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16th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2023

作者： Tang, Hao Zhou, Yi Zhou, Tong School of Mechanical Engineering Nanjing University of Science and Technology Nanjing China Jiangsu Research Center for Intelligent Navigation and Control of Complex Motion Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350327144

MEMS disk resonator gyroscope has become a hot research topic nowadays because of its excellent performance and processing advantages. This paper takes the large stiffness MEMS disk resonator gyroscope as the research object, and firstly establishes the dynamic equations in ideal and non-ideal states, studies the quadrature error mechanism of MEMS disk gyroscope, and analyzes the causes of serious quadrature coupling of large stiffness MEMS disk resonator gyroscope based on it;then a large stiffness MEMS disk resonator gyroscope quadrature suppression method based on axial reconfiguration is proposed for this problem. The method is based on the experimental calculation of the deflection angle of each stiffness axis of the gyroscope, pre-selection of the drive and sense axis with small quadrature coupling error, and the quadrature suppression of the large stiffness disk resonator gyroscope by means of electrostatic coupling stiffness correction;finally, the closed-loop control scheme of the large stiffness disk resonator gyroscope is proposed based on the method, including the closed-loop control of drive mode, quadrature error closed-loop suppression, and force rebalance detection control. Experiments show that the closed-loop control method based on axial reconstruction can effectively reduce the output bias of the gyroscope and improve the bias instability performance of the gyroscope, and its bias instability improves from 104.3°/h to 3.2°/h compared with the gyroscope under open-loop quadrature, open-loop detection, which verifies the effectiveness of the method on the performance improvement of large-stiffness MEMS disk resonator gyroscope. © 2023 IEEE.

关键词： Gyroscopes

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Self-Contrastive Learning Fault Diagnosis Network for Signal Imaging: A Case Study

Self-Contrastive Learning Fault Diagnosis Network for Signal...

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2024 China Automation Congress, CAC 2024

作者： He, Wenbin Mao, Jianxu Wang, Yaonan Li, Zhe Yan, Feng Liu, Kexin College of Electrical & Information Engineering National Engineering Research Center of Robot Visual Perception & Control Technology Hunan University Hunan China College of Control Science & Engineering State Key Laboratory of Industrial Control Technology Zhejiang University Zhejiang China

ISBN: (纸本)9798350368604

The deep convolution method based on MSDP signal imaging has been proven to be an effective means of monitoring the robot grinding process. This method has very high requirements on the quality of imaging and requires a lot of computing resources. This paper proposes an image self-contrastive learning network that can effectively extract fault information from low-pixel fuzzy images and achieve efficient and accurate condition monitoring. The network first calculates the correlation distance matrix between two identical modified symmetrized dot pattern (MSDP) images and uses the generated similarity labels to calculate the contrast loss to extract the embedded features of the image. Finally, the classification network is trained using the cross entropy loss to achieve the classification of fault images. The method was verified on a robotic grinding platform to significantly reduce the calculation time while maintaining the recognition accuracy, which provides reliable technical support for the real-time monitoring of the robotic grinding process. © 2024 IEEE.

关键词： Contrastive Learning fault diagnosis robotic grinding signal imaging

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Dynamic Modeling Method for Turbofan Engines Based on Improved NARX Networks 50

Dynamic Modeling Method for Turbofan Engines Based on Improv...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Gu, Nannan Zhao, Zhihong He, Jinbao Huang, Jing Bao, Jianyu Wang, Yunlai School of Electronic and Information Engineering Ningbo University of Technology Ningbo China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China School of Mechatronics Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781665464543

This paper proposes a NARX network-based modeling method to improve the real-time performance of dynamic component-level engine models. This method combines the component-level model with the NARX network black-box modeling technique. It collects training data by solving the common working equation of the component-level model (N-R model) using the Newton-Raphson method and uses a multilayer feedforward neural network to approximate the nonlinear mapping from the input state space to the solution of the common working equation. This approach eliminates the need for iterative computations in solving the common working equation, thus enhancing the real-time performance of the component-level model. Using the N-R model as the benchmark, simulation results show that the NARX network model with embedded component-level modeling has a maximum dynamic error of 0.061% during ground state modeling and 0.36% across the full envelope;the average runtime for full envelope modeling is 0.046 seconds, which is only 4.3% of that of the benchmark model;for step inputs, the component residual during the dynamic process is only 0.02% of that of the benchmark model. These findings demonstrate that the engine model established by this method has high accuracy, good real-time performance, and robustness. © 2024 IEEE.

