atomically dispersed dual-site catalysts featuring Co and Ni nascent pair sites for efficient electrocatalytic overall water splitting

引用

Journal of Materials Science & technology 2024年第11期178卷 210-225页

作者： Imran Khan Yaogang Chen Zhiyang Li Wenjie Liu Salman Khan Sami Ullah Linlin Liu Amir Zada Sharafat Ali Shabana Shaheen Lei Yang State Key Laboratory of Urban Water Resource and Environment Shenzhen Key Laboratory of Organic Pollution Prevention and ControlSchool of Civil and Environmental EngineeringHarbin Institute of Technology ShenzhenShenzhen 518055China School of Physics and Electronics Central South UniversityChangsha 410083China CNAS Accredited Test Center Guangdong Engineering Technology Research Center of Air PurificationHealthlead Co.Ltd.Shenzhen 518055China Key laboratory of Functional Inorganic Material Chemistry Ministry of Education of the People's Republic of ChinaHeilongjiang UniversityHarbin 150080China K.A.CARE Energy Research&Innovation Center(ERIC) King Fahd University of Petroleum&Minerals(KFUPM)Dhahran 31261Saudi Arabia Department of Chemistry Abdul Wali Khan UniversityMardanKhyber Pakhtunkhwa 23200Pakistan School of Physics University of Electronic Science and Technology of ChinaChengdu 610054China

The scarcity of highly effective and economical catalysts is a major impediment to the widespread adop-tion of electrochemical water splitting for the generation of ***_(2),a low-cost candidate,suffers from inefficient catalytic ***,a captivating strategy has emerged,which involves the en-gineering of heteroatom doping to enhance electrochemical *** investigation demonstrates a successful implementation of the strategy by combining ultrathin MoS_(2) nanosheets with Co and Ni dual single multi-atoms(DSMAs)grown directly on 2D N-doped carbon nanosheets(CoNi-MoS_(2)/NCNs)for the purpose of improving hydrogen evolution reaction(HER)and oxygen evolution reaction(OER).With the aid of a dual-atom doped bifunctional electrocatalyst,effective water splitting has been achieved across a broad pH range in *** double doping of Co and Ni strengthens their interactions,thereby altering the electromagnetic composition of the host MoS_(2) and ultimately leading to improved electrocat-alytic ***,the synergistic effect between NCNs and MoS_(2) nanosheets provided efficient electron transport channels for ions and an ample surface area with open voids for ion ***-sequently,the CoNi-MoS_(2)/NCNs catalysts demonstrated exceptional stability and activity,producing low degree overpotentials of 180.5,124.9,and 196.4 mV for HER and 200,203,and 207 mV for OER in neu-tral,alkaline,and acidic mediums,respectively,while also exhibiting outstanding overall water-splitting performance,durability,and stability when used as an electrolyzer at universal pH.

关键词： Multifunctional catalyst Water splitting Functionalized carbon nanosheets Interface engineering pH-universal electrocatalysis

来源：评论

学校读者我要写书评

暂无评论

Event-Based Distributed Estimation of Stochastic Systems over Sensor Networks with Deception Attacks∗

Event-Based Distributed Estimation of Stochastic Systems ove...

引用

2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Wang, Zifan Liu, Yifan Fan, Yougao Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China Institute of Spacecraft System Engineering Beijing100094 China Beijing Institute of Spacecraft Environment Engineering Beijing100094 China

ISBN: (纸本)9781728190037

This paper addresses H∞ state estimation problem for a class of discrete-time stochastic delayed systems subject to deception attacks over sensor networks. We consider the scenario where the sensor output and estimator output are transmitted to its corresponding estimator and other estimators, respectively, over two different digital channels. To cope with the problem of constrained bandwidth, the event-triggering ideas are implemented on both sensor-to-estimator and estimator-to-estimator channels. Meanwhile, we consider there is an attacker that possibly corrupts the measurement output. Under these circumstances, we aim to design the state estimator such that the exponential mean-square stability with H∞ performance is satisfied. By virtue of Lyapunov-Krasovskii functional, we can derive the explicit estimator parameters by solving a set of linear matrix inequalities (LMIs). Finally, a numerical example is established to verify our theoretical results. © 2021 IEEE.

