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Chemically bonded multi-nanolayer inorganic aerogel with a record-low thermal conductivity in a vacuum

National Science Review 2023年第10期10卷 96-105页

作者： Hongxuan Yu Menglin Li Yuanpeng Deng Shubin Fu Jingran Guo Han Zhao Jianing Zhang Shixuan Dang Pengyu Zhang Jian Zhou Dizhou Liu Duola Wang Chuanwei Zhang Menglong Hao Xiang Xu Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology and Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast University Key Lab of Aerospace Bearing Technology and Equipment of the Ministry of Industry and Information Technology Harbin Institute of Technology

Inorganic aerogels have exhibited many superior characteristics with extensive applications,but are still plagued by a nearly century-old tradeoff between their mechanical and thermal *** reducing thermal conductivity by ultralow density,inorganic aerogels generally suffer from large fragility due to their brittle nature or weak joint crosslinking,while enhancing the mechanical robustness by material design and structural engineering,they easily sacrifice thermal insulation and ***,we report a chemically bonded multi-nanolayer design and synthesis of a graphene/amorphous boron nitride aerogel to address this typical tradeoff to further enhance mechanical and thermal *** to the chemically bonded interface and coupled toughening effect,our aerogels display a low density of 0.8 mg cm-3with ultrahigh flexibility（elastic compressive strain up to 99% and bending strain up to 90%）,and exceptional thermostability（strength degradation <3% after sharp thermal shocks）,as well as the lowest thermal conductivities in a vacuum(only 1.57 mW m-1K-1at room temperature and 10.39 mW m-1K-1at500℃) among solid materials to *** unique combination of mechanical and thermal properties offers an attractive material system for thermal superinsulation at extreme conditions.

关键词： inorganic aerogels multi-nanolayer mechanical-thermal tradeoff flexibility thermal superinsulation

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Improving Accuracy of the IμUWB Fusion Positioning Approach Utilizing ESEKF and VBUKF for Underground Coal Mining Working Face

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IEEE Internet of Things Journal 2025年第13期12卷 24672-24685页

作者： Cao, Bo Jiang, Mingrui Li, Menglan Ke, Xuran Zhang, Chao Zhang, Hua Zeng, Qiliang Xu, Biyong Anhui Science and Technology University School of Mechanical Engineering Chuzhou233100 China Hefei University of Technology School of Mechanical Engineering Hefei230041 China Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot Anhui Wuhu241002 China

The high-precision positioning of the shearer in underground coal mines remains a significant challenge task for realizing automation and intelligent coal mining. Most of the presently conventional positioning approaches, nonetheless, tend to deliver low accuracy and unreliable estimations in the GPSdenied underground coal mine environment. Additionally, the current experiments remain in the simulation verification stage while lacking of the real field experiments. In order to improve reliability and positioning accuracy of target node (TN) in coal mines, this paper proposes a fusion positioning scheme with the combination of the inertial measurement unit (IMU) and Ultrawideband (UWB) based on error state extended Kalman filter (ESEKF) approach with the utilization of the available measurements obtained from IMU system and the established UWB localization system. Subsequently, the VBUKF method that incorporates the variational Bayesian (VB) and unscented Kalman filter (UKF) is implemented to the result of fusion localization with consideration of the changeable measurement noise to further eliminate the trajectory error and refine the final estimation accuracy. Furthermore, to bridge the research gap of the real field experiments using the IμUWB fusion system, the experimental investigation is performed to evaluate the effectiveness of the proposed method in the underground coal mine environment. The experimental results demonstrate that the presented ESEKF method, after applying the VBUKF smoothing, is capable to achieve better performances than the contrasted methods in terms of localization, and also can significantly improve the positioning accuracy of the shearer in the coal mining working face. © 2025 IEEE.

关键词： Coal mines

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controllability of heterogeneous networked sampled-data systems

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Science China(information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Adjustable patch and feature prior token-based transformer for weakly supervised semantic segmentation

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International Journal of Computers and Applications 2024年第7期46卷 445-454页

作者： Li, Linjuan Zhang, Haoxue Xie, Gang Bai, Yanhong School of Electronic and Information Engineering Taiyuan University of Science and Technology Taiyuan China Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China

