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第41届中国控制会议

作者： Gang Li Xiaowei Jiang Le You Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work looks into the quantized impulsive consensus challenges of nonlinear leader-following multi-agent *** graph theory,principle of differential dynamics,logarithmic quantizer,matrix theory,and the Lyapunov function,among other things,are used to investigate the key discoveries on *** appropriate consensus protocols which contain quantized all agents' relative state information and quantized a part of agents' relative state *** the sake of reducing communication consumption and energy,we combine two control strategies and design two control protocols according to the characteristics of quantized control and impulsive *** a series of deductions,we find that under quantized impulsive control,multi-agent systems can achieve consensus as long as certain sufficient conditions are ***,the simulation example demonstrates the validity and correctness of this papers theoretical approach.

关键词： Multi-agent systems Leader-following Quantized impulsive consensus

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A calibration method of external parameters of 2D laser in rotary 3D scanning

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Optoelectronics Letters 2022年第12期18卷 730-736页

作者： WANG Shihao QIAO Zhifeng HUANG Jiahao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin300384China

Aiming at the problem of external parameter calibration in the combined rotating three-dimensional(3D) scanning process of laser radar and turntable, a fast 3D data scanning and accurate equipment calibration method suitable for industrial application scenarios is proposed. The coordinates of the center of the circle in the laser radar coordinate system are obtained by fitting the coordinates of the center of the circle with the scanning arc. Through the standard size and rotation angle of the target ball, the coordinates of the ball center in the turntable coordinate system are obtained. The rotation parameter R and the translation parameter T of the minimum value of the data set conversion error function in the two coordinate systems are calculated. The experimental results show that the error between the converted data and the actual data is within 0.1 mm, which meets the actual work requirements. This calibration method has the advantages of high accuracy and strong robustness.

关键词： coordinate rotation parameter

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Research on Lightweight Small Object Detection Method with Fusion Attention Mechanism

Research on Lightweight Small Object Detection Method with F...

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2023 China Automation Congress, CAC 2023

作者： Dai, Haowen Liu, Bingyou Wan, Guoyang Qi, Jingjing Wan, Luanfei School of Electrical Engineering Anhui Polytechnic University Wuhu China Anhui Polytechnic University The Key Lab. of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Wuhu China Anhui Dar Intelligent Control System Co. Ltd. Wuhu China Wuhu Institute of Technology Wuhu China

ISBN: (纸本)9798350303759

In the task of small object detection, due to the relatively small size of the objects, complex situations such as occlusion and overlap may arise in high-density scenes. These factors can significantly increase the issues of missed detections and false detections in object detection tasks. To address the aforementioned issues, this paper proposes a lightweight small object detection model, YOLOv5s-MGC. Firstly, we introduce an improved Mobilenetv3 network to replace the backbone network of YOLOv5s, aiming to improve the network's capability for effective feature extraction. Secondly, we incorporate the GSConv module into the feature fusion network to reduce model parameters and strengthen the network's ability in fusing feature information. Finally, we have integrated Convolutional Block Attention Module (CBAM) at the forefront of the detection heads, achieving the fusion of fine-grained features. We assessed our approach on the openly accessible dataset 'SHWD' and contrasted the results with the baseline YOLOv5s and various SOTA object detection models. Precisely, our method attains an accuracy of 91.1%, exceeding the baseline module by 1.6%. Furthermore, the module size is reduced to 1.97MB and it achieves a 52.4 FPS. In comparison to other prevailing algorithms, YOLOv5s-MGC enables efficient and accurate small object detection. © 2023 IEEE.