关键词： Sensor networks

来源：评论

学校读者我要写书评

暂无评论

Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise

arXiv

引用

arXiv 2024年

作者： Liao, Jing-Xiao He, Chao Li, Jipu Sun, Jinwei Zhang, Shiping Zhang, Xiaoge Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong School of Instrumentation Science and Engineering Harbin Institute of Technology Harbin China School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China

Blind deconvolution (BD) has been demonstrated as an efficacious approach for extracting bearing fault-specific features from vibration signals under strong background noise. Despite BD's desirable feature in adaptability and mathematical interpretability, a significant challenge persists: How to effectively integrate BD with fault-diagnosing classifiers? This issue arises because the traditional BD method is solely designed for feature extraction with its own optimizer and objective function. When BD is combined with downstream deep learning classifiers, the different learning objectives will be in conflict. To address this problem, this paper introduces classifier-guided BD (ClassBD) for joint learning of BD-based feature extraction and deep learning-based fault classification. Firstly, we present a time and frequency neural BD that employs neural networks to implement conventional BD, thereby facilitating the seamless integration of BD and the deep learning classifier for co-optimization of model parameters. Specifically, the neural BD incorporates two filters: i) a time domain quadratic filter to utilize quadratic convolutional networks for extracting periodic impulses;ii) a frequency domain linear filter composed of a fully-connected neural network to amplify discrete frequency components. Subsequently, we develop a unified framework to use a deep learning classifier to guide the learning of BD filters. In addition, we devise a physics-informed loss function composed of kurtosis, l2∕l4 norm, and a cross-entropy loss to jointly optimize the BD filters and deep learning classifier. Consequently, the fault labels provide useful information to direct BD to extract features that distinguish classes amidst strong noise. To the best of our knowledge, this is the first of its kind that BD is successfully applied to bearing fault diagnosis. Experimental results from three datasets demonstrate that ClassBD outperforms other state-of-the-art methods under noisy conditions

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Safety-critical control with control Barrier Functions: A Hierarchical Optimization Framework

arXiv

引用

arXiv 2024年

作者： Xie, Junjun Hu, Liang Qin, Jiahu Yang, Jun Gao, Huijun The Department of Automation School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China The Department of Automation University of Science and Technology of China Hefei230085 China The Department of Aeronautical and Automotive Engineering Loughborough University LeicestershireLE11 3TU United Kingdom The Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

The control barrier function (CBF) has become a fundamental tool in safety-critical systems design since its invention. Typically, the quadratic optimization framework is employed to accommodate CBFs, control Lyapunov functions (CLFs), other constraints and nominal control design. However, the constrained optimization framework involves hyper-parameters to tradeoff different objectives and constraints, which, if not well-tuned beforehand, impact system performance and even lead to infeasibility. In this paper, we propose a hierarchical optimization framework that decomposes the multi-objective optimization problem into nested optimization sub-problems in a safety-first approach. The new framework addresses potential infeasibility on the premise of ensuring safety and performance as much as possible and applies easily in multi-certificate cases. With vivid visualization aids, we systematically analyze the advantages of our proposed method over existing QP-based ones in terms of safety, feasibility and convergence rates. Moreover, two numerical examples are provided that verify our analysis and show the superiority of our proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Constrained optimization

来源：评论

学校读者我要写书评

暂无评论

General Design and Thermodynamic Analysis of a Supercritical Carbon Dioxide Cannon

引用

Journal of Thermal Science 2021年第1期30卷 123-132页

作者： ZHANG Fan LIU Hongrui WU You LI Jiaqi YU Huazhang WANG Xiaoliang GUO Baoting YUAN Yixiang Key Laboratory of Light Duty Gas Turbine Institute of Engineering ThermophysicsChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Department of Fluid Control and Automation Harbin Institute of TechnologyHarbin 150001China Force Academy of People’s Armed Police Beijing 100012China

This paper presents a new supercritical carbon dioxide(SCO_(2))cannon based on the carbon dioxide(CO_(2))’s thermodynamic cycle under constant ***,Virial equation and NIST database are applied to formulate SCO_(2)’s property and analyze the thermodynamic cycle,which is aimed to get the optimization equation using the cannon’s exit velocity as objective *** the cannon’s structural parameters,such as diaphragm thickness and barrel length,and CO_(2)’s filling mass,are ***,the flow field and velocity’s change during the launch process is performed with *** field test,the ultra-high pressure sensor and ultra-high speed camera are used to measure the pressure distribution along the barrel’s axial direction and the projectile’s exit velocity under different *** results show that all the performance indexes meet the design *** innovative SCO_(2)cannon in this paper has obvious advantages such as high safety,low cost and fast loading,which can be applied in many situations such as disaster relief,peacekeeping and ***,the unique energy storage method and thermodynamic design ensure its subsequent development.

