检索结果-内蒙古大学图书馆

Topography Modeling of Surface Grinding Based on Random Abrasives and Performance Evaluation

Chinese Journal of Mechanical engineering 2024年第5期37卷 126-148页

作者： Yanbin Zhang Peng Gong Lizhi Tang Xin Cui Dongzhou Jia Teng Gao Yusuf Suleiman Dambatta Changhe Li Key Lab of Industrial Fluid Energy Conservation and Pollution Control Qingdao University of TechnologyMinistry of EducationQingdao 266520China School of Materials Science and Engineering Xi’an University of TechnologyXi’an 710048China College of Mechanical Engineering and Automation Liaoning University of TechnologyJinzhou 121001China Mechanical Engineering Department Ahmadu Bello UniversityZaria 810106Nigeria

The surface morphology and roughness of a workpiece are crucial parameters in grinding *** prediction of these parameters is essential for maintaining the workpiece’s surface ***,the randomness of abrasive grain shapes and workpiece surface formation behaviors poses significant challenges,and accuracy in current physical mechanism-based predictive models is *** address this problem,by using the random plane method and accounting for the random morphology and distribution of abrasive grains,this paper proposes a novel method to model CBN grinding wheels and predict workpiece surface ***,a kinematic model of a single abrasive grain is developed to accurately capture the three-dimensional morphology of the grinding ***,by formulating an elastic deformation and formation model of the workpiece surface based on Hertz theory,the variation in grinding arc length at different grinding depths is ***,a predictive model for the surface morphology of the workpiece ground by a single abrasive grain is *** model integrates the normal distribution model of abrasive grain size and the spatial distribution model of abrasive grain positions,to elucidate how the circumferential and axial distribution of abrasive grains influences workpiece surface ***,by integrating the dynamic effective abrasive grain model,a predictive model for the surface morphology and roughness of the grinding wheel is *** examine the impact of changing the grit size of the grinding wheel and grinding depth on workpiece surface roughness,and to validate the accuracy of the model,experiments are *** indicate that the predicted three-dimensional morphology of the grinding wheel and workpiece surfaces closely matches the actual grinding wheel and ground workpiece surfaces,with surface roughness prediction deviations as small as 2.3%.

关键词： Surface topography prediction Grinding Grinding wheel model Random plane method

来源：评论

学校读者我要写书评

暂无评论

A Memristive Spiking Neural Network Circuit for Bio-inspired Navigation Based on Spatial Cognitive Mechanisms

引用

IEEE Transactions on Biomedical Circuits and Systems 2024年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation,a high-level and crucial function for organisms' survival in nature,enables autonomous exploration and navigation within the environment. However,most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation,capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application,the entire SNN is quantized and deployed on a real memristive hardware platform,achieving about a 21× reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

SightAid: empowering the visually impaired in the Kingdom of Saudi Arabia (KSA) with deep learning-based intelligent wearable vision system

引用

Neural Computing and Applications 2024年第19期36卷 11075-11095页

作者： Talaat, Fatma M. Farsi, Mohammed Badawy, Mahmoud Elhosseini, Mostafa Machine Learning Department Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt Faculty of Computer Science & amp Engineering New Mansoura University Gamasa35712 Egypt College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer Science and Information Department Applied College Taibah University Madinah46537 Saudi Arabia

In the Kingdom of Saudi Arabia, visual impairment poses significant challenges for approximately 17.5% of school-aged children, mainly due to refractive errors. These challenges extend to everyday navigation, environmental interaction, and overall life quality. Motivated by the desire to empower visually impaired individuals, who face navigational limitations, difficulties in object recognition, and inadequate assistance from traditional technologies, we propose SightAid. This innovative wearable vision system utilizes a deep learning-based framework, addressing the gaps left by current assistive solutions. Traditional methods, such as canes and GPS devices, often fail to meet the nuanced and dynamic needs of the visually impaired, especially in accurately identifying objects, understanding complex environments, and providing essential real-time feedback for independent navigation. SightAid comprises a seven-phase framework involving data collection, preprocessing, and training of a sophisticated deep neural network with multiple convolutional and fully connected layers. This system is integrated into smart glasses with augmented reality displays, enabling real-time object detection and recognition. Interaction with users is facilitated through audio or haptic feedback, informing them about the location and type of objects detected. A continuous learning mechanism, incorporating user feedback and new data, ensures the system's ongoing refinement and adaptability. For performance assessment, we utilized the MNIST dataset, and an Indoor Objects Detection dataset tailored for the visually impaired, featuring images of everyday objects crucial for safe indoor navigation. SightAid demonstrates remarkable performance with accuracy up to 0.9874, recall values between 0.98 and 0.99, F1-scores ranging from 0.98 to 0.99, and AUC-ROC values reaching as high as 0.9999. These metrics significantly surpass those of traditional methods, highlighting SightAid's potential to substan

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Trash Detection in Water Bodies Using Yolo With Explainable AI Insight 6

Trash Detection in Water Bodies Using Yolo With Explainable ...