关键词： Object detection

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Multi-objective optimization of heat sink with multi-cross-ribbed-fins for a motor controller

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Journal of engineering and Applied Science 2022年第1期69卷 1-21页

作者： Zhang, Chao Chen, Liang Tong, Zhiting Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

A novel multi-cross-ribbed-fin layout was proposed to supersede the original smooth fin to fulfill the lightweight requirement of the air-cooled heat sink for the electrical vehicle motor controller. The thermal design with multi-cross-ribbed-fins was optimized using the multi-objective optimization method to minimize the chip’s temperature rise and the weight of the heat sink simultaneously. The design variables are the number of multi-cross-ribbed-fins ranging from 12 to 24, the number of cross ribs on either side varying from 1 to 4, and cross rib height in the region of 1.00–2.50mm. The standard k-Ε turbulence model was validated compared to the experimental data for the original heat sink with smooth fins. The Pareto front solution set was obtained by performing the mixed-level orthogonal design procedure with the numerical simulations, constructing the surrogated-based model with backpropagation neural net training, and implementing the genetic algorithm. The numerical results showed that the recommended optimal designs have the multi-cross-ribbed-fin number of 17–19, the number of cross ribs of 2–3, and a cross rib height of 2.13–2.50mm. The maximum decreases in the temperature rise and weight are 7.63% and 9.45%, respectively. For verifying the superiority of current optimal designs, one of the optimal designs of the heat sink, which yields comparative temperature rise of the chip but reduced weight, was selected to be experimentally tested and compared with the data for the original heat sink. © 2022, The Author(s).

关键词： Genetic algorithms

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An accurate pose measurement method of workpiece based on rapid extraction of local feature points

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Optoelectronics Letters 2022年第6期18卷 372-377页

作者： ZHANG Jiangtao QIAO Zhifeng WANG Shihao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin 300384China

Ceramic sanitary products with complex curved surfaces are generally fragile and difficult to *** the industrial robot is utilized to realize the automatic grinding of such products,the precise positioning of the product is required *** this paper,an accurate pose measurement system for complex curved surface parts is designed by point cloud registration *** order to improve the stability of the system,this paper combines the advantages of normal vector features and fast point feature histogram(FPFH)features,and proposes a point cloud registration algorithm based on the rapid extraction of local feature *** results verify that the improved algorithm has improved both efficiency and accuracy,and the system can effectively achieve accurate positioning of products.

关键词： robot system curved

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Vehicle object detection algorithm with SSD fused RFP structure

Vehicle object detection algorithm with SSD fused RFP struct...

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2022 Chinese Automation Congress, CAC 2022

作者： Cao, Mengxin Cheng, Fanyong Wei, Yangyang Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Anhui Polytechnic University Wuhu241000 China School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Anhui Key Laboratory of Electric Drive and Control Anhui Polytechnic University Wuhu241000 China

ISBN: (纸本)9781665465335

Object detection is extensively used in sectors as intelligent transportation and monitoring, however the current general single shot multibox detector (SSD) has the drawback of being unable to detect small objects. This study proposes an improved SSD to enhance the detection accuracy of small objects, dubbed RFP-SSD. It adopts Resnet50 as the backbone network and fuses an attention mechanism to boost shallow feature extraction in the feature extraction stage. Further, a recursive feature pyramid (RFP) structure is applied to facilitate multiscale fusion among feature maps. The experimental findings reveal that RFP-SSD outperforms the SSD in terms of detection. The mAP of RFP-SSD is 87.77%, which is a 6.77% improvement over the general SSD. © 2022 IEEE.

关键词： Feature extraction

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Fault Diagnosis for Photovoltaic Inverter based on Attention Recurrent Neural Network

Fault Diagnosis for Photovoltaic Inverter based on Attention...

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2021 International Conference on Power System Technology, POWERCON 2021

作者： Fang, Junren Cheng, Fanyong Meng, Xianmeng Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment School of Electrical Engineering Anhui Polytechnic University Anhui Key Laboratory of Electric Drive and Control School of Electrical Engineering Wuhu China

