检索结果-内蒙古大学图书馆

3rd International Conference on Electronic Information engineering and Data Processing, EIEDP 2024

作者： Yang, Jingtao Sun, Lihui Wang, Gang College of Information and Control Engineering Jilin University of Chemical Technology Jilin China College of Mechanical Engineering Jilin Polytechnic of Communications Jilin China School of Mechanical and Control Engineering Baicheng Normal College Baicheng China

ISBN: (纸本)9781510680531

This paper addresses the challenges of target occlusion and the difficulty in detecting small underwater organisms due to the behavioral characteristics of underwater fauna. An improved YOLOv5 algorithm for underwater target detection is proposed to enhance performance in underwater environments. Firstly, YOLOv5 incorporates the Coordinate Attention module to further enhance feature extraction. Secondly, a BiFPN (Bidirectional Feature Pyramid Network) is employed to better integrate features of different scales. Finally, a DyHead (Detection Head based on attention mechanism) is added for target detection. Experimental results on the URPC2020 dataset show that the improved YOLOv5 network achieves a 1.7% increase in mAP@0.5 and a 1.1% increase in mAP@0.5-0.95. The parameter count of the improved YOLOv5 network only increases by 5.5%, with a computational overhead of 5.6%. Therefore, the proposed approach demonstrates superior performance in underwater target detection tasks. © 2024 SPIE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Position Regulation of Industrial Robots via Bounded Integral Terminal Sliding Mode control Algorithm

引用

IEEE Transactions on Industrial Electronics 2024年第7期71卷 7403-7412页

作者： Cong, Yongzheng Du, Haibo Zhu, Wenwu Chen, Chih-Chiang Hefei University of Technology School of Electrical Engineering and Automation Hefei230009 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

For the position regulation problem of six degrees of freedom (6-DOF) industrial robots, a novel bounded finite-time position regulate algorithm is developed and employed to improve the dynamic performance of the industrial robots. First, based on the model feature, a bounded finite-time position regulate law is proposed to overcome input saturation constraints for the considered systems. Rigorous analysis guarantees the finite-time stability of the closed-loop system in the absence of disturbance. Then, to improve the disturbance rejection property of the robot systems in the presence of disturbance, an improved bounded finite-time control law based on the integral terminal sliding mode is constructed. Finally, simulations and experimental results are provided to show the effectiveness of the proposed bounded control law. © 1982-2012 IEEE.

关键词： Asymptotic stability

来源：评论

学校读者我要写书评

暂无评论

Current Status and Future Perspectives of the Active Knee Joint Rehabilitation Device

引用

Recent Patents on engineering 2022年第4期16卷 11-29页

作者： Jiang, Jingang Gao, Ziwen Song, Shichang Yu, Xiaoyang Zeng, Yang Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Harbin150080 China School of International Studies Harbin Institute of Technology Harbin150001 China School of Measurement-Control Tech and Communications Engineering Harbin University of Science and Technology Harbin150080 China

Background: Today, living standards and medical technology are improving, and the aging global population is increasing. However, more and more older adults are suffering from knee diseases. This will seriously affect patients’ daily life and their mental state. In many studies, repeti-tive physical exercises and motor activities in real-world environments have been shown to help im-prove knee muscle strength and restore damaged nerves. Therefore, physical knee therapy is very nec-essary. The use of rehabilitation training devices for movement therapy has shown great potential. Objective: This study aimed at exploring the structural features, functions, and development status of the knee rehabilitation training device. Methods: This review explores the structure and function of various current knee rehabilitation devices based on structural and kinematic properties of the knee joint in relation to requirements of physical knee rehabilitation. This paper aims to present a systematic guideline and outline a refer-ence for future designers of rehabilitation devices. Results: By analyzing the structure and movement of the knee joint and combining the strategies of physical knee rehabilitation, movement requirements during knee rehabilitation training are con-cluded. According to the structure, drive form, transmission mode, and rehabilitation environment of knee rehabilitation devices, the devices are classified and compared;some typical features are summarized;some current problems are analyzed, and the future trends and development directions of rehabilitation devices are discussed. Conclusion: Current rehabilitation equipment has a variety of structures and functions, but a good balance between weight and volume is hardly maintained. The protection of the body needs to be further improved. Many knee rehabilitation devices are only concepts, not physical objects, and lack clinical trial data. Power sources and drives are large and heavy, which can compress the knee jo

