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2023 International Conference on Computer Application and Information Security, ICCAIS 2023

作者： Bai, Yun Wang, Haobo Xing, Feng Lu, En Liu, Wencong Engineering Training Center Xi'an University of Science & Technology Shaanxi Xi'an China School of Electric and Control Engineering Xi'an University of Science & Technology Shaanxi Xi'an China

ISBN: (纸本)9781510675032

Considering the impact of background noise, the traditional bridge crack detection method cannot completely extract the crack features and effectively fuse them, resulting in low crack detection accuracy, false and missed detection. This paper presents a bridge crack detection algorithm based on improved U-Net (I-U-Net) network, specifically designed to address the mentioned challenges. Firstly, the residuals module with bottleneck structure (Res-Bot) is combined with the U-Net model to obtain complete crack information. Secondly, in order to eliminate the interference of background noise, optimized convolutional block attention module (O-CBAM) is introduced, adding dimensionality reduction convolutional layer and dilated convolutional layer, which effectively reduces the number of network parameters while simultaneously improving the feature extraction capabilities of the network. Thirdly, based on the idea of multi-size fusion, different sizes of convolution kernels are selected according to different levels to extract crack information, and the encoder-decoder-multi-size fusion (EDMSF) module is constructed. Finally, the effectiveness of the I-U-Net network is demonstrated through the public bridge crack dataset and the self-made dataset. © 2024 SPIE.

关键词： Crack detection

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Performance analysis of UAV-based mixed underwater PLC-RF systems

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Digital Communications and Networks 2024年第5期10卷 1332-1340页

作者： Shenghai Chen Liang Yang Xianfu Lei College of Computer Science and Electronic Engineering Hunan UniversityChangsha410082China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua418000China School of Information Science and Technology Southwest Jiaotong UniversityChengdu610031China

In this study,we analyzed the performance of an Unmanned Aerial Vehicle(UAV)-based mixed Underwater Power Line Communication-Radio Frequency(UPLC-RF)*** this network,a buoy located at the sea is used as a relay to transmit signals from the underwater signal source to the UAV through the PLC *** assume that the UPLC channel obeys a log-normal distribution and that the RF link follows the Rician *** this model,we obtained the closed-form expressions for the Outage Probability(OP),Average Bit-error-rate(ABER),and Average Channel Capacity(ACC).In addition,the asymptotic analysis of the OP and ABER was performed,and an upper bound for the average capacity was ***,the analytical results were verified by Monte Carlo simulation thereby demonstrating the effect of impulse noise and the altitude of the UAV on network performance.

关键词： ABER Average bit-error-rate ACC Average channel capacity OP Outage probability UAV Unmanned aerial vehicle UPLC Underwater power line communication

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Superhydrophobic ceramic membrane coupled with a biphasic solvent for efficient CO_(2)capture

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Green Energy & Environment 2025年第4期10卷 834-844页

作者： Kaili Xue Zhen Chen Xiaona Wu Heng Zhang Haiping Chen Junhua Li State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Beijing Key Laboratory of Pollutant Monitoring and Control in Thermoelectric Production Process School of EnergyPower and Mechanical EngineeringNorth China Electric Power UniversityBeijing102206China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing102206China

An innovative strategy was proposed by integration of membrane contactor(MC)with biphasic solvent for efficient CO_(2) capture from flue *** accessible fly ash-based ceramic membrane(CM)underwent hydrophobic modification through silane grafting,followed by fluoroalkylsilane decoration,to prepare the superhydrophobic membrane(CSCM).The CSCM significantly improved resistance to wetting by the biphasic solvent,consisting of amine(DETA)and sulfolane(TMS).Morphological characterizations and chemical analysis revealed the notable enhancements in pore structure and hydrophobic chemical groups for the modified *** of wetting/bubbling behavior based on static wetting theory referred the liquid entry pressure(LEP)of CSCM increased by 20 kPa compared to pristine *** with traditional amine solvents,the biphasic solvent presented the expected phase *** experiments demonstrated that the CO_(2) capture efficiency of the biphasic solvent increased by 7%,and the electrical energy required for desorption decreased by 32%.The 60-h continuous testing and supplemental characterization of used membrane confirmed the excellent adaptability and durability of the *** study provides a potential approach for accessing hydrophobic ceramic membranes and biphasic solvents for industrial CO_(2) capture.

