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2018 4th International Conference on Mechanical Engineering and Automation Science, ICMEAS 2018

作者： Hu, Yahui Li, Xiangjun Chen, Chuncheng Su, Lili Zheng, Qingchun Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin University of Technology 391 Binshui West Road Tianjin Xiqing District300384 China

The micro-texture on the tool surface is an effective way to improve the quality of the drilling. While high-performance micro-texture plays an important role in improving the quality of working surface and prolonging the life of tool. In this study, a three-dimensional finite element model was established to study the relationship between drilling thrust, torque and microstructure parameters (micro-pit depth, micro-pit diameter and micro-pit spacing) during drilling of cortical bone. The model was validated by cortical bone drilling using a micro-structured tool. On basis of this, the thrust and torque prediction models of the micro-texture parameters were obtained. The results indicate that the thrust and torque increased with the increase of micro-pit diameter;while the increase of the micro-pit spacing caused the thrust and torque to decrease. When the depth of the micro-pit increased, the thrust and torque decreased first and then increased, and we found that the effect of micro-pit spacing and micro-pit depth on force and torque is insignificant. © Published under licence by IOP Publishing Ltd.

关键词： Torque

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Visual servoing of magnetic swimming robot based on mean shift and fast template matching algorithm

Visual servoing of magnetic swimming robot based on mean shi...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Xiang, Hongbiao Zhang, Tilei Li, Mengwei Wang, Shoujun Yang, Xiuping Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781728163215

The actuation and control of mini-scale swimming robots have exhibit promising potential in limited and constrained environments, such as biomedical, micro-assembly and microfluidic applications. However, closed-loop control is still a challenging for the precision and repeatability in those applications. In this paper, a new type of soft-micro swimming robot based on magnetoelastic composite material is designed, and the swimmer can move freely on the water surface controlled by a rotating magnetic field with visual servoing. The visual feedback control strategy is proposed based on Mean Shift Algorithm and Fast Template Matching. The algorithm includes three parts: prediction, template matching, target positioning and template updating. To understand the characteristics of the swimmer, the relationship between swimming speed and magnetic field strength and frequency is verified by the algorithm in experiments. Furthermore, the proposed path following method with visual servoing applied in this control system. The experimental results show that the algorithm runs fast, has high accuracy and good real-time performance, and can provide great potential in mini-scale robot applications. © 2019 IEEE.

关键词： Visual servoing

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Swimming characteristics of soft robot with magnetoelastic material

Swimming characteristics of soft robot with magnetoelastic m...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Xiang, Hongbiao Li, Mengwei Zhang, Tilei Wang, Shoujun Yang, Xiuping Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781728163215

Cable-less micro-robots have exhibit great capabilities for remote applications in small and constrained environments, especially in biotechnology and healthcare. This paper presents a swimmer propelled by its undulatory deformation using magnetoelastic composite material. The robot can move freely on water surface driven through a function of magnetic field, such as forward, backward and steering with different velocity. The magnetic field is generated by 3D Helmholtz coils, and the locomotion of the micro swimming robot is controlled by different applied magnetic field. To understand the characteristics of the swimmer, the force balance equation is established, and the morphologies of swimmer with different magnetic field are analyzed and described through finite element analysis method. Furthermore, we discuss and analyze relationship between the parameters of magnetic field and the speed of the swimmer. The experimental results verified the speed model of the swimming robot, which is influenced by the frequency and strength of magnetic field. © 2019 IEEE.

