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SSRN 2023年

作者： Qiang, Wang Chen, Zhihui Gu, Zhiyuan Li, Lingqiao Guo, Deyi Shi, Baopeng Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics Taiyuan University of Technology Taiyuan030024 China

The metal-dielectric dimer is a kind of ideal structure for significantly enhancing single-molecule fluorescence. This enhancement arises from the interaction of single molecules with the metal-dielectric dimer, leading to localized surface plasmon resonance (LSPR), which amplifies the light field by several orders of magnitude. One-dimensional photonic crystals (1D PCs) possess a distinctive photonic bandgap property and can provide nearly perfect reflection for specific wavelengths. These attributes contribute significantly to the enhancement of fluorescence. In light of these considerations, we propose the utilization of 1D PCs as the substrate and a silicon-silver dimer as the quantum dots emitter to achieve remarkable emission enhancement. Our design involves a 20 nm gapped silicon-silver dimer with a 50 nm nanochannel positioned above it. Through the optimization of structural parameters, our results demonstrate that this configuration can achieve approximately five orders of magnitude higher fluorescence enhancement than the bare structure, with a total fluorescence average enhancement of up to 3965 times. These findings stand for the unique sensitivity of the device, making it a promising choice for applications in biological nanoparticle detection, environmental monitoring, and other fields in the future. © 2023, The Authors. All rights reserved.

关键词： Silicon

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Compound Fault Diagnosis of Planetary Gearbox Using Capsule Network with Multi-Scale Convolutional Neural Network

Compound Fault Diagnosis of Planetary Gearbox Using Capsule ...

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2024 Prognostics and system Health Management Conference, PHM 2024

作者： Li, Guoyan Zhang, Jingbin Lu, Guoliang School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu61173 China Taiyuan University of Technology Key Laboratory of Advance Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China School of Mechanical Engineering Key Laboratory of High-efficiency and Clean Mechanical Manufacture of MOE Shandong University National Demonstration Center for Experimental Mechanical Engineering Education Jinan250061 China

ISBN: (纸本)9798350360585

Capsule network is an innovative deep learning-based model that uses neuron vectors as inputs and outputs of the network. It can achieve independent output of multiple classification labels, and solve the problem of decoupling recognition of compound fault components in planetary gearboxes. However, the single-scale feature extraction cannot fully explore multi-scale feature information in compound fault signals. This study proposes a capsule network combined with multi-scale convolutional feature fusion to diagnose the compound fault of planetary gearbox. The multi-scale features are extracted from STFT images of vibration signals using convolutional layers with different kernel sizes;secondly, a capsule network is designed to classify and identify the fault components by using the dynamic routing algorithm. The experiments are conducted to assess the performance of the proposed method, and the results indicates that it can effectively decoupling identify the compound faults with strong anti-interference and stability. © 2024 IEEE.

关键词： Dynamic routing algorithms

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Dual-point noncoaxial rotational Doppler effect towards synthetic OAM light fields for real-time rotating axis detection

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Light(advanced Manufacturing) 2023年第4期4卷 10-20页

作者： Yanxiang Zhang Zijing Zhang Han Lin Zhongquan Nie Rui Feng Yuan Zhao Baohua Jia School of Physics Harbin Institute of TechnologyHarbin 150001China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Centre for Atomaterials and Nanomanufacturing(CAN) School of ScienceRMIT UniversityMelbourne3000 VICAustralia

Probing the axis of a rotator is important in astrophysics,aerospace,manufacturing,machinery,automation,and virtual reality,*** optical solutions commonly require multiple sequential measurements via symmetry-broken light fields,which make them time-consuming,inefficient,and prone to accumulated ***,we propose the concept of a dual-point noncoaxial rotational Doppler effect(DNRDE)and demonstrate a one-shot detection technique to solve this *** on-demand synthetic orbital angular momentum(OAM)light beam impinges on a rotating scatterer surface,supporting dual-point rotational Doppler shifts,in which the information of the rotating axis is acquired by comparing these two frequency shifts with a prescribed *** existence of arbitrary dual-point Doppler shifts enables the one-time direct identification of rotating axis orientations,which is fundamentally inaccessible in single-point *** robust detection technique is compatible with generalised synthetic OAM light fields by utilising optical modal *** with traditional approaches,our DNRDE-driven detection approach exhibits a four-fold enhancement in measurement speed,higher energy efficiency,and superior accuracy with a maximal absolute measurement error of 2.23°.The proposed dual-point detection method holds great promise for detecting rotating bodies in various applications,such as astronomical surveys and industrial manufacturing.

