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9th Symposium on Novel Photoelectronic Detection Technology and Applications

作者： Zhang, Qinghui Li, Hao Lu, Lei Pan, Wei Su, Zhilong Zhang, Mengya Lv, Pengtao Key Laboratory of Grain Information Processing and Control of Ministry of Education Henan University of Technology Ministry of Education Zhengzhou450001 China College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China Department of R & D OPT Machine Vision Tech Co. Ltd Dongguan523860 China Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering Science Shanghai University Shanghai200444 China

ISBN: (纸本)9781510664432

When using traditional phase-shift profilometry for 3D measurement, it is necessary to keep the measured object static during the shooting process. When the measured object is moving, errors will occur if the projection and capture of the fringe image is not fast enough. This paper proposes a new method to reconstruct the moving object by double sampling. A trigger control device is applied to the camera and projector, which ensures that after each projection, two consecutive images are captured before the next projection. Then, the phase information is retrieved by analyzing the relationship between the motion and fringe patterns. Finally, the moving object is retrieved successfully. The proposed method increased the frame rate of the moving object reconstruction. © 2023 SPIE.

关键词： Profilometry

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Simulation Research on Generalized Proportional Integral Observer Based Active Disturbance Rejection control for Coarse Pointing Assembly

Simulation Research on Generalized Proportional Integral Obs...

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2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Jijun Ma Yulong Guo YuNing Wang Yongkang Shi Beijing Research Institute of Telemetry Beijing China Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Research Institute of Telemetry Beijing China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

The coarse pointing assembly (CPA), as the outer loop of the laser terminal, its tracking stability is the basis for ensuring laser communication. This paper presents the model of the CPA. Aiming at the disturbance factors in the low-speed operation process of the CPA, an active disturbance rejection control (ADRC) method for the position loop of the CPA is designed based on the generalized proportional integral observer (GPIO) to achieve disturbance compensation control. Finally, simulations are carried out on the system model. The simulation results show that compared with the PID control strategy adopted, the proposed ADRC strategy based on GPIO of the CPA can effectively improve the tracking accuracy.

关键词： Robust control Tracking loops Accuracy Simulation Computational modeling Laser stability Observers Laser modes Stability analysis Assembly

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intelligent 3D Visual defect Detection for Industrial Applications 3

Intelligent 3D Visual defect Detection for Industrial Applic...

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2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022

作者： Yang, Rui Ke, Hualin Gan, Lin Li, Yuhong Hu, Ruihan Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China Xinjiang Production and Construction Corps Key Laboratory of Modern Agricultural Machinery Shihezi University Shihezi China

Currently, new energy industries such as electric vehicles and energy storage batteries are experiencing rapid growth throughout the world. As a recognized ideal energy storage element, lithium batteries have also attracted considerable interest. To improve image contrast, the industry employs image preprocessing algorithms. Due to the high requirement of image consistency in the template matching method, which is difficult to meet in practice, and the large apparent difference between defects, it is challenging to design features. Therefore, the framework for defect detection is based on a method of deep learning with strong feature expression capability. In light of the severe imbalance in the number of samples in defect detection, data augmentation and generation methods are used to simulate real samples in order to improve the training effect of deep neural networks and alleviate the burden of data annotation to some extent. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Lithium batteries

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controlled on-chip fabrication of large-scale perovskite single crystal arrays for high-performance laser and photodetector integration

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Light(Science & Applications) 2023年第4期12卷 558-569页

作者： Zhangsheng Xu Xun Han Wenqiang Wu Fangtao Li Ru Wang Hui Lu Qiuchun Lu Binghui Ge Ningyan Cheng Xiaoyi Li Guangjie Yao Hao Hong Kaihui Liu Caofeng Pan CAS Center for Excellence in Nanoscience Beijing Key Laboratory of Micro-nano Energy and SensorBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 101400China School of Nanoscience and Technology University of Chinese Academy of SciencesBeijing 100049China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Colllege of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China Center on Nanoenergy Research School of Physical Science and TechnologyGuangxi UniversityNanning 530004China Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China College of Materials Science and Engineering Ocean University of ChinaQingdao 266100China State Key Laboratory for Mesoscopic Physics Frontiers Science Centre for Nano-optoelectronicsSchool of PhysicsPeking UniversityBeijing 100871China Songshan Lake Materials Laboratory Dongguan 523808China

