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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Chen, Li-Jia Zou, Jia-Min Zhou, Yang Hao, Guo-Zhu Wang, Yang School of Shipping Wuhan University of Technology Wuhan430070 China Hubei Provincial Key Laboratory of Inland Waterway Shipping Technology Wuhan University of Technology Wuhan430070 China Intelligent Transportation System Research Center Wuhan University of Technology Wuhan430070 China National Key Laboratory of Waterway Traffic Control Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9789819639762

Waterway navigation scene segmentation is crucial for safe and efficient autonomous vessel operation. To address the issues of large parameter sizes in current high-resolution semantic segmentation models, the difficulty in deployment on embedded devices, and inaccurate segmentation in navigation scenarios, this study proposes an improved Fast-SCNN-based real-time semantic segmentation network for waterway scenes. The proposed network is enhanced by incorporating a dual attention mechanism in the context branch, which allows feature extraction along spatial and channel dimensions to be guided more effectively, thereby improving accuracy. A pyramid pooling module based on decomposed dilated convolution is designed to enhance the model's multi-scale feature representation capabilities while ensuring real-time performance is maintained. Additionally, a loss function combining Focal Loss and Dice Loss is introduced to enhance focus on hard-to-classify samples and improve prediction accuracy for target regions, thereby significantly enhancing the model's ability to recognize minority-class targets. Experimental results have demonstrated that the improved model achieves a segmentation accuracy (mIoU) of 80.6% on the constructed On_Water_Dataset, with an inference speed of 90.1 frames per second, Segmentation accuracy increased by 16.9% relative to the original model. Deployment and experimental verification on embedded devices have confirmed that real-time performance is maintained while effectively segmenting complex backgrounds and multi-scale objects in waterway navigation scenarios. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Semantic Segmentation

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A Soft-Sensor Modeling Method Based on Gated Stacked Isomorphic Autoencoder 41

A Soft-Sensor Modeling Method Based on Gated Stacked Isomorp...

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第41届中国控制会议

作者： Jianjun Yang Xiaolu Xu Xiaohui Yin Wenxing Liu Yi Yuan Jian Peng 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 Huaxin Cement Co. Ltd

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Soft sensing mainly studies the real-time prediction of some key performance indicators or quality variables in the actual production process,which has the role of guiding production in the actual production *** stacked autoencoder is a multi-layer autoencoder *** input variables will be encoded and decoded through each layer of autoencoders,and the obtained hidden features will be retained as the input of the next *** this way,high-level data features can be successfully learned from the input layer to the intermediate *** isomorphic autoencoder reconstruct an identical data input layer,and the reconstruction is performed by minimizing the error of the decoded data from the original input ***,for a soft measurement model,some data information may also reduce the accuracy or generalization of the *** order to overcome the above shortcomings,this paper proposes a gated stacked isomorphic autoencoder,which evaluates the contribution of each hidden layer feature through the gating unit,and then integrates the information of different hidden layers to complete the prediction and estimation of related main ***,the effectiveness and feasibility of the method are verified in practical industrial cases.

关键词： Deep learning soft sensor stacked autoencoder gating unit

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A Multi-Time-Scale Prediction Method for Blast Furnace Gas Utilization Rate Based on Causality Analysis

A Multi-Time-Scale Prediction Method for Blast Furnace Gas U...

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2023 China Automation Congress, CAC 2023

作者： Zhao, Guoyu An, Jianqi Guo, Yunpeng Yang, Chenglin He, Yong School of Future Technology China University of Geosciences China School of Automation China University of Geosciences China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798350303759

Blast furnace operating parameters regulate the gas utilization rate (GUR), and different operating parameters affect the GUR on different time scales. However, the existing methods only analyze and model the prediction on a single-time scale, and the accuracy of the model needs to be improved. In this paper, a multi-time-scale prediction method of blast furnace gas utilization rate based on causality is proposed. Firstly, according to the production characteristics of the blast furnace, burden and blast supply are the operation means to regulate the blast furnace on different time scales. Then, this paper presents a blast furnace operation parameter extraction method fusing correlation coefficient and information entropy, and selects two most informative parameters to characterize the operation. On this basis, the causal analysis method is used to prove that the selected operation parameters affect the development trend of GUR. Finally, the long and short time scale prediction models of GUR are established, which are verified by the data of the actual blast furnace production process, improving the prediction accuracy of the GUR efficiently. © 2023 IEEE.