关键词： Rotational Doppler effect Rotating axis orientations Real-time detection Orbital angular momentum Optical vortices

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Broadband Chaos Generation and Synchronization Induced by Integrated Tri-section Laser

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IEEE Access 2024年 13卷 1-1页

作者： Guo, Yuanyuan Wei, Wuyin Gao, Hua Zhang, Yuanye Zhao, Tong Jia, Zhiwei Chang, Pengfa Wang, Longsheng Wang, Anbang Wang, Yuncai Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan China College of Information Engineering Shanxi Vocational University of Engineering Science and Technology Taiyuan China School of Information Engineering Guangdong University of Technology Guangzhou China

Broadband chaos generation is numerically demonstrated using an integrated tri-section laser which is composed of mutually coupled distributed feedback (DFB) lasers with a phase section, and the broadband chaos synchronization of two DFB lasers is achieved using the integrated laser as a driver. The simulation results indicate that the integrated tri-section laser with optical feedback can generate broadband chaos with a bandwidth up to 34 GHz, based on dual-mode beating effect. The influence of feedback strength and frequency interval on the chaos bandwidth are studied in detail. As a common driving signal, the broadband chaos signal can induce the response DFB lasers to generate chaos signals with a bandwidth of no less than 25 GHz and meanwhile achieve chaos synchronization with a correlation coefficient beyond 0.98. The low correlation coefficient between the drive signal and the response signal ensures the security of the chaos carrier from the public channel. Moreover, the dynamic properties of the integrated laser and the influence of the external parameters on chaotic synchronization are also investigated. Authors

关键词： Distributed feedback lasers

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Phase-gain Dual-parametric Spectrum Measurement in Chaotic Brillouin Optical Correlation Domain Analysis

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IEEE Sensors Journal 2025年

作者： Chen, Jing Wang, Yahui Ma, Jinglian Huang, Haochen Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Taiyuan University of Technology College of Physics and Optoelectronics Taiyuan China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan030024 China

In this paper, the chaotic Brillouin phase-gain dual-parametric spectrum (BDS) is measured for the first time, which can realize high-accuracy and large-range dynamic strain demodulation in chaotic Brillouin optical correlation domain analysis (CBOCDA). The phase of the chaotic probe wave is measured by a Sagnac interferometer (SI) combined with an optical bandpass filter (OBPF) and a beat frequency locking technique. The Brillouin gain spectrum (BGS), Brillouin phase-shift spectrum (BPS), and BDS are measured in the chaotic BOCDA system through both simulation and experiment, and the feasibility of their demodulation with high-accuracy and large-range dynamic strain is verified. The chaotic BPS exhibits good linearity at the Brillouin frequency shift (BFS) and can be used to demodulate high-accuracy tiny strains. The measurement error of a 1 μΕ strain is only 0.0446 μΕ. The linear range of the chaotic BDS is extended to 150 MHz, and more than 10 mΕ dynamic strain measurements can be enabled by incorporating the slope-assisted method. © 2001-2012 IEEE.

关键词： Ultraviolet spectroscopy

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Research on Identification Strategy of Fault-Sensitive Frequency for Planetary Gearboxes

Research on Identification Strategy of Fault-Sensitive Frequ...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Xie, Ruitong Zhang, Mian Chen, Jiwei Zhu, Songsong Wang, Zhiyuan Zhao, Mengxiong Xiang, Hongbiao Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

Planetary gearboxes find extensive application in wind power generation, aerospace, industrial production and other fields. Harsh operational conditions and prolonged periods of continuous work often lead to various gear damages. Therefore, it is important to continuously monitor the health status of planetary gearboxes. However, the fault-sensitive frequencies of planetary gearboxes used in the existing signal models and fault diagnosis indicators are calculated theoretically or searched artificially. In response to this, this paper proposes a strategy for identifying fault-sensitive frequencies in planetary gearboxes intelligently by combining spectral amplitude analysis with three models: Random Forest (RF), Support Vector Machine (SVM) and Deep Neural Network (DNN). Experiments are carried out to verify the effectiveness and superiority of the proposed strategy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

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An Order Demodulation Analysis Method for Planetary Gearboxes