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

TRAVERSABILITY ESTIMATION BASED ON VEHICLE CHARACTERISTICS AND ENVIRONMENTAL GEOMETRY 10

TRAVERSABILITY ESTIMATION BASED ON VEHICLE CHARACTERISTICS A...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： He, Naixiang Su, Qinghua Wang, Liyong Song, Yue Wang, Haodong Zhang, Haoyuan Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China School of Mechanical Engineering and Vehicles Beijing Institute of Technology Beijing China

ISBN: (纸本)9781837242672

In unstructured environments, ensuring the safe operation of autonomous vehicles necessitates precise perception and thorough analysis of the surrounding terrain. Existing traversability analysis methods frequently rely on data from a single sensor and fail to integrate vehicle characteristics with environmental geometric features. This limitation results in weak environmental perception and poor performance in traversability analysis. To address these challenges, this paper proposes an innovative approach. By fusing data from multiple LiDAR sensors, the method constructs a locally dense traversability map, significantly enhancing the completeness and reliability of terrain ***, this approach combines vehicle characteristics with multiple environmental geometric factors to generate a traversability layer. This integration leads to a more holistic understanding of the terrain, improving the vehicle's ability to navigate complex environments safely. The proposed method demonstrates outstanding performance in traversability estimation, enabling a more accurate evaluation of traversability. This, in turn, provides a solid guarantee for the safe driving of autonomous vehicles in various challenging *** system underwent rigorous testing in unstructured environments to validate its effectiveness. The test results indicate that the elevation maps and traversability layer generated by this method exhibit significant improvements in both detail and accuracy. These advancements ensure that autonomous vehicles can better perceive and navigate their surroundings, ultimately contributing to safer and more reliable autonomous driving in unstructured and complex terrains. © The Institution of engineering & technology 2024.

关键词： Tracked vehicles

来源：评论

学校读者我要写书评

暂无评论

Remaining Life Prediction Method of Rolling Bearing Based on TD3 Optimization Model Updating Strategy 16

Remaining Life Prediction Method of Rolling Bearing Based on...

引用

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

作者： Wang, Yujing Jiao, Guangpeng Kang, Shouqiang Xie, Jinbao Sun, Yulin School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China School of Physics and Electronic Engineering Hainan Normal University Haikou China

ISBN: (纸本)9798350327144

To address the problems of model degradation and low prediction accuracy in the of update procedure the rolling bearing life prediction model, the updating strategy of twin delayed deep deterministic policy gradient(TD3) is suggested to optimize the prediction model, and it applied to rolling bearing remaining useful life prediction. Continuous wavelet transform is used to build a dataset by converting the rolling bearing vibration data into two-dimensional time-frequency spectrum diagram. Deep reinforcement learning is introduced to design the elements of state, action, reward value and loss function, which are employed to training of the prediction model, this model is composed convolutional neural network (CNN) and bidirectional long short-term memory. The delayed update and soft update techniques of the TD3 algorithm are used to reduce the update frequency of the CNN feature network. A new loss function is proposed to establish a new model updating strategy for solving the prediction model degradation problem. The experimental study using the PHM2012 dataset and the finding indicate that, in comparison to the compared methodologies, the suggested prediction method with model optimization strategy can reduce the root mean square error and mean square error by more than 23.8% and 20.8% respectively, reducing the prediction error by at least 18.6% and improve the scores by more than 0.213. © 2023 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Anchor-Free Detector Using Cross-Dimensional Interactive Feature Balance for SAR Ship Detection 5

A Lightweight Anchor-Free Detector Using Cross-Dimensional I...