Metal halide perovskites possess intriguing optoelectronic properties,however,the lack of precise control of on-chip fabrication of the large-scale perovskite single crystal arrays restricts its application in integrated ***,we report a space confinement and antisolvent-assisted crystallization method for the homogeneous perovskite single crystal arrays spanning 100 square centimeter *** method enables precise control over the crystal arrays,including different array shapes and resolutions with less than 10%-pixel position variation,tunable pixel dimensions from 2 to 8 pm as well as the in-plane rotation of each *** crystal pixel could serve as a high-quality whispering gallery mode(WGM)microcavity with a quality factor of 2915 and a threshold of 4.14μJ cm^(-2).Through directly on-chip fabrication on the patterned electrodes,a vertical structured photodetector array is demonstrated with stable photoswitching behavior and the capability to image the input patterns,indicating the potential application in the integrated systems of this method.

关键词： arrays crystal precise

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Norm-Integrated Softmax Loss For Deep Face Recognition

Norm-Integrated Softmax Loss For Deep Face Recognition

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IEEE International Conference on image processing

作者： Jun Chen Yiwei Wang Haiyan Zhang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

The key to face recognition lies in how to improve the model’s ability to extract facial features. To this end, numerous loss functions based on different metrics have been proposed to increase the margin of feature distinction between different classes. Methods based on Cosine distance significantly enhance face recognition performance by focusing on angular constraints between samples and classes, demonstrating their superiority over those based on Euclidean distance. However, a significant oversight in these methods is the neglect of feature magnitude’s importance in representing facial features. To address this gap, our study introduces the NormIntegrated Softmax loss (NIface loss), a novel loss function that amalgamates feature norms with angular information. This integration offers a comprehensive perspective for feature classification, augmenting the compactness of intra-class features. Extensive evaluations on large-scale public datasets have demonstrated the efficacy of NIface loss in enhancing recognition accuracy and stability.

关键词： Measurement Technological innovation image recognition Accuracy Face recognition Focusing Euclidean distance

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Design of Load Frequency controller for Power System Based on Equivalent Input Disturbance Method

Design of Load Frequency Controller for Power System Based o...

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New Energy and Energy Storage System control Summit Forum (NEESSC)

作者： Jianrong Zhang Hang Xu Hongzhang Wang Chuanke Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350389012

ISBN: (纸本)9798350389029

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively.

关键词： Perturbation methods Process control Interference Power system stability control systems Linear matrix inequalities Numerical models Frequency control Load modeling Energy storage

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Dynamic Event-Triggered Model Predictive control for Multiple Platoons under Non-Ideal Communications

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IEEE Internet of Things Journal 2025年

作者： Han, Qiaoni Xu, Chengfei Wang, Xiaocheng Yang, Hongjiu Zuo, Zhiqiang Yang, Bo Guan, Xinping Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin300072 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Tianjin University School of Electrical and Information Engineering Tianjin300072 China Tianjin Normal University Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission College of Electronic and Communication Engineering Tianjin300387 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China

The uncertainty of wireless communication seriously affects the control performance of the platoon. In this paper, a model predictive control (MPC) method based on dynamic event-triggering is proposed to address the impact of non-ideal communications on multi-vehicle systems. Firstly, a hierarchical platoon architecture combining backbone layer and sub-platoon layers is proposed to achieve efficient coordination among multiple platoons, and a communication-aware control mechanism is designed for each vehicle to effectively mitigate the adverse effects of non-ideal communication scenarios. Secondly, a dynamic event-triggering mechanism is established for each vehicle, which is related to time-varying delay and random packet loss parameters, so as to effectively reduce the frequency of MPC solutions and data transmission. Additionally, based on different communication topologies, distributed model predictive controllers are suggested for backbone layer and sub-platoon layer to achieve precise and comfortable tracking. Then, sufficient conditions are provided to ensure the recursive feasibility of the MPC algorithm and the stability of the platoon system. Finally, extensive simulations are conducted, and the results demonstrate the effectiveness of the proposed algorithm in terms of control performance and low computational complexity under non-ideal communication conditions. © 2014 IEEE.