关键词： supercritical carbon dioxide(SCO_(2))cannon state equation thermodynamic analysis field test

来源：评论

学校读者我要写书评

暂无评论

An adaptive observer-based SOC estimation method for lithium-ion batteries against sensor measurement uncertainties

An adaptive observer-based SOC estimation method for lithium...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Xiaoyi Xu Hao Luo Mo-Yuen Chow Cong-Sheng Huang Yuchen Jiang Department of Control Science and Engineering Harbin Institute of Technology Harbin P. R. China Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

Accurate estimation of battery state of charge (SOC) is critical for efficient and safe battery applications. The measurement uncertainties of sensors, including measurement noises and sensor bias will affect the estimation accuracy inevitably. Therefore, quantifying the relationship between the sensor measurement uncertainties and the SOC estimation errors and seeking better SOC estimation methods has been a hot topic of research. In this paper, model errors and SOC estimation errors under measurement noise and sensor bias are derived. The resulting analyses can be used to assess the robustness of the SOC estimates. In addition, an adaptive observer-based SOC estimation method for lithium-ion batteries is proposed to cope with the measurement uncertainty. Simulation experiments demonstrate the effectiveness of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

JOINT TRAJECTORY REPLANNING FOR MARS ASCENT VEHICLE UNDER PROPULSION SYSTEM FAULTS: A SUBOPTIMAL LEARNING-BASED WARM-START APPROACH

arXiv

引用

arXiv 2024年

作者： Li, Kun Ran, Guangtao Guo, Yanning Park, Ju H. Zhang, Yao Department of Control Science and Engineering Harbin Institute of Technology Harbin150001 China Department of Electrical Engineering Yeungnam University Gyeongsan38541 Korea Republic of School of Engineering University of Southampton SouthamptonSO16 7QF United Kingdom

During the Mars ascent vehicle (MAV) launch missions, when encountering a thrust drop type of propulsion system fault problem, the general trajectory replanning methods relying on step-by-step judgments may fail to make timely decisions, potentially leading to mission failure. This paper proposes a suboptimal joint trajectory replanning (SJTR) method, which formulates the joint optimization problem of target orbit and flight trajectory after a fault within a convex optimization framework. By incorporating penalty coefficients for terminal constraints, the optimization solution adheres to the orbit redecision principle, thereby avoiding complex decision-making processes and resulting in a concise and rapid solution to the replanning problem. A learning-based warm-start scheme is proposed in conjunction with the designed SJTR method. Offline, a deep neural network (DNN) is trained using a dataset generated by the SJTR method. Online, the DNN provides initial guesses for the time optimization variables based on the current fault situation, enhancing the solving efficiency and reliability of the algorithm. Numerical simulations of the MAV flight scenario under the thrust drop faults are performed, and Monte Carlo experiments and case studies across all orbit types demonstrate the effectiveness of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images

引用

Journal of Advanced Research 2024年

作者： Sun, Weiling Yan, Pengfei Li, Minglei Li, Xiang Jiang, Yuchen Luo, Hao Zhao, Yanbin Department of Medical Oncology Harbin Medical University Cancer Hospital Harbin 150040 China Department of Endoscope Harbin Medical University Cancer Hospital Harbin 150040 China Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China

