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IEEE International Conference on Mechatronics and Automation

作者： Bibo Jiang Jianyuan Zhang Xueshuai Yang Zhiwei Li CNOOC Ener Tech Equipment Technology Co. Ltd Tianjin China Tianjin Key Laboratory for Control Theory and Applications in Complicated System Tianjin University of Technology Tianjin China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

Binocular vision is an important technique in 3D (three-dimensional) reconstruction. Two images captured by binocular camera are used to reconstruct 3D information according to the geometric relationship and optical imaging parameters of binocular camera. In binocular vision system, the focal length, base distance and measuring object distance are mutually restricted, and the measurement accuracy is different under different parameter configurations. In this paper, the parameter selection and measurement performance of binocular vision system are studied. A laser scanning binocular vision measuring device is constructed, and the binocular matching speed is accelerated by actively projecting laser line to the measured object. By extracting the center bright line of the laser bright line fringe in the image for stereo matching, parallax is obtained to calculate the distance of the object. By adjusting the system structure parameters, the influence of the system structure parameters on the ranging performance is analyzed and studied. In this paper, combining experimental analysis with theoretical analysis, the parameter setting conditions of binocular vision system high precision measurement are proposed. It helps to improve the performance of the ranging system by rationally designing the parameters of the binocular ranging system.

关键词： Performance evaluation Three-dimensional displays Accuracy Machine vision Measurement by laser beam Length measurement Cameras

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Modal Fusion Sign Language Recognition Based on Swin Transformer Architecture

Modal Fusion Sign Language Recognition Based on Swin Transfo...

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International Conference on Image, Vision and Computing (ICIVC)

作者： Yujie Gao Yadong Li Bin Liu Yifan Tian Minfeng Zhu Jian Luo School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Control Theory &Applications in Complicated System Tianjin University of Technology Tianjin China

Sign language plays an important role in information transmission and emotional communication between the hearing-impaired and the outside world. It is expressed through a rapid and complex combination of gestures, body postures and facial expressions. In this paper, Google's MediaPipe framework is used to extract and process key point information of hands. Depth features are used to supplement the RBG diagram. A framework of skeleton sensing multi-modal recognition suitable for complex scenes is proposed. This can be used to deal with the problem of sign language recognition of multi-modal information in different scenes. However, most of the existing sign language recognition methods are traditional convolutional networks and LSTM. Although they have excellent achievements in image recognition and video recognition, their application in sign language recognition does not conform to the characteristics of sign language. In this paper, a Swin Transformer model is used to process both depth information and RGB information. Finally, statistical data fusion method was used to fuse the depth prediction results with RGB prediction results. Experimental analysis shows that this method performs well in sign language recognition in complex scenes compared with existing methods.

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In-situ Monitoring of Maximum and Average Chip Junction Temperature within Multichip IGBT Power Modules Using Kelvin Emitter Voltage

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Yang, Jianxiong Ran, Li Che, Yanbo Du, Mingxing Tianjin University of Technology Tianjin Key Laboratory of Control Theory and Applications in Complicated System Tianjin300384 China Chongqing University State Key Laboratory of Power Transmission Equipment and System Security and New Technology School of Electrical Engineering Chongqing400044 China University of Warwick School of Engineering CoventryCV4 7AL United Kingdom Tianjin University Key Laboratory of Smart Grid of Ministry of Education School of Electrical and Information Engineering Tianjin300072 China

Parallel configurations of power chips within a multichip IGBT power module (M-IGBT-PM) are employed to meet the required current and power ratings. When the internal chips of an M-IGBT-PM experience uneven temperature distributions and package aging, it becomes challenging to determine the maximum and average temperatures of the chips within the module. This paper investigates the relationship between four transient thermal-sensitive electrical parameters (T-TSEPs) derived from the Kelvin emitter voltage and the chip junction temperature, while establishing relevant mathematical models. It compares the sensitivity and linearity of these four T-TSEPs, and also assesses the influence of external gate resistance, bus voltage, and load current on each of them. A key innovation in this paper is the proposal of a method for monitoring the maximum and average temperatures across the chips within the M-IGBT-PM, which is not influenced by the load current. The experimental results suggest that the temperature derived from the quasi-turn-on delay time is a good approximation of the maximum chip temperature, whereas the temperatures predicted by the other T-TSEPs are nearer to the average temperature. © 2025 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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Study on 6D Pose Estimation system of Occlusion Targets for the Spherical Amphibious Robot based on Neural Network 20

Study on 6D Pose Estimation System of Occlusion Targets for ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Du, Chaofeng Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory BinshuiXidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China School of Life Science Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