关键词： Blast furnaces

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Distributed Event-Triggered Formation control for a Multi-robotic Fish system

Distributed Event-Triggered Formation Control for a Multi-ro...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Dai, Shijie Wu, Zhengxing Tan, Min Yu, Junzhi School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9789811966125

This paper investigates the formation control problem for a multi-robotic fish system and a distributed event-triggered-based formation control framework is proposed. The framework consists of a communication topology, a distributed formation control law, and a dynamic event-triggered communication mechanism. In particular, a position-based formation control law is presented to drive the multi-robotic fish system to an anticipated configuration based on local measurements while keeping pace with a moving target. Meanwhile, a dynamic event-triggered mechanism is utilized to measure importance of the interactive information and decide the communication timing. The proposed formation control method shows its merits to greatly reduce communication consumption with a limited loss of formation control performance. Finally, simulations with quantitative comparisons are presented to verify the effectiveness of the proposed framework. This formation control framework provides a solid foundation for future marine cooperative control of the multi-robotic fish system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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A Novel Rolling Bearing Vibration Impulsive Signals Detection Approach Based on Dictionary Learning

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1188-1198页

作者： Chuan Sun Hongpeng Yin Yanxia Li Yi Chai School of Big Data&Software Engineering Chongqing UniversityChongqing 401331China Key Laboratory of Complex System Safety and Control Ministry of EducationChongqing UniversityChongqing 400044China

The localized faults of rolling bearings can be diagnosed by its vibration impulsive ***,it is always a challenge to extract the impulsive feature under background noise and non-stationary *** paper investigates impulsive signals detection of a single-point defect rolling bearing and presents a novel data-driven detection approach based on dictionary *** overcome the effects harmonic and noise components,we propose an autoregressive-minimum entropy deconvolution model to separate harmonic and deconvolve the effect of the transmission *** address the shortcomings of conventional sparse representation under the changeable operation environment,we propose an approach that combines K-clustering with singular value decomposition(K-SVD)and split-Bregman to extract impulsive components *** experiments on synthetic signals and real run-to-failure signals,the excellent performance for different impulsive signals detection verifies the effectiveness and robustness of the proposed ***,a comparison with the state-of-the-art methods is illustrated,which shows that the proposed approach can provide more accurate detected impulsive signals.

关键词： Dictionary learning impulsive signals detection Kclustering with singular value decomposition(K-SVD) minimum entropy deconvolution rolling bearing signal processing

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Design and Wave Propagation Characterization of Starchiral Metamaterials

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Acta Mechanica Solida Sinica 2022年第2期35卷 215-227页

作者： Yajun Xin Han Wang Cong Wang Jinxin Yao Qian Ding Haoqiang Gao Shuliang Cheng Yongtao Sun Key Laboratory of Green Construction and Intelligent Maintenance for Civil Engineering of Hebei Province Yanshan UniversityQinhuangdao 060000China Hebei Province Low-Carbon and Clean Building Heating Technology Innovation Center Yanshan UniversityQinhuangdao 060000China Department of Mechanics and Tianjin Key Laboratory of Nonlinear Dynamics and Control Tianjin UniversityTianjin 300072China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China

Metamaterials with simple artificial topological properties made from industrially produced single-phase materials have extraordinary innovation and *** this paper,we investigated wave propagation characteristics of a hexastarchiral lattice metamaterial with periodic assemblies and used the finite element(FE)method to study the band gap ***,in order to understand the mechanism of band gaps,we discussed the mode shapes of unit cells and found that the bending of the ligament and the overall rotation have a high correlation with the generation of omnidirectional band *** relationships bet ween geometric parameters and band gap properties have also been systematically studied,which demonstrated that the band gaps of the proposed metamaterial could be reasonably predicted through the evolution of geometric ***,the transmission characteristics of finite sandwich panel structures composed of periodic unit cells were calculated to verify the correctness of the band gap simulation results,which proved that the proposed artificial metastructure has potential application value in vibration and noise reduction projects.

关键词： Hexastarchiral lattice metamaterials Band gap properties Finite element method Rotational resonance

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3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach 8th

3D Point Cloud-Based Lithium Battery Surface Defects Detecti...