关键词： Carbon capture Membrane contactor Hydrophobic modification Membrane wetting Biphasic solvent

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Identification of Fractional Discrete Linear System Based on Information Compression Matrix 41

Identification of Fractional Discrete Linear System Based on...

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第41届中国控制会议

作者： Hongwei Wang Bingchen Chen Chenlei Liu Qian Zhang School of Control Science and Engineering Dalian University of Technology School of Electrical Engineering Xinjiang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The identification issues of fractional system mainly are how to deal with structure identification and parameters *** this paper,the single input and single output fractional-order linear discrete system with the colored noise is first ***,the information compression matrix is constructed by objective functions with different orders,and the decomposition and transformation theorem of the information compression matrix and its proof are *** this basis,a structure judgment criterion for extracting the optimal model is proposed to simultaneously realize the identification of the model structure,order and parameters of fractional order systems by alternating calculation of information compression *** simulation results demonstrate the effectiveness of the proposed method.

关键词： fractional order system information compression matrix recursive identification matrix decomposition discrete system

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Object Tracking Algorithm Using Siamese Attention Mechanism based Key Point Network 23

Object Tracking Algorithm Using Siamese Attention Mechanism ...

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15th International Conference on Digital Image Processing, ICDIP 2023

作者： Zhang, Feng Liu, Guifu Yuan, Shuai Kong, Xiangjie Geng, Jinyu School of Electrical and Control Engineering Shenyang Jianzhu University China School of Computer Science and Engineering Shenyang Jianzhu University China

ISBN: (纸本)9798400708237

The tracker based on Siamese network usually adopts the cross-correlation of convolutional features between the object branch and the search branch to describe the visual object tracking task as a similarity matching. However, most trackers apply backbone networks to represent multi-scale features in a hierarchical manner, which has limitations in distinguishing similar object. In addition, the feature information on each channel and spatial region is treated equally in the calculation process. In fact, the feature importance of these locations is not the same, and the anchor box detection mechanism requires setting a large number of anchor boxes with redundant hyperparameters, which can lead to computational and memory overload. As for these problems, this paper proposes an object tracking algorithm using siamese attention mechanism based key point network, called SAMR (Siamese Attention Mechanism Reppoints). First of all, the backbone network res2net is used to represent fine-grained multi-scale features on a hierarchical basis for increasing the receptive field of each layer. Then the channel and spatial attention information of the attention mechanism is to enhance the discriminant ability and positioning ability of the feature map. Finally, a set of key points anchor-free frames is adopted to detect and track the object. Experiments on challenging datasets such as VOT2018, VOT2019, and OTB100 illustrate that the SAMR proposed in this paper is superior to other advanced trackers in tracking accuracy. © 2023 ACM.

关键词： Object detection

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Receding horizon control for continuous-time mean-field systems

Receding horizon control for continuous-time mean-field syst...

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作者： Gao, Rong Liu, Junzhe Zhang, Fang Xu, Juanjuan Wang, Hongxia School of Mathematics and Statistics Science Ludong University Yantai China School of Control Science and Engineering Shandong University Jinan China College of Electrical and Automation Engineering Shandong University of Science and Technology Qingdao China

In this paper, we study the receding horizon control (RHC) stabilization of continuous-time mean-field system. An explicit RHC controller is obtained by introducing a cost function with two terminal matrices and the conditions that make the system stable are also obtained;that is, when two coupled Lyapunov inequalities are satisfied, the system controlled by RHC is stabilized. Finally, a simulation example is given to verify the effectiveness of the proposed strategy. © 2023 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Stabilization

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Adaptive Particle Swarm Optimization of U-net Parameters for Marine Aquaculture Image Segmentation 13

Adaptive Particle Swarm Optimization of U-net Parameters for...

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13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Zhao, Jin Wang, Jun Han, Min Fan, Jianchao School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Department of Computer Science Department of Data Science City University of HongKong Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798331516147

Marine aquaculture image segmentation plays a crucial role in managing aquatic resources and environmental protection. Traditional deep learning models rely on manual parameter tuning for image segmentation, which limits their efficiency and accuracy. This paper proposes an adaptive Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the U-net model automatically. The algorithm dynamically adjusts the PSO parameters based on the population’s entropy and clustering metrics and employs a hill-climbing algorithm to address the issue of the PSO easily falling into local optima, enhancing the algorithm’s adaptability. The proposed algorithm updates and iterates particles to automatically find suitable model parameters. The remote sensing data used in this experiment were from the Yellow Sea aquaculture area near Dalian, China, with a segmentation accuracy of 91.8%. This method improves segmentation accuracy, reduces the burden of manual parameter tuning, and provides an effective solution for optimizing deep learning models. © 2025 IEEE.