ISBN: (纸本)9781665407373

With the depletion of traditional fossil fuels and increasing environmental pollution, photovoltaic solar energy is widely used as a renewable energy source for electricity production. Photovoltaic inverter is one of the most important system balancing devices in photovoltaic power system. Insulated gate bipolar transistor (IGBT) is the core component of photovoltaic inverter, and its open circuit will affect the stable operation of photovoltaic power system, therefore, the fault diagnosis of IGBT is of great significance. Most existing methods cannot effectively pay attention to the context information of the collected signals to improve the accuracy of fault diagnosis. This paper proposes a new fault diagnosis method that uses the DC-side current of IGBT as the input signal and combines attention mechanism with recurrent neural network to diagnose and locate fault. A photovoltaic power simulation system was established, and simulation data was collected to train and verify the performance of the proposed method. Experimental results show that the method can perform reasoning based on context information and make up for the inability of recurrent neural network to focus on important features, thereby diagnostic performance can be improved. Compared with traditional data-driven methods, the proposed method not only has better diagnostic performance, but also has strong robustness in noisy environments. © 2021 IEEE.

关键词： Failure analysis

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Feature Pyramid Network Based on Skip Connect for Vehicle Prediction 2

Feature Pyramid Network Based on Skip Connect for Vehicle Pr...

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2nd International Conference on Robotics, Automation and intelligent Control, ICRAIC 2022

作者： Li, Peixin Liu, Jiaqi Yang, Lu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

The trajectory prediction of the target vehicle can improve the perception ability of autonomous driving vehicles in the open world environment and is an essential technology for realizing high-level fully automatic driving. The traditional vehicle trajectory prediction model based on image input is sensitive to the image style of the dataset and has weak generalization ability. The prediction model based on intermediate features can overcome the problem of different dataset styles. However, there are relatively few explorations on building models based on intermediate semantic features. Inspired by the feature pyramid in image processing, this paper proposes an FPSP (Feature Pyramid network based on Skip connect for vehicle Prediction) network. By adding the pyramid feature branch, the original network is improved. The initial coarse information is hierarchically introduced into corresponding abstract high-dimensional features. Experiments on the KITTI dataset prove that FPSP achieves considerable improvement with only a slight increase in time consumption. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Small-Target Infrastructure Detection with Spatial Tracking and Multi-Level Feature Extraction of Railway Track Scenes

Small-Target Infrastructure Detection with Spatial Tracking ...

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2024 International Conference on intelligent Communication, Sensing and Electromagnetics, ICSE 2024

作者： Du, Heng Cang, Huaiming Bai, Yiwen Wang, Xinyi Beijing Elephant Technology Co. Ltd Beijing China School of Transportation Science and Engineering Beihang University Beijing102206 China State Key Lab of Intelligent Transportation System Beijing100191 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350354935

In the field of railway transportation, with the continuous improvement of train running speed and the continuous increase of operating mileage, it becomes particularly important to ensure the safety and integrity of small-Target infrastructure along the railway train. Although many small-Target detection methods have been proposed, the research on small-Target infrastructure detection along rail trains is very rare. To solve this problem, this paper proposes a small-Target infrastructure detection network with spatial tracking and multi-level feature extraction based on Yolov8n. The experimental results show that ST-YOLO has a 3.6% mAP improvement on the OSDaR23 dataset compared to the baseline Yolov8n, and shows significant advantages over other state-of-The-Art methods. © 2024 IEEE.

关键词： Railroads

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Teaching Innovation and Practice of Mind Mapping Applied to engineering Drawing Course 12

Teaching Innovation and Practice of Mind Mapping Applied to ...

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12th IEEE International Conference on Educational and Information Technology, ICEIT 2023

作者： Xue, Yahong Mu, Haozhi Xue, Lijun Wang, Xiaofei Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9781665475518

engineering drawing is a compulsory technical foundation course for mechanical majors. Its main task is to cultivate students' ability to draw and read engineering drawings. The content of this course is complicated and abstract and not easy to understand, which makes it difficult for students to learn. Mind mapping is a visual thinking tool to systematize and organize abstract and complicated knowledge. Taking the application of mind mapping to various teaching processes of engineering drawing course, such as the construction of framework, the sorting out of fragmented knowledge, the solution of drawing geometry and sectional view, and the group project for important and difficult content as examples, we illustrate the importance of mind map in cultivating students' knowledge generalization ability, independent learning ability, enhancing students' logical thinking, creative thinking, divergent thinking, and stimulating students' interest in learning. © 2023 IEEE.

关键词： Students

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