关键词： Newton-Raphson method

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Towards understanding and prediction of corrosion degradation of organic coatings under tropical marine atmospheric environment via a data-driven approach

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1151-1161页

作者： Shaopeng Liu Lingwei Ma Jinke Wang Yiran Li Haiyan Gong Haitao Ren Xiaogang Li Dawei Zhang Beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Materials Corrosion and Protection Data Center University of Science and Technology BeijingBeijing 100083China Institute of Materials Intelligent Technology Liaoning Academy of MaterialsShenyang 110004China Luoyang Ship Material Research Institute Sanya 572032China

The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various *** complexity of a dynamic environment,combined with high costs,extended experimental periods,and limited data,places a limit on the comprehension of this *** study addresses this challenge by investigating the corrosion de-gradation of damaged organic coatings in a tropical marine environment using an atmospheric corrosion monitoring sensor and a random forest(RF)*** damage simulation,a polyurethane coating applied to a Fe/graphite corrosion sensor was intentionally scratched and exposed to the marine atmosphere for over one *** correlation analysis was performed for the collection and filtering of en-vironmental and corrosion current *** to the RF model,the following specific conditions contributed to accelerated degrada-tion:relative humidity(RH)above 80%and temperatures below 22.5℃,with the risk increasing significantly when RH exceeded 90%.High RH and temperature exhibited a cumulative effect on coating degradation.A high risk of corrosion occurred in the *** RF model was also used to predict the coating degradation process using environmental data as input parameters,with the accuracy show-ing improvement when the duration of influential environmental ranges was considered.

关键词： organic coating degradation atmospheric corrosion machine learning exposure test random forest coating sensor

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Chaotic Map-Based Authentication and Key Agreement Protocol with Low-Latency for Metasystem

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Computers, Materials & Continua 2024年第3期78卷 4471-4488页

作者： Guojun Wang Qi Liu School of Electronics&Information Engineering Nanjing University of Information Science&TechnologyNanjing210044China Yancheng Polytechnic College Yancheng224000China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of SoftwareNanjing University of Information Science and TechnologyNanjingChina

With the rapid advancement in exploring perceptual interactions and digital twins,metaverse technology has emerged to transcend the constraints of space-time and reality,facilitating remote AI-based *** this dynamic metasystem environment,frequent information exchanges necessitate robust security measures,with Authentication and Key Agreement(AKA)serving as the primary line of defense to ensure communication ***,traditional AKA protocols fall short in meeting the low-latency requirements essential for synchronous interactions within the *** address this challenge and enable nearly latency-free interactions,a novel low-latency AKA protocol based on chaotic maps is *** protocol not only ensures mutual authentication of entities within the metasystem but also generates secure session *** security of these session keys is rigorously validated through formal proofs,formal verification,and informal *** confronted with the Dolev-Yao(DY)threat model,the session keys are formally demonstrated to be secure under the Real-or-Random(ROR)*** proposed protocol is further validated through simulations conducted using VMware workstation compiled in HLPSL language and C *** simulation results affirm the protocol’s effectiveness in resisting well-known attacks while achieving the desired low latency for optimal metaverse interactions.

关键词： Metasystem authentication and key agreement chaotic map secure communication

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Exploration of Early Marriage Among College Students: Health Consequences and Strategic Implications for Biotechnology Firms

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Journal of Commercial Biotechnology 2023年第5期28卷 364-378页

作者： Zhang, Cunquan Tang, Li School of Naval Architecture Ocean and Energy Power Engineering Wuhan University of Technology Wuhan430063 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430063 China

This study investigates the experiences of married undergraduate students at a Midwestern religious liberal arts institution, with a focus on health consequences of early marriage and strategic implications for biotechnology firms. The study aims to understand the impact of marriage on student engagement and health, examining how married life, interactions with peers, family, and faculty, and involvement in academic and social activities affect students' well-being. Employing a grounded theory approach, the research analyzes the adjustment to married life among college students and its effects on their academic commitment. The findings reveal that marriage introduces complexities such as increased responsibilities and altered social interactions, which could potentially influence students' mental health and academic performance. These factors are critical for biotechnology firms that are developing health and wellness solutions targeted at the college demographic. The study shows that only a small percentage of undergraduate students are married, indicating unique challenges they face, including balancing academic responsibilities with marital life. The relationship quality among these students emerged as a potential factor influencing their academic success and well-being, an aspect crucial for biotechnology companies focusing on mental health interventions. Data from an online survey at a Midwestern college highlights the correlation between marital status and academic performance, with relationship satisfaction and communication playing a negligible role. These insights are vital for biotechnology firms seeking to develop or tailor mental health and wellness programs for this specific group. Furthermore, the adaptation of married students to college life, their social support systems, and levels of marital satisfaction provide a comprehensive understanding of their unique needs and challenges. This knowledge is instrumental for biotechnology firms in creating tar

关键词： Students

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Deep Learning-Based Image Retrieval With Unsupervised Double Bit Hashing

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IEEE Transactions on Circuits and Systems for Video technology 2023年第11期33卷 7050-7065页