An Order Demodulation Analysis Method for Planetary Gearboxe...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Chen, Jiwei Xie, Ruitong Zhu, Songsong Zhao, Mengxiong Wang, Zhiyuan Zhang, Mian Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

In addressing challenges such as the speed change of planetary gearbox (PG) during operation and the complexity in extracting fault features, an order demodulation analysis method based on order tracking (OT) and variational mode decomposition (VMD) is proposed. Non-stationary time domain signals are transformed into relatively stable angular domain signals through angular resampling. The intrinsic mode function (IMF) is obtained by demodulation of the angular multi-component signal using the VMD method. The instantaneous order of a proper IMF is calculated via Hilbert Transform. The sensitive single component is selected by matching the meshing order and the central order of the instantaneous order. Finally, the amplitude of the characteristic order components extracted from the instantaneous order spectrum was used as features and Support Vector Machine (SVM) was employed for the classification of four different conditions in the sun gear. Comparing the results of the proposed method with Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), the experimental results demonstrate the effectiveness of the proposed method in diagnosing PGs under non-stationary conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Epicyclic gears

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Optical funnel:broadband and uniform compression of electromagnetic fields to an air neck

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Photonics Research 2021年第9期9卷 1675-1682页

作者： FEI SUN YICHAO LIU YIBIAO YANG Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China

An optical funnel,which performs as a passive electromagnetic compressor,can guide electromagnetic waves from a wide inlet to a narrow outlet without reflectance/scattering and squeeze electromagnetic fields uniformly to an air *** this study,an optical funnel is designed by precisely filling subwavelength ceramic blocks with a gradient refractive index inside a tapered *** gradient refractive index is designed by transformation optics,which is isotropic and all above unit,thus exhibiting a broadband *** to the mechanism of impedance matching over the whole funnel,extremely low reflectance/scattering and stable enhancement of fields can be *** field enhancement factor in different regions of the funnel(e.g.,in the air neck)can be flexibly designed just by modifying the funnel-width ratios.

关键词： scattering reflectance refractive

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Tracking performance limitations of networked control systems with packet dropouts and logarithmic quantization 41

Tracking performance limitations of networked control system...

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第41届中国控制会议

作者： Jianhao Li Xiaowei Jiang Hao Chen Shaoying Wang Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System College of Science Binzhou University School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,we focus on the tracking performance(TP) limitations of networked control systems(NCS s).The control system considered is a multi-input and multi-output(MIMO) discrete-time network control system with time delay,channel noise,packet dropouts,and logarithmic quantization communication *** modeling the channel,we assumed the channel noise to be additive white Gaussian noise(AWGN) and used a binary random process to model packet dropouts and a logarithmic quantizer to model the quantization *** explicit expression of the TP limitations of NCSs utilizing the two-degree-of-freedom(TDOF) controller is then derived using the frequency-domain approach,coprime decomposition,and Youla parameterization *** results show that the essential characteristics of the plant(locations and directions of nonminimum phase zeros and unstable poles) and network constraints(time delay,packet dropouts,quantization,and noise power spectral density) are closely related to the TP limitations.

关键词： Networked control systems tracking performance limitations packet dropouts logarithmic quantization

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Surgical Gesture Recognition in Open Surgery Based on 3DCNN and SlowFast 7

Surgical Gesture Recognition in Open Surgery Based on 3DCNN ...

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7th IEEE Information Technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Men, Yutao Luo, Jian Zhao, Zixian Wu, Hang Luo, Feng Zhang, Guang Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China Systems Engineering Institute Academy of Military Sciences People's Liberation Army Tianjin300161 China

ISBN: (纸本)9798350370782

In the field of computer-aided medicine, automated surgical gesture recognition is an important research direction. Its main applications include automated skills assessment, intraoperative guidance, and education and training systems. Current research has focused on robotic surgery, and there is less research on surgical gestures for open surgery. Therefore, in this study, a new simulated open surgery dataset was developed, and a series of surgical gestures for open surgery were defined for closure the abdomen surgery with the cooperation of professional doctors. In addition, this paper uses the classical algorithm 3DCNN and SlowFast model in the field of action recognition to perform offline recognition of surgical gestures for open surgery on the dataset. 3DCNN uses R3D and R(2+1)D models. The experimental results show that on the self-built open surgical dataset, the R3D model has the best surgical gesture recognition results, with an accuracy rate of 90.4%, a precision rate of 90.5%, and a recall rate of 90.0%. © 2024 IEEE.

关键词： Gesture recognition

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