引用

5th International Conference on Video, Signal and Image Processing, VSIP 2023

作者： Shen, Jiaming Bai, Lin Wang, Haijuan Ji, Bo Cheng, Wenming Zhang, Guocai School Of Electronics And Control Engineering Changan University Xian China Zhejiang Aerospace Runbo Measurement And Control Technology Co. Ltd Hangzhou China

ISBN: (纸本)9798400709272

In recent years, the deep convolutional neural network (CNN) model has rapidly developed, and it is widely used in SAR remote sensing target detection. Many methods utilize preset anchor boxes for target classification and boundary box coordinate regression. However, these methods encounter challenges when deployed to edge devices. Firstly, in SAR images, ships are sparsely and unevenly distributed, rendering most anchor boxes redundant. Secondly, the target detection model relying on anchor boxes demands extensive computation during anchor box generation, typically running on hardware-rich environments. Nevertheless, edge devices lack the necessary hardware environment to meet the deployment requirements of the CNN model. To address these issues, this paper proposes a lightweight anchor-free detector called Cross-Dimensional Interactive Feature Balance (CDIFB-Net). We adopt a key point strategy to predict the bounding box, eliminating the reliance on anchors. CDIFB-Net employs a partial convolution (PConv) based model as a lightweight feature extraction network to tackle the model's lightweight problem. Additionally, considering the characteristics of large target scale differences and unbalanced target distribution in SAR ship images, and to reduce the precision decline problem caused by lightweight, this paper introduces a cross-dimensional interactive feature balance pyramid (CDI-FBP), which balances semantic information of different levels through feature pyramid aggregation and averaging. The cross-dimensional interaction module (CDIM) establishes the relationship between the ship target and the background. Experiments conducted on the SAR Ship dataset (SSDD) and High-resolution SAR Image dataset (HRSID), along with inference experiments in different hardware environments, validate the effectiveness of the network for SAR ship detection. The experimental results demonstrate that the proposed CDIFB-Net maintains fast reasoning, low delay, and excellent detectio

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

FCA-Net: A Fast Inference and Channel Attention Based Network for Hyperspectral Image Classification 16

FCA-Net: A Fast Inference and Channel Attention Based Networ...

引用

2023 16th International Conference on Computer and Electrical engineering, ICCEE 2023

作者： Ji, Bo Bai, Lin Wang, Haijuan Shen, Jiaming Chen, Guoqiang Jin, Ying School of Electronics and Control Engineering Changan University Xian China Zhejiang Aerospace Runbo Measurement and Control Technology Co. Ltd Hangzhou China

Hyperspectral imaging (HSI) is a competitive remote sensing technique used in various fields such as land cover mapping and environmental monitoring. Each hyperspectral imaging (HSI) scene is comprised of numerous narrow and contiguous spectral bands, rendering the extraction of information from HSI data cubes a challenging and computationally intricate endeavor. Convolutional neural networks (CNNs) have garnered widespread adoption for HSI classification due to their impressive performance. Nevertheless, the substantial number of internal parameters within CNNs engenders high computational and memory requirements, resulting in inefficient floating-point operations per second (FLOPS), particularly when faced with frequent memory access and an abundance of operators. To address this issue, this paper proposes a novel framework named Fast Inference and Channel Attention-based Network (FCA-Net). Specifically, the framework introduces a lightweight convolutional layer and a channel attention mechanism (CAM) to enhance the extraction of spatial and spectral information within the network. The proposed FCA-Net significantly reduces computational costs while maintaining reliable classification results and can perform fast processing on GPU or even CPU, making it a promising option for embedded systems. Furthermore, the optimized global computational cost, including reduced demand for compute power and memory, results in lower energy consumption, which has previously been proven advantageous for improving deep model performance. © Published under licence by IOP Publishing Ltd.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