Weakly supervised semantic segmentation is a challenging task, utilizing only low-cost weak supervision to produce pixel-level predictions. Existing transformer-based methods for weakly supervised semantic segmentation have some limitations: (1) Fixing patch size might destroy the structured semantics, which is unfriendly to objects of different scales, and (2) Ignoring the prior features when using multi-head attention mechanisms might lead to inaccurate segmentation localization. To tackle these issues, we proposed an effective transformer framework coupled with the adjustable patch and prior feature tokens, termed as APFPformer, in which an adjustable patch module is developed to split the image according to the area of the salient object for preserving the structured semantics in patches. A prior feature token module is devised to exploit the edge and texture information as prior tokens, ensuring the gain of discriminative representation. Additionally, a single-stage scheme is applied to reduce the computation and rapid segmentation process. Our experiments demonstrate the superiority of our approach over early methods, gaining competitive mean Intersection-over-Union scores of 67.9% on the PASCAL VOC2012 dataset and 40.2% on the MS COCO dataset. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Semantic Segmentation

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Detection of Oscillations in Process control Loops From Visual Image Space Using Deep Convolutional Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 982-995页

作者： Tao Wang Qiming Chen Xun Lang Lei Xie Peng Li Hongye Su the Department of Electronic Engineering the School of InformationYunnan UniversityKunming 650091China DAMO Academy Alibaba GroupHangzhou 311100China the State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Oscillation detection has been a hot research topic in industries due to the high incidence of oscillation loops and their negative impact on plant *** numerous automatic detection techniques have been proposed,most of them can only address part of the practical *** oscillation is heuristically defined as a visually apparent periodic ***,manual visual inspection is labor-intensive and prone to missed *** neural networks(CNNs),inspired by animal visual systems,have been raised with powerful feature extraction *** this work,an exploration of the typical CNN models for visual oscillation detection is ***,we tested MobileNet-V1,ShuffleNet-V2,Efficient Net-B0,and GhostNet models,and found that such a visual framework is well-suited for oscillation *** feasibility and validity of this framework are verified utilizing extensive numerical and industrial *** with state-of-theart oscillation detectors,the suggested framework is more straightforward and more robust to noise and *** addition,this framework generalizes well and is capable of handling features that are not present in the training data,such as multiple oscillations and outliers.

关键词： Convolutional neural networks(CNNs) deep learning image processing oscillation detection process industries

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Research on Fault Diagnosis Algorithm of Air Compressor Based on Low-Rank Matrix Recovery

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2024年第12期51卷 2010-2016页

作者： Yu, Tianming Long, Cheng Feng, Guoliang School of Automation Engineering Northeast Electric Power University Jilin Jilin 132012 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin Jilin 100190 China

Air compressors are crucial in industrial production, but issues such as equipment aging and improper operation can lead to faults, severely impacting efficiency and safety. Traditional MFCC spectrogram-based diagnostic methods are challenged by background noise interference, making accurate fault feature extraction difficult. To address this, this study proposes an air compressor fault identification algorithm based on low-rank matrix recovery. By applying low-rank background modeling to the MFCC spectrogram to eliminate background noise, the algorithm effectively extracts primary features. The MobileNetV2 model is then used to extract features from the MFCC foreground images, followed by dimensionality reduction using Principal Component Analysis (PCA). The reduced-dimensional fault features are analyzed using k-means clustering. Experimental results show that for Data 2, the VGG19 model achieved an accuracy of 95.90%, an F1-score of 0.91, and a recall of 0.93, with a processing time of 1916 seconds. In comparison, the ResNet50 model attained an accuracy of 94.88%, an F1-score of 0.91, and a recall of 0.93, with a processing time of 826 seconds. These results demonstrate that the foreground features obtained through low-rank background modeling exhibit superior performance in fault identification and clustering, enhancing the accuracy and stability of fault diagnosis. Thus, the proposed algorithm shows promising potential for diagnosing and repairing air compressor faults. © (2024), (International Association of Engineers). All rights reserved.

关键词： K-means clustering

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Anti-Windup Active Power control for Wind Turbines Considering Loads Reduction 13

Anti-Windup Active Power Control for Wind Turbines Consideri...