关键词： Magnetic fields

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Mechanical Analysis and Performance Optimization for the Lunar Rover’s Vane-Telescopic Walking Wheel

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Engineering 2020年第8期6卷 936-943页

作者： Lu Yang Bowen Cai Ronghui Zhang Kening Li Zixian Zhang Jiehao Lei Baichao Chen Rongben Wang 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 Guangdong Key Laboratory of Intelligent Transportation System School of Intelligent Systems EngineeringSun Yat-sen UniversityGuangzhou 510275China College of Transportation Jilin UniversityChangchun 130025China Department of Mechanical Science and Engineering Tokyo Institute of TechnologyTokyo 152-8550Japan Armour College of Engineering Illinois Institute of TechnologyChicagoIL 60616USA China Academy of Space Technology Beijing 100029China

It is well-known that optimizing the wheel system of lunar rovers is ***,this is a difficult task due to the complex terrain of the moon and limited resources onboard lunar *** this study,an experimental prototype was set up to analyze the existing mechanical design of a lunar rover and improve its ***,a new vane-telescopic walking wheel was proposed for the lunar rover with a positive and negative quadrangle suspension,considering the complex terrain of the ***,the performance was optimized under the limitations of preserving the slope passage and minimizing power *** was achieved via analysis of the wheel force during ***,the effectiveness of the proposed method was demonstrated by several simulation *** newly designed wheel can protrude on demand and reduce energy consumption;it can be used as a reference for lunar rover development engineering in China.

关键词： intelligent vehicle Vane-telescopic walking wheel Performance optimization Vane spring Lunar rover

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SI-YOLO: A Deep Learning Algorithm Suitable for Surgical Instrument Detection

SSRN

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SSRN 2022年

作者： Liu, Zhenzhong Zhou, Yifan Sun, Qiyuan Wang, Yan Polat, Kemal Nour, Majid Alenezi, Fayadh Alhudhaif, Adi Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China Department of Electrical and Electronics Engineering Bolu Abant Izzet Baysal University Bolu14280 Turkey Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Department of Electrical Engineering College of Engineering Jouf University 72238 Saudi Arabia Department of Computer Science College of Computer Engineering and Sciences in Al-kharj Prince Sattam bin Abdulaziz University P.O. Box 151 Al-Kharj 11942 Saudi Arabia

Surgical instrument detection and tracking is one of the core technologies of surgical robots, which can assist clinicians in completing operations. However, existing methods need further improvement in terms of real-time performance and accuracy. We propose a deep learning algorithm, SI-YOLO, for detection of surgical instruments. SimAM attention mechanism is used to improve the feature extraction ability of YOLOv5. Replacing PANet with BiFPN in the neck network improves the feature fusion strategy. The α-IoU loss function is used to improve the regression accuracy of detection boxes. The mAP and FPS of the SI-YOLO reach 99.2% and 120 frames/sec, respectively. Aiming at the problem of ID transformation in the disappearance and occlusion of surgical instruments, the Inception-ResNet-v2 structure is added on the basis of the appearance feature extraction network Cosine of the DeepSort tracking algorithm. Combining SI-YOLO with the improved DeepSort implements the Tracking by Detection (TBD) algorithm. In the case of device disappearance or occlusion, the frequency of ID transitions is reduced by approximately 30%. Finally, we built a simulated surgery experimental platform, established our own data set, and realized the preliminary application of the proposed algorithm. © 2022, The Authors. All rights reserved.

关键词： Object detection

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Tool Path Generation Method for Three-dimensional Vibration-assisted Machining 16

Tool Path Generation Method for Three-dimensional Vibration-...

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16th IEEE International Conference on Mechatronics and Automation, ICMA 2019

作者： Wang, Guilian Lv, Bingrui Liu, Bin Mu, Haozhi 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 Tianjin Laboratory of Control Theory and Applications in Complicated System Tianjin300384 China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781728116983

In this paper, a new tool path generation method is proposed for the 3D (three-dimensional) vibration-assisted 6-DOF (six degree of freedom) machine tool machining system. The tool feed path is generated by the tangent point method and the coordinate transformation theory. It is worth noting that this method needle is only used when the tool and workpiece surface topography can be mathematically described. Finally, a numeric simulation method is used to simulate the tool path which is required when machining workpiece surfaces with different topography tools. The results show that the tool path generation method is widely applicable to tools and workpieces of various shapes, and it is of great significance to reveal the influences of different tool shapes on the tool path. © 2019 IEEE.

