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An end-to-end instance segmentation method based on improved ConvNeXt V2

International Journal of Wireless and Mobile Computing 2024年第4期26卷 384-392页

作者： Wang, Wenlu Sun, Ying Xu, Manman Bai, Dongxu Huang, Li Zou, Chunlong Chen, Baojia Tang, Dalai Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China College of Mechanical Engineering Hubei University of Automotive Technology Hubei Shiyan China Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance China Three Gorges University Hubei Yichang China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot China

In order to improve the efficiency of indoor mobile robots in locating and segmenting environmental instances, an instance segmentation method based on RTMDet is proposed. Firstly, the more powerful ConvNeXt V2 is used as the backbone network of the model, which improves the performance of the existing RTMDet model. Subsequently, NAS-FPN is used as a converged network to detect the network at any given time. Finally, AdamW is used as the model optimiser, which effectively solves the problem of excessive memory occupation when updating parameters and improves the performance of the model. The proposed method obtains the highest evaluation index in all cases. After training and testing on the Cityscapes data set, the recognition accuracy reaches 65.0%. © 2024 Inderscience Enterprises Ltd.

关键词： Statistical tests

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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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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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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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Research on workflow recognition for liver rupture repair surgery

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Mathematical Biosciences and Engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

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Flexible liquid metal electromagnetic shielding materials

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Science China(Technological Sciences) 2023年第10期66卷 2757-2774页

作者： BAI YunLong ZHANG Jie ZHANG MingKuan RAO Wei Key Laboratory of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100039China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China 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

The demand for flexible shielding has been rapidly growing in recent *** materials using solid metals,carbon materials,or MXenes as shielding units usually have difficulty in combining high shielding and flexibility(stretching and bending characteristics),and thus they gradually fail to meet the shielding needs of flexible ***,shielding materials with both flexibility and high conductivity are urgent to fill this ***-based room temperature liquid metal(LM)is an emerging functional material with a low melting point,low viscosity,low modulus,and easy ***,due to wettability and compatibility issues,it is difficult to apply bulk LMs directly in the field of electromagnetic shielding(EMS).The article reviews the fabrication methods,performance,and applications of LMs EMS materials from three perspectives:Macroscopic LMs,micro/nano-LMs,and LM-based *** gallium-based liquid EMS materials demonstrate the characteristics of high shielding performance with stretchability and a wide shielding *** this review,different types of gallium-based LM materials are described from macroscopic to microscopic,from liquid to semi-solid,from high density to low density,from room temperature to ultra-low temperature,and from monolayer structure to multilayer *** prospect of LM materials as amorphous high-performance EMS materials is demonstrated in various applications,such as mobile communication,astronomical observation,radar,and medical detection,showing tremendous potential in the EMS field.

关键词： liquid metal electromagnetic shielding flexibility

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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 ...

引用

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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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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Condition Monitoring of Railway Vehicle Suspension system Based on PCA-SVM Method

Condition Monitoring of Railway Vehicle Suspension System Ba...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Liu, Fulong Guo, Honglin Zhang, Xiaotao Chen, Wei Gu, Fengshou Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldHD1 3DH United Kingdom

ISBN: (纸本)9783031702341

The suspension system is critical to ensure the running safety and comfortability of railway vehicle. This paper employed conventional machine learning method of principal component analysis and support vector machine (PCA-SVM) to diagnose the damper fault, wheel surface fault, roller fault, damper fault coupled with wheel surface fault and damper fault coupled with wheel and roller surface faults. The effectiveness of this method was verified by data obtained from a 1/5th scaled roller rig. The results shown that the performance of PCA-SVM was acceptable for railway vehicle suspension system monitoring. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Rollers (machine components)

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Real Time Surgical Instrument Object Detection Using YOLOv7 1

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6th EAI International Conference on Robotics and Networks, EAI ROSENET 2022

作者： Zheng, Laiwang Liu, Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9783031338267

ISBN: (纸本)9783031338250

With the rapid development of minimally invasive surgery (MIS) in the medical field, surgical robot technology has developed rapidly. Human-machine combined assisted surgical technology has begun to bring good news to the majority of doctors and patients who need surgery. It has gradually become a common medical treatment. Minimally invasive surgery can overcome the shortcomings of traditional surgery. MIS has the advantages of less trauma, less impact on patients, faster recovery, less intraoperative blood loss, and so on. For surgical robots, surgical instruments are important execution components that have been widely concerned and studied in recent years. One of the core technologies of surgical robots is the detection of surgical equipment based on deep learning, which can effectively assist doctors to complete the surgery. Current surgical instrument detection methods need to be improved in real-time performance and accuracy. Therefore, this paper proposes a new real-time detection algorithm, which is based on the deep learning object detection system YOLOv7. The real dataset, which contained information on seven surgical instruments, was selected for training and validation. Experiments show that the method has good precision, recall rate, and mAP, which can be used to improve the ability of robot-assisted doctors to identify instruments during surgery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object recognition

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