关键词： Aquaculture

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PMSM Vector control System Based on Improved Active Disturbance Rejection Speed controller 2

PMSM Vector Control System Based on Improved Active Disturba...

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2nd International Conference on Robotics, Artificial Intelligence and Intelligent control, RAIIC 2023

作者： Deng, Jijie Chen, Yong Wang, Wei Tiangong University School of Control Science and Engineering Tianjin China Tiangong University School of Electronic & Information Engineering Tianjin China

ISBN: (纸本)9798350328004

The traditional ADRC speed regulator utilizes a fast optimal function known as the fal function. However, this function's derivative is discontinuous at segment points, leading to potential negative effects on the system's performance. In order to address this issue and optimize control effectiveness, the nonlinear function need to be enhanced to ensure continuity and differentiability throughout all segment points. Furthermore, ADRC requires adjustment of numerous parameters, which can be challenging. To alleviate this difficulty, a fuzzy controller is employed to adjust the non-linear error feedback link. This helps reduce the complexity associated with parameter tuning in ADRC. Simulation results demonstrate that the ADRC speed controller, incorporating the improved nonlinear function, achieves superior control performance compared to the original controller. Additionally, the fuzzy controller proves effective in easing the parameter adjustment process. © 2023 IEEE.

关键词： controllers

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Diagnosing Oral Mucosal Diseases Using Deep Learning

Diagnosing Oral Mucosal Diseases Using Deep Learning

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2024 China Automation Congress, CAC 2024

作者： Lu, Miao Zhang, Jiayuan Cao, Yuqi Zhang, Rui Zhang, Guangxin State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Information Center Stomatology Hospital Zhejiang University School of Medicine Hangzhou China

ISBN: (纸本)9798350368604

Oral Potentially Malignant Disorders (OPMD) contain a variety of diseases with complex pathological features, most of which are associated with systemic diseases and have a high risk of malignant transformation, making diagnosis challenging. In this regard, we adopted rapidly developing artificial intelligence methods in recent years, using deep learning for feature extraction and multi-task research on images of oral mucosal diseases. Concerning the severity of oral mucosal diseases, we employed a Swin Transformer-based classification model for the classification of benign diseases, OPMD, and oral cancer, achieving an accuracy of 94.2% and a precision of 95.0%. Further research explored the instance segmentation algorithm based on Mask2Former, comparing it with classic segmentation algorithm to achieve automated segmentation of oral mucosal inflammatory lesions. The study shows that deep learning methods can effectively discriminate the severity of oral mucosal disease images and segment lesion areas, providing solid research foundation for intelligent assisted diagnosis. © 2024 IEEE.

关键词： Image segmentation

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Adaptive SSO Suppressor Based on SVD-Prony Algorithm in PV Grid-Connected System

Adaptive SSO Suppressor Based on SVD-Prony Algorithm in PV G...

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International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Liang, Liyuan Sun, Dongyang Liu, Jinfeng School of Electrical and Electronic Engineering Harbin University of Science and Technology Heilongjiang Harbin150080 China School of Measurement Control Technology and Communication Engineering Harbin University of Science and Technology Heilongjiang Harbin150080 China

ISBN: (纸本)9789819618514

The risk of sub-synchronous oscillation of PV grid-connected system is increased by the decrease of power grid strength or the disturbance of DC voltage. It is theoretically necessary and engineering urgent to study the mechanism of sub-synchronous oscillation of PV grid-connected system and put forward corresponding suppression strategies. In this paper, a dq synchronous rotating coordinate system control model of PV grid-connected system with subsynchronous oscillation is established, and the influence of subsynchronous oscillation on PV grid-connected system is analyzed according to the model. An adaptive SSO suppressor based on SVD-Prony algorithm is designed to track and suppress sub-synchronous oscillations that vary in each frequency band. This algorithm can extract the effective mode information of the subsynchronous oscillation in PV grid-connected system, and then update it to the central resonant frequency of the suppressor, and generate the output which can compensate the subsynchronous oscillation component in the closed-loop control system. Finally, a simulation experiment platform is set up to verify the effectiveness of the suppression strategy proposed in this paper. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Closed loop control systems

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