关键词： Machine tools

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Research on Feedforward control Based on Robot Dynamics Parameters Identification

Research on Feedforward Control Based on Robot Dynamics Para...

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IEEE International Conference on Mechatronics and Automation

作者： Xingmao Shao Shoujun Wang Liusong Yang Nan Liu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China CITIC Heavy Industries Company Ltd. Luoyang China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Accurate robot dynamics model can effectively improve the motion control performance of robot, and accurate dynamics parameters are the basis for establishing dynamics model. This paper discusses the parameter identification method of the tandem manipulator and the feedforward control scheme based on dynamics. First, we deduced the basic parameters of the first three joints of the UR5 manipulator, and identified the parameters through experimental sampling and calculation. Secondly, we established a feedforward control mechanism based on dynamics using the Simulink platform, and simulated and verified the feedforward control of the robot three-axis system. The experimental results show that the feedforward control scheme based on robot dynamics can effectively improve the error convergence performance, which proves the effectiveness of the method.

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Visual Servoing of Magnetic Swimming Robot Based on Mean Shift and Fast Template Matching Algorithm

Visual Servoing of Magnetic Swimming Robot Based on Mean Shi...

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IEEE International Conference on Robotics and Biomimetics

作者： Hongbiao Xiang Tilei Zhang Mengwei Li Shoujun Wang Xiuping Yang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China

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Robust Tensor Principal Component Analysis Based on F-norm

Robust Tensor Principal Component Analysis Based on F-norm

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IEEE International Conference on Mechatronics and Automation

作者： Weimin Ge Jinxiang Li Xiaofeng Wang National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Tensor principal component analysis (TPCA) has been widely used to extract appearance features of colour objects or colour scenes presented in tensor form. Using L 1 -norm as the distance metric, the existing TPCA-L 1 with its greedy (TPCA-L 1 -G) and non-greedy (TPCA-L 1 -NG) algorithms were proposed to reduce the sensitivity to outliers. The two algorithms, however, only derived TPCA solution in a form of two-dimensional matrix without actually extending them to the tensor subspaces and without performing experimental verification for tensor data. Simultaneously, the spatial correlations between pixels of the raw tensor data cannot be effectively preserved. To solve the problems, a robust tensor principal component analysis algorithm based on F-norm distance metric is proposed in this paper, which not only preserves the spatial structure of the raw data, but also reduces the sensitivity to outliers in tensor data. Experiments on reconstruction error and classification rate show that the proposed algorithm is effective and superior to other tensor algorithms in performances.

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An Incremental Feature Extraction Method for Weld Surface Defect Recognition

An Incremental Feature Extraction Method for Weld Surface De...

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IEEE International Conference on Mechatronics and Automation

作者： Jun Liu Keguang Ren Xiaofeng Wang Weimin Ge National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Binshui Xidao 391 Xiqing District Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

To meet the requirements of online feature extraction for weld defect recognition, an Incremental 2DPCA algorithm (I2DPCA) without estimating the covariance matrix of weld surface images is firstly proposed. A set of weld features with multiple orthogonal principal components can be obtained by a recursive estimation method, instead of the eigenvalue decomposition method or the singular value decomposition method. The computational complexity will be greatly reduced and the online feature extraction speed will be improved. To extract more structure features and reduce the dimension of weld images, an Incremental row-column Bidirectional PCA (IBDPCA) algorithm is presented based on I2DPCA, which preserves the weld features in the horizontal and vertical directions of weld images, and realizes the incremental feature extraction and data dimensionality reduction in the row and column directions. Finally, a series of comparative experiments are performed on the collected weld defect dataset. The results show that the proposed algorithm is superior to other PCA algorithms in convergence rate, classification rate, and complexity. The convergence rate is more than 99%, the classification rate can reach 96%, which can meet the online feature extraction requirements for weld defect recognition.

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