The amphibious robot needs to accurately estimate the 6D pose of the target in tasks such as target tracking, docking with the recovery module, and target grasping. The current research on target 6D pose estimation is mainly applied to unoccluded targets, but when the target is occluded, the target's pose cannot be accurately identified. Compared with other algorithms, the PVNet algorithm shows better robustness when target is occluded, but the accuracy is still low. To improve the accuracy of the PVNet algorithm, this paper adds the confidence score prediction of the prediction vector at the last layer of the PVNet network, and designs a vector confidence score loss function to train the network. Before generating the hypothetical keypoints, the pixels whose confidence score is lower than the set threshold are screened out, so that the generated hypothetical 2D keypoints are closer to the true 2D keypoints. Finally, the method in this paper is compared with the Tekin, PoseCNN, Oberweger and Pvnet algorithm, and demonstrate the superiority of the proposed method. © 2023 IEEE.

关键词： Semantics

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PID control for Aeroengine Based on Sparrow Search Algorithm

PID Control for Aeroengine Based on Sparrow Search Algorithm

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2021 China Automation Congress, CAC 2021

作者： Xu, Liang Wang, Hao Liu, Ying Xue, Wei Li, Ningning Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China National Key Laboratory for Complex Systems Simulation Beijing China BeijingAerospace Propulsion Institute Beijing China

ISBN: (纸本)9781665426473

To address the problem of aeroengine PID parameter optimization and tuning, this work employs the excellent performance of the sparrow search algorithm (SSA) with high convergence accuracy and fast convergence speed to propose a self-tuning PID control method (SSA-PID) for aeroengine parameters. Considering that the oil supply output by the actuator may have a substantial overshoot, the proposed technique adds a penalty mechanism for the overshoot at the output, designs and improves the fitness function weighted by performance indicators, and effectively avoids the possible excessive overshoot and sharp oil supply phenomenon of the engine oil supply. The SSA-PID simulates and verifies the mathematical models of the turbofan engine ' s steady-state operating points on the ground and at high altitudes. The results show that the SSA-PID control method has better parameter tuning and optimization effects, a faster speed step response, and generates a fuel supply that does not have a large overshoot, thereby proving its effectiveness and feasibility. © 2021 IEEE

关键词： Three term control systems

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Study on Autonomous Surgical control system of The Vascular Interventional Surgical Robot Based on Catheter Tip Location Tracking 20

Study on Autonomous Surgical Control System of The Vascular ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Feng, Zhimin Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

The control system of vascular interventional surgical robot is a complex nonlinear system. When the catheter is inserted into human blood vessels, due to the irregular and curved shape of human blood vessels, the catheter will undergo small deformation, which will affect the displacement of the catheter. In order to reduce the displacement tracking error, a BP neural network PID controller was designed to compensate the displacement error of the autonomous vascular interventional surgical robot. Firstly, the dynamic analysis is carried out according to the axial displacement motion of the vascular interventional surgical robot, and the catheter displacement tracking controller was designed. According to the displacement error, BP neural network PID control is used to output three parameters of PID. Finally, in the experiment and PID control simulation comparison, the results show that the BP neural network PID control has a small displacement tracking error and superior tracking performance, which can meet the requirements. © 2023 IEEE.

关键词： Three term control systems

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A DDPG-Based Method of Autonomous Catheter Navigation in Virtual Environment 20

A DDPG-Based Method of Autonomous Catheter Navigation in Vir...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Tian, Wei Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

Vascular interventional surgery is the main method for treating cardiovascular diseases. But navigating endovascular catheters through the vascular tree is a highly challenging task even for highly trained specialists. Automation of this task can reduce the burden on surgeons and is expected to improve the surgical outcomes. Although there have been relevant studies utilizing reinforcement learning algorithms to realize autonomous navigation of catheter in the virtual environment Cathsim. However, the kinematics model of the catheter in Cathsim does not conform to the operating mode of the catheter in real vascular interventional surgery. Besides, there are problems such as low success rates of catheter autonomous navigation tasks. To address these issues, this paper modifies the kinematics model of the catheter in Cathsim and designs a catheter autonomous navigation model based on reinforcement learning DDPG (Deep Deterministic Policy Gradient) algorithm. The experimental results show that the agents trained through DDPG in this paper performs better than the agents trained through PPO (Proximal Policy optimization) in other studies in terms of navigation task success rate, completion time, and contact force between the catheter and vascular wall during the navigation process. © 2023 IEEE.

关键词： Reinforcement learning

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Design of control system for Lower Limb Rehabilitation Robot on the Healthy Side sEMG Signal 20

Design of Control System for Lower Limb Rehabilitation Robot...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yu, Shiqin Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

With the number of stroke patients increasing year by year, rehabilitation exoskeleton robot has been paid more and more attention. For the rehabilitation exoskeleton robot, human-computer interaction ability is an important index, which affects the