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8th International Workshop on Advanced Computational Intelligence and intelligent Informatics, IWACIII 2023

作者： Rehman, Zia Ur Wang, Xin Alsumeri, Abdulrahman Abdo Ali Khan, Malak Abid Ali Ma, Hongbin State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819975891

Detecting the lithium battery surface defects is a difficult task due to the illumination reflection from the surface. To overcome the issue related to labeling and training big data by using 2D techniques, a 3D point cloud-based technique has been proposed in this paper. The 3D point cloud-based defect detection of lithium batteries used feature-based techniques to downscale the point clouds to reduce the computational cost, extracting the normals of the points and calculating their differences to detect the defects of the battery which assure the quality of the product. This paper offers a novel strategy using 3D point clouds to get beyond the labeling and training challenges involved with conventional 2D approaches. This 3D point cloud-based approach for lithium battery fault identification makes use of feature-based methods to improve the point cloud data and lessen the computing burden. In our work, the experiments show that the feature-based technique precisely detects the affected surface of the battery. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Lithium batteries

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10-Hertz squeezed light source generation on the cesium D_(2)line using single photon modulation

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Frontiers of physics 2023年第3期18卷 167-174页

作者： Guan-Hua Zuo Yu-Chi Zhang Gang Li Peng-Fei Zhang Peng-Fei Yang Yan-Qiang Guo Shi-Yao Zhu Tian-Cai Zhang State Key Laboratory of Quantum Optics and Quantum Optics Devices Collaborative Innovation Center of Extreme OpticsInstitute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China College of Physics and Electronic Engineering Shanxi UniversityTaiyuan 030006China Department of Physics Zhejiang UniversityHangzhou 310027China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China

Generation of squeezed light source is a promising technique to overcome the standard quantum limit in precision ***,we demonstrate an experimental generation of quadrature squeezing resonating on the cesium D_(2)line down to 10 Hz for the first *** maximum squeezing in audio frequency band is 5.57 ***,we have presented a singlephoton modulation locking to control the squeezing angle,while effectively suppressing the influence of laser noise on low-frequency *** whole system operates steadily for *** generated low-frequency squeezed light source can be applied in quantum metrology,light–matter interaction investigation and quantum memory in the audio frequency band and even below.

关键词： squeezed state optical parametric amplifier low-frequency squeezing

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Object Detection and Multiple Objective Optimization Manipulation Planning for Underwater Autonomous Capture in Oceanic Natural Aquatic Farm

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Journal of Field Robotics 2025年

作者： Hai, Huang Tao, Jiang Xinyu, Bian Hao, Zhou Xu, Yang Gang, Wang Hongde, Qin Xinyue, Han National Key Laboratory of Science and Technology on Underwater Vehicle Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Bei Jing China

Underwater autonomous capture operations offer significant potential for reducing labor and health risks in sea organism industries. This study presents a comprehensive solution for cross-domain underwater object detection and autonomous capture. A novel unsupervised domain adaptive learning method is proposed, integrating multiscale domain adaptive modules and attention mechanisms into a Faster Region-Convolutional Neural Network framework. This approach enhances feature alignment across diverse aquatic domains without parameter tuning. Additionally, an efficient, parameterless constrained multiobjective optimization algorithm is introduced for underwater autonomous mobile capture, integrating parameterized trajectory planning with innovative features, such as adaptive mutation strategies and constraint violation tolerance. The proposed approaches are extensively validated through simulations, tank experiments, and real-world oceanic trials in the Natural Aquatic Farm of Zhangzidao Island. Results demonstrate the system's robustness in complex underwater environments with varying currents, with experimental outcomes validating the accuracy and reliability of detection and capture capabilities. This research significantly advances autonomous underwater systems' capabilities in object detection and capture tasks, addressing complex challenges in realistic organism capture applications across diverse aquatic environments. © 2025 Wiley Periodicals LLC.

关键词： Health risks

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Adaptive Sliding Mode control for Flexible Dual-manipulator with Friction Compensation

Adaptive Sliding Mode Control for Flexible Dual-manipulator ...

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2022 Chinese Automation Congress, CAC 2022

作者： Song, Tao Zheng, Shiqi Sun, Jiachun Li, Liangguang Chang, Qing Li, Zhipeng China University of Geosciences Wuhan Campus School of Automation China Hubei Key Laboratory of Advanced Control and Intelligent Automation Fo Complex Systems Wuhan China

ISBN: (纸本)9781665465335

This paper focuses on the coordinated tracking control scheme of dual-manipulator based on friction compensation. First, a new dual-manipulator model with flexible joints and friction is constructed;Second, a new adaptive neural control method is proposed for the dual-manipulators with flexible joints. Neural networks are used to approximate the unknown nonlinear dynamics in the model;Third, new state observers are constructed to estimate the joint friction. Based on the observers, the friction can be well compensated. The stability of the system is derived by using Lyapunov method. The simulation results verify the effectiveness of the practical method. © 2022 IEEE.

关键词： Lyapunov methods

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