引用

6th International Conference on Robotics and automation in Industry, ICRAI 2024

作者： Rasheed, Shafaq Mirza, Amal Saeed, Muhammad Saad Yousaf, Muhammad Haroon University of Engineering and Technology Department of Computer Engineering Taxila Pakistan National Center of Robotics and Automation Swarm Robotics Lab Taxila Pakistan

ISBN: (纸本)9798350355703

Waste disposal into water bodies is a serious concern for environmental engineers, often resulting in urban flooding, soil degradation in agricultural areas, and freshwater pollution. Additionally, trash accumulation in water bodies threatens ma-rine life by introducing contaminants through storm drains, rivers, and other channels. Furthermore, the unique character-istics of underwater environments, including high noise levels, low visibility, and color variation, pose challenges for trash detection. Thus, addressing this issue is crucial for environmental sustainability. The work focuses on both floating and submerged trash in water bodies. Typically, the detection of trash on water bodies is impacted by environmental variability, diverse appearance, and background clutter. These conditions also make usual object detection techniques less effective. Deep learning methods have shown promise in handling challenging visual tasks, therefore researchers have turned to them to get over these challenges. In this work, we focus on applying different versions of YOLO to the problem of water trash detection. To assess these models' performance, we use four different datasets: Trash Flow rate Dataset, DeepTrash, FloW, and TrashICRA. Each dataset represents various trash types under different conditions such as underwater trash and floating trash. Our study attempts to identify the best method suitable for the detection of aquatic waste. Our results highlight the effectiveness of YOLO variants in identifying the presence of trash in water ecosystems. By leveraging Grad-CAM we gain insights into the interpretability and transparency of deep learning models thus enabling Explainable AI. This approach will also contribute to the understanding and trustworthiness of artificial systems deployed for trash detection applications by providing a transparent view of decision making process of deep learning models. © 2024 IEEE.

关键词： Storm sewers

来源：评论

学校读者我要写书评

暂无评论

Anti-Windup for Internal Model control With Asymmetric Input Saturation

引用

IEEE control Systems Letters 2025年 9卷 126-131页

作者： Adegbege, Ambrose A. Owolabi, Opeyemi S. Ogunba, Kolawole S. Jubril, Abimbola M. The College of New Jersey Laboratory for Embedded Control and Optimization Department of Electrical and Computer Engineering EwingNJ08628 United States Obafemi Awolowo University Department of Electronic and Electrical Engineering Ife220282 Nigeria

In this letter, we introduce a novel anti-windup design approach for internal model control (IMC) that addresses the issue of asymmetric input saturation. To enhance closed-loop performance during periods of saturation, we utilize information about the asymmetrical limits of input saturation in the anti-windup design. This is achieved through a combination of static matrix scaling, a constant offset term, and a generalized sector condition that guarantees both global and regional stability of the closed loop. Our approach generalizes existing techniques for incorporating directionality compensation into anti-windup designs and can be interpreted as a search over a class of left-coprime factorization of the linear internal model controller. We demonstrate the effectiveness of this design approach on a well-known and widely used anti-windup example. © 2017 IEEE.

关键词： Matrix factorization

来源：评论

学校读者我要写书评

暂无评论

Dynamic Event-Triggered Consensus control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

引用

IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin Li Yue Long Tieshan Li Hongjing Liang C.L.Philip Chen the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China the School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： Constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

来源：评论

学校读者我要写书评

暂无评论

SR-Mamba: Data-Driven EV Charging Load-Altering Attack Detection and Localization Using Selective State based Model 6

SR-Mamba: Data-Driven EV Charging Load-Altering Attack Detec...