Introduction: Bronchoscopy is of great significance in diagnosing and treating respiratory illness. Using deep learning, a diagnostic system for bronchoscopy images can improve the accuracy of tracheal, bronchial, and pulmonary disease diagnoses for physicians and ensure timely pathological or etiological examinations for patients. Improving the diagnostic accuracy of the algorithms remains the key to this technology. Objectives: To deal with the problem, we proposed a multiscale attention residual network (MARN) for diagnosing lung conditions through bronchoscopic images. The multiscale convolutional block attention module (MCBAM) was designed to enable accurate focus on lesion regions by enhancing spatial and channel features. Gradient-weighted Class Activation Map (Grad-CAM) was provided to increase the interpretability of diagnostic results. Methods: We collected 615 cases from harbin Medical University Cancer Hospital, including 2900 images. The dataset was partitioned randomly into training sets, validation sets and test sets to update model parameters, evaluate the model's training performance, select network architecture and parameters, and estimate the final model. In addition, we compared MARN with other algorithms. Furthermore, three physicians with different qualifications were invited to diagnose the same test images, and the results were compared to those of the model. Results: In the dataset of normal and lesion images, our model displayed an accuracy of 97.76% and an AUC of 99.79%. The model recorded 92.26% accuracy and 96.82% AUC for datasets of benign and malignant lesion images, while it achieved 93.10% accuracy and 99.02% AUC for normal, benign, and malignant lesion images. Conclusion: These results demonstrated that our network outperforms other methods in diagnostic performance. The accuracy of our model is roughly the same as that of experienced physicians and the efficiency is much higher than doctors. MARN has great potential for assisting p

关键词： Attention mechanism Bronchoscopy Computer aided diagnosis Convolutional neural network Deep learning

来源：评论

学校读者我要写书评

暂无评论

A quantitative and constructive proof of Willems’ Fundamental Lemma and its implications

A quantitative and constructive proof of Willems’ Fundament...

引用

American control Conference (ACC)

作者： Julian Berberich Andrea Iannelli Alberto Padoan Jeremy Coulson Florian Dörfler Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Department of Information Technology and Electrical Engineering ETH Zurich Zurich Switzerland

Willems’ Fundamental Lemma provides a powerful data-driven parametrization of all trajectories of a controllable linear time-invariant system based on one trajectory with persistently exciting (PE) input. In this paper, we present a novel proof of this result which is inspired by the classical adaptive control literature and differs from existing proofs in multiple aspects. The proof involves a quantitative and directional PE notion, allowing to characterize robust PE properties via singular value bounds, as opposed to binary rank- based PE conditions. Further, the proof is constructive, i.e., we derive an explicit PE lower bound for the generated data. As a contribution of independent interest, we generalize existing PE results from the adaptive control literature and reveal a crucial role of the system’s zeros.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Microstructure and properties evolution of plasma sprayed Al_(2)O_(3)-Y_(2)O_(3) composite coatings during high temperature and thermal shock treatment

引用

Journal of Rare Earths 2021年第6期39卷 718-727,I0004页

作者： Xingyu Wang Xiaolong Wang Xiaowen Sun Yong Yang Chen Zhang Yuduo Ma Yuhang Cui Yanchun Dong Dianran Yan You Wang Key Lab.for New Type of Functional Materials in Hebei Province State Key Laboratory of Reliability and Intelligence of Electrical EquipmentTianjin Key Laboratory of Materials Laminating Fabrication and Interface Control TechnologySchool of Materials Science and EngineeringHebei University of TechnologyTianjin 300132China Department of Materials Science Harbin Institute of TechnologyHarbin 150001China

Al_(2)O_(3)-Y_(2)O_(3) composite powder with TiO_(2) additive was plasma sprayed to prepare Al_(2)O_(3)-Y_(2)O_(3) composite *** micro structure and properties evolution of the Al_(2)O_(3)-Y_(2)O_(3) coatings during high temperature and thermal shock resistance were *** results show that the micro structure of the Al_(2)O_(3)-Y_(2)O_(3)-TiO_(2) coating is more uniform than that of the Al_(2)O_(3)-Y_(2)O_(3) ***,amorphous phase is formed in the two *** Al_(2)O_(3)-Y_(2)O_(3)(-TiO_(2)) coatings were heat treated for 2 h at temperatures of 800,1000 and 1200℃,*** is found that the microstructure and properties of the two coatings have no obvious change at 800℃.Some of the amorphous phase is crystallized at1000℃,and meanwhile Y_(2)O_(3) and Al_(2)O_(3) react to form YAG phase and YAM *** 1200℃,all of the amorphous phases are *** heat treatment,the micro hardness of the two coatings is *** thermal shock resistance of the Al_(2)O_(3)-Y_(2)O_(3) system coatings can be improved by using TC4 titanium alloy as substrate and with NiCrAlY bonding ***,the Al_(2)O_(3)-Y_(2)O_(3)-TiO_(2) coating exhibits better thermal shock resistance due to the addition of TiO_(2).

关键词： Al_(2)O_(3)-Y_(2)O_(3)coating TiO_(2) Plasma spraying Thermal shock resistance Microstructure evolution

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：