作者： Guo, Jing-Ming Prayuda, Alim Wicaksono Hari Prasetyo, Heri Seshathiri, Sankarasrinivasan National Taiwan University of Science and Technology Department of Electrical Engineering Advanced Intelligent Image and Vision Technology Research Center Taipei City10607 Taiwan Department of Informatics Surakarta57126 Indonesia

Unsupervised image hashing is a widely used technique for large-scale image retrieval. This technique maps an image to a finite length of binary codes without extensive human-annotated data for compact storage and effective semantic retrieval. This study proposes a novel deep unsupervised double-bit hashing method for image retrieval. This approach is based on the double-bit hashing method, which has been shown to better preserve the neighboring structure of binary codes than single-bit hashing. Traditional double-bit hashing methods require the entire dataset to be processed simultaneously to determine optimal thresholding values of binary feature encoding. In contrast, the proposed method trains the hashing layer in a minibatch manner, allowing for adaptive threshold learning through a gradient-based optimization strategy. Additionally, unlike most former methods, which only train the hashing networks on top of fixed pre-trained neural networks backbone. The proposed learning framework trains both hashing and backbone networks alternately asynchronously. This strategy enables the model to maximize the learning capability of the hashing and backbone networks. Furthermore, adopting the lightweight Vision Transformer (ViT) in the proposed method allows the model to capture both local and global relationships between multiple image views exemplar, which lead to better generalization, thus maximizing the retrieval performance of the model. Extensive experiments on CIFAR10, NUS-WIDE, and FLICKR25K datasets validate that the proposed method has superior retrieval quality and computational efficiency than state-of-the-art methods. © 2023 IEEE.

关键词： Neural networks

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Magnetorheological damper parameter identification and its application in semi-active control of power equipment

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Noise and Vibration Worldwide 2024年第11期55卷 632-650页

作者： Wei, Huang Jian, Xu Yi, Yao Yongliang, Zhang Xin, Wang SINOMACH Technology Research Center of Engineering Vibration Control Beijing China Beijing China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei China

In recent years, magnetorheological dampers (MRD) have played a significant role in vibration control in various fields such as vehicles, military, building structures, etc. However, the mechanical model of MRD is very complex due to its hysteresis, which makes it difficult to identify the model’s parameters. In addition to experimental data, under the condition of no other prior knowledge, eight unknown parameters of the Bouc-Wen model are identified in this study based on the particle swarm optimization (PSO) algorithm. According to the trend of parameter variation with current, fitting research is conducted, and the variation law of parameters with current is summarized. Based on the identified parameters, the MRD’s output force is predicted under any current other than the experimental current. Subsequently, the application of MRD in semi-active control of power equipment is performed out, and proposed Simulink calculation programs for single-stage and two-stage vibration control systems are built. Then, a comparative study with passive and active control is conducted. In this paper, linear quadratic regulator (LQR) control is adopted for the active control, and the controller’s parameters are optimized based on the PSO algorithm. The results show that the adopted semi-active control can significantly reduce the transmitted force from power equipment to the foundation and can effectively mitigate the disturbance of power equipment to the environment. This study offers important guidance for the vibration control of MRD in industrial engineering. © The Author(s) 2024.

关键词： Vibration control

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Comparative Study of Linear Variable Flux Reluctance Machine with Linear Wound Field Flux Reversal Machine

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CES Transactions on Electrical Machines and Systems 2023年第1期7卷 73-80页

作者： Tingting Jiang Liang Xu Jinghua Ji Wenxiang Zhao the School of Electrical and Information Engineering the Jiangsu Key Laboratory of Drive and Intelligent Control for Electric Vehicleand the National Center for International Research on StructuralHealth Management of Critical ComponentsJiangsu UniversityZhenjiang 212013China IEEE

As members of doubly salient magnetless linear machines,linear variable flux reluctance(LVFR)and wound field flux reversal(LWFFR)machines inherit the merits of conventional magnetless linear machines such as low cost,high flux adjustment capability and high ***,like linear switched reluctance machine,they have a very simple and compact long secondary,which are very attractive for long stroke ***,low force capability is their major *** solve this issue,new LVFR and LWFFR machine topologies were proposed in recent work,while lacking studies on their force improvement mechanism and further force *** this paper,LVFR and LWFFR machines with improved force performance are comparatively studied with the emphasis on their force *** operation principle of the two machines is analyzed based on magnetic field harmonics produced by flux *** of air-gap flux density harmonic components to no-load back electromagnetic forces of the two machines are analyzed and the average force equation is ***,force capabilities of the both machines are investigated by means of the time-stepping finite-element analysis to verify the theoretical analysis.

关键词： Wound field Variable flux reluctance Flux reversal Linear machine Finite-element analysis

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