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

作者： Wang, Guozhong Luo, Hao Jiao, Xuguo Yang, Zhibo Zhao, Xinxin School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China

ISBN: (纸本)9798350361674

In recent years, the proportion of wind power in electricity contribution is increasing, and wind power generation technology has developed rapidly. How to enhance the stability of wind turbine systems and extend their service life are still challenging problems due to uncertain and intermittent characteristics of natural wind. In order to ensure that variable speed wind turbines track the active power instructions released by the power system, an improved anti-windup rotor speed control strategy is designed to switch different control strategies according to the wind turbine rotor speed value, with the aim of optimizing the mechanical loads of pitch systems. Firstly, in the low wind speed region, the maximum wind energy capture is achieved by optimal torque control. When the rotor speed increases to a critic value, torque control determined by the turbine's rated output power and rotor speed is adopted. In the high wind speed region, the pitch controller is used to adjust the wind energy capture coefficient to maintain the rotor speed at its rated value. Moreover, in order to solve the problem of integral saturation in traditional rotor speed control methods, this paper proposes a bounded constraints assisted Proportional-Integral (PI) pitch angle control scheme to optimize the operation of pitch system. This control method can effectively eliminates integral saturation, mitigate fatigue loads of wind turbines, reduces overshoot of rotor speed and ensures safe and stable operation of wind turbines. Finally, the proposed method is simulated on OpenFAST platform to verify its advancement. © 2024 IEEE.

关键词： Wind turbines

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An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

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Frontiers of Computer Science 2024年第3期18卷 183-197页

作者： Xingxing CHEN Qingfeng CHENG Weidong YANG Xiangyang LUO State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of TechnologyZhengzhou 450001China Henan Province Key Laboratory of Cyberspace Situation Awareness Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China

With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of ***,it is a great challenge to achieve anonymous authentication of IoT nodes and secure data *** present,blockchain technology is widely used in authentication and s data storage due to its decentralization and ***,Fan et *** a secure and efficient blockchain-based IoT authentication and data sharing *** studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT *** overcome these security flaws,this paper proposes an enhanced authentication and data transmission scheme,which is verified by formal security proofs and informal security ***,Scyther is applied to prove the security of the proposed ***,it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.

关键词： Internet of Things blockchain authentication data transmission

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Question Answering System of Traditional Chinese Medicine based on BERT and Knowledge Graph

Question Answering System of Traditional Chinese Medicine ba...

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2024 International Conference on Distributed Systems, Computer Networks and Cybersecurity, ICDSCNC 2024

作者： Wang, Renyuan Wang, Zhongce Li, Qi Jilin Institute of Chemical Technology College of Information and Control Engineering Jilin China Jilin Agricultural Science and Technology University Electrical and Information Engineering College Jilin China

ISBN: (纸本)9798350375442

With the continuous growth in demand for health information and medical services, there is a large number of medical question-answering systems available in the market. The system has made progress in the realm of general medicine, but still faces challenges in the field TCM (Traditional Chinese Medicine). For example, problems such as inaccurate information and lack of personalization of answers may arise. There is a vast amount of TCM knowledge available online for medical diagnosis, but traditional search engines are unable to make judgments based on the actual condition of patients, failing to meet user needs. Therefore, this paper proposes a TCM question and answer system based on BERT and knowledge graph. The experimental results show that both the BERT+BiLSTM+ CRF model and the BiLSTM+Attention model have achieved improvements, enhancing the precision, recall, and F1-score of TCM information recognition. This ensures the question-answering system's responses are more closely aligned with user needs. © 2024 IEEE.

关键词： Question answering

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Explainable Neural Network for Sensitivity Analysis of Lithium-ion Battery Smart Production

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1944-1953页

作者： Kailong Liu Qiao Peng Yuhang Liu Naxin Cui Chenghui Zhang School of Control Science and Engineering Shandong UniversityJinan 250061China Information Technology Analytics&Operations groupQueen’s University BelfastBelfast BT71NNUK

Battery production is crucial for determining the quality of electrode,which in turn affects the manufactured battery *** battery production is complicated with strongly coupled intermediate and control parameters,an efficient solution that can perform a reliable sensitivity analysis of the production terms of interest and forecast key battery properties in the early production phase is urgently *** paper performs detailed sensitivity analysis of key production terms on determining the properties of manufactured battery electrode via advanced data-driven *** be specific,an explainable neural network named generalized additive model with structured interaction(GAM-SI)is designed to predict two key battery properties,including electrode mass loading and porosity,while the effects of four early production terms on manufactured batteries are explained and *** experimental results reveal that the proposed method is able to accurately predict battery electrode properties in the mixing and coating *** addition,the importance ratio ranking,global interpretation and local interpretation of both the main effects and pairwise interactions can be effectively visualized by the designed neural *** to the merits of interpretability,the proposed GAM-SI can help engineers gain important insights for understanding complicated production behavior,further benefitting smart battery production.

关键词： Battery management battery manufacturing data science explainable artificial intelligence sensitivity analysis

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