关键词： Predictive control systems

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Hybrid Data-Free Knowledge Distillation

arXiv

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arXiv 2024年

作者： Tang, Jialiang Chen, Shuo Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Center for Advanced Intelligence Project RIKEN Japan Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generation-based methods train student networks by collecting massive real examples and generating synthetic examples, respectively. However, they inevitably become weak in practical scenarios due to the difficulties in gathering or emulating sufficient real-world data. To solve this problem, we propose a novel method called Hybrid Data-Free Distillation (HiDFD), which leverages only a small amount of collected data as well as generates sufficient examples for training student networks. Our HiDFD comprises two primary modules, i.e., the teacher-guided generation and student distillation. The teacher-guided generation module guides a Generative Adversarial Network (GAN) by the teacher network to produce high-quality synthetic examples from very few real-world collected examples. Specifically, we design a feature integration mechanism to prevent the GAN from overfitting and facilitate the reliable representation learning from the teacher network. Meanwhile, we drive a category frequency smoothing technique via the teacher network to balance the generative training of each category. In the student distillation module, we explore a data inflation strategy to properly utilize a blend of real and synthetic data to train the student network via a classifier-sharing-based feature alignment technique. Intensive experiments across multiple benchmarks demonstrate that our HiDFD can achieve state-of-the-art performance using 120 times less collected data than existing methods. Code is available at https://***/tangjialiang97/HiDFD. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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Optimized Statistical Model for Complex Chemical Processes Monitoring

Optimized Statistical Model for Complex Chemical Processes M...

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Data Driven control and Learning Systems (DDCLS)

作者： Jian Zhang Xiaohe Qu Zhiwei Lei Haifeng Zhang Kai Zhong Datang East China Electric Power Test and Research Institute Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei Anhui China

The traditional kernel principal components analysis (KPCA) and linear discriminant analysis (LDA) have been verified to be two effective approaches for fault detection and diagnosis in recent years. Nevertheless, the conventional method and corresponding improved ones still exposed their deficiencies in some ways. Facing this dilemma, this paper presents a combination of optimized KPCA and modified LDA (OKPCA-MLDA), in which the OKPCA avoids the loss of original features after centralizing data in the eigenspace by adjusting covariance matrix's eigenvalue and transforming the distribution of variables thus providing representative and abundant principal components for the classifier. In addition, the MLDA maximizes a brand new objective function in feature space which achieves better classification performance than the conventional LDA, then utilizing diagnostic thresholds and similarity coefficients to identify the fault types. Based on the combined model, not only the fault detection and diagnosis can be realized simultaneously but also the accuracy of detection and diagnosis can be guaranteed. Furthermore, the simulation experiments on Tennessee Eastman (TE) benchmark process clearly illustrated the superiority of our proposed strategy.

关键词：

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Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

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Chinese Automation Congress (CAC)

作者： Yuan Huang Chi Xu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Recent advancements in Novel View Synthesis using neural radiance fields and 3D Gaussian splatting have demon-strated promising results. However, these methods conventionally rely on accurate initial poses and point clouds from the model of structure from motion, which poses challenges in sparse input views. To addressing these drawbacks, we introduces an novel method for view synthesis based on 3D Gaussian splatting. Our approach operates on sparse input views without the prerequisite of pose priors, achieving reconstruction and real-time rendering of novel perspectives. For the deficiency of camera poses and point cloud, we employ an end- to-end deep learning model to recover the 3D structure from a few of 2D images to initialize the 3D Gaussian point cloud. In addressing the issue with few-shot, we utilize the differentiable rasterization module to render depth map and apply regulation on it. Additionally, we incorporate supervision between input views by interpolating to generate novel perspectives during training. Experimental results demonstrate that our proposed method significantly enhances the capabilities of 3D Gaussian splatting for novel view synthesis in sparse views and without the necessity of camera pose priors.

关键词： Point cloud compression Training Solid modeling Three-dimensional displays Structure from motion Cameras Rendering (computer graphics) Regulation Real-time systems image reconstruction

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