引用

6th International Conference on Electronic engineering and Informatics, EEI 2024

作者： Li, Yi Hanif, Umara College of Design and Engineering National University of Singapore Department of Electrical and Computer Engineering Singapore Central South University Department of Automation Changsha410083 China

ISBN: (纸本)9798350353594

Driven by the imperative to reduce emissions from transportation, Electric Vehicles (EVs) are proliferating rapidly. However, the widespread adoption of EV charging facilities poses a potential threat to the stability of the grid. Manipulating the demand for charging facilities can disrupt the supply/demand balance of the grid, potentially leading to blackouts. Moreover, current load alternation attack detection relies on static linearized grid modeling, which struggles to accurately represent the dynamic nature of the grid, thus making it difficult to detect such attacks effectively. In this paper, we propose a data-driven model using a State Space Model (Mamba-based structure) to capture temporal correlation among buses. We introduce spectral domain representation to enhance detection and utilize hidden grid representations for identifying load alternative attacks and their location. © 2024 IEEE.

关键词： State of charge

来源：评论

学校读者我要写书评

暂无评论

HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation

引用

Chinese Journal of Electronics 2023年第1期32卷 189-198页

作者： GUAN Qi SHENG Zihao XUE Shibei Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Real-time six degrees-of-freedom(6D)object pose estimation is essential for many real-world applications, such as robotic grasping and augmented reality. To achieve an accurate object pose estimation from RGB images in real-time, we propose an effective and lightweight model, namely high-resolution 6D pose estimation network(HRPose). We adopt the efficient and small HRNetV2-W18 as a feature extractor to reduce computational burdens while generating accurate 6D poses. With only 33% of the model size and lower computational costs, our HRPose achieves comparable performance compared with state-of-the-art models. Moreover, by transferring knowledge from a large model to our proposed HRPose through output and feature-similarity distillations, the performance of our HRPose is improved in effectiveness and efficiency. Numerical experiments on the widely-used benchmark LINEMOD demonstrate the superiority of our proposed HRPose against state-of-the-art methods.

关键词： Knowledge engineering Computational modeling Pose estimation Grasping Benchmark testing Feature extraction Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Vision-Based Quadrotor Rapid Landing control with An Uncooperative Platform: An Alternating Predictive Observer Approach

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Shao, Liren Guo, Zeyu Yang, Jun Li, Shihua School of Automation Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University China Department of Aeronautical and Automotive Engineering Loughborough University Loughborough U.K

The challenge of allowing a quadrotor to land quickly on an unknown moving platform using visual cues is addressed. A position-based visual servoing (PBVS) framework is designed that utilises the relative position data captured by the onboard camera to ensure a successful landing. The inherent limitation imposed by the camera's low sampling rate, which hampers the update and transfer rate of control commands, is mitigated by introducing an alternating predictive observer (APO). This observer inputs rapid actual or virtual position information into the control system. Actual relative positions are used for observer design when available from the camera, whereas virtual relative positions, predicted by the quadrotor model, are used when direct sampling is unattainable. This approach enables a process that alternates between prediction and observation, allowing for the design of a sampled-data controller that updates at a fast rate, commensurate with the APO. The robustness of the proposed PBVS-APO controller is exhibited, requiring no prior knowledge of the platform's dynamics. Validation through numerical simulations and experiments confirms the high control bandwidth and the rapid landing efficacy of the control strategy. IEEE

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Human arm motion capture system 9

Human arm motion capture system

引用

9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Olar, Marius Leonard Leba, Monica Ionica, Andreea University of Petrosani Department of System Control and Computer Engineering Petrosani Romania University of Petrosani Department of Management and Industrial Engineering Petrosani Romania

ISBN: (纸本)9798350377224

The implementation of robotics and human support technologies has opened up new possibilities for recovering the mobility impaired and increasing human productivity in the last few decades. Exoskeletons have been developed as a major component of this progress in order to capture any form of arm motion be it passive or active. Motion capture systems, employing different sensors like IMU sensors, EMG sensors, motion sensors, fiber optic sensors are used to capture arm movements. These sensors provide information on position, movement, muscle contraction, and movement intent of the arm. The use of multiple sensor types allows for redundancy and accurate outcomes. Potentiometer position sensor can be combined with other types of sensors to measure acceleration, orientation, force exerted and arm bendability. The combinations improve accuracy and adaptability for arm motion capture during rehabilitation. Various combinations of adapted sensors can be used for each joint of the hand depending on the peculiarities of application. Sensors enable precise and natural control over recovery devices or exoskeletons which is especially important in terms of rehabilitation process improvement. © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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：