TRGR: Transmissive RIS-aided Gait Recognition Through Walls

TRGR: Transmissive RIS-aided Gait Recognition Through Walls

引用

2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Huang, Yunlong Liu, Junshuo Zhang, Jianan Mi, Tiebin Shi, Xin Qiu, Robert Caiming Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan China North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9798350351255

Gait recognition with radio frequency (RF) signals enables many potential applications requiring accurate identification. However, current systems require individuals to be within a line-of-sight (LOS) environment and struggle with low signal-to-noise ratio (SNR) when signals traverse concrete and thick walls. To address these challenges, we present TRGR, a novel transmissive reconfigurable intelligent surface (RIS)-aided gait recognition system. TRGR can recognize human identities through walls using only the magnitude measurements of channel state information (CSI) from a pair of transceivers. Specifically, by leveraging transmissive RIS alongside a configuration alternating optimization algorithm, TRGR enhances wall penetration and signal quality, enabling accurate gait recognition. Furthermore, a residual convolution network (RCNN) is proposed as the backbone network to learn robust human information. Experimental results confirm the efficacy of transmissive RIS, highlighting the significant potential of transmissive RIS in enhancing RF-based gait recognition systems. Extensive experiment results show that TRGR achieves an average accuracy of 97.88% in identifying persons when signals traverse concrete walls, demonstrating the effectiveness and robustness of TRGR. © 2024 IEEE.

关键词： Channel state information

来源：评论

学校读者我要写书评

暂无评论

Image-Based Fast Finite-Time Target Tracking control of Onboard Inertially Stabilized Camera Platform

引用

IEEE Transactions on Industrial Electronics 2024年第12期71卷 16409-16418页

作者： Sun, Xunhong Zhu, Wenwu Du, Haibo Chen, Weile Chen, Chih-Chiang Hefei University of Technology School of Electrical Engineering and Automation Hefei230009 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University School of Automation Nanjing210096 China National Cheng Kung University Department of Systems and Naval Mechatronic Engineering Tainan70101 Taiwan

In this article, we investigate the problem of fast finite-time target tracking control of the inertially stabilized platform (ISP) with a camera that mounted on a mobile robot. At first, the kinematics of the onboard ISP target tracking system is established by the geographic coordinate and pinhole camera model, which includes the state-dependent uncertainties and external disturbances. Then, based on the image information captured by camera, a continuous image-based fast finite-time control algorithm is designed for target tracking. Rigorous analysis proves that the target can be tracked at the center of camera's view in finite time in the absence of disturbances. In the presence of disturbances, the tracking error can converge to a region around the origin in finite time. Simulation and experimental comparisons are presented to confirm the efficiency of the proposed method. © 1982-2012 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Equivalent Ratio of Frequency Regulation Resources Based on Derivation of Open-Loop control Frequency Deviation 16

Equivalent Ratio of Frequency Regulation Resources Based on ...

引用

16th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2024

作者： Ning, Jia Wang, Hanxiang Wang, Ying School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Southeast University Key Laboratory of Measurement and Control of Cse Ministry of Education Nanjing China

ISBN: (纸本)9798350386127

The conventional approach to frequency regulation predominantly relies on thermal and hydroelectric power generation units. As a growing variety of frequency regulation resources become accessible to power systems, there is significant variation in their performance characteristics, it is important to quantify their capabilities in the frequency service markets. This study introduces a technique to calculate the equivalent ratio of these resources by analyzing their primary response to frequency deviations derived from open-loop control. Based on the rotor motion equation of the generator, this paper constructs a load frequency control model incorporating two distinct regulation resources, linearize their outputs, and integrate them into the model. Through differential equations, this paper derives analytical expressions for the frequency deviation curve, enabling the determination of key frequency metrics. The equivalent ratio is then calculated by comparing the output power of resources with similar performance indicators. Finally, the paper investigates the impact of diverse parameters on the computation of the equivalent ratio employing simulation-based experimental analysis. © 2024 IEEE.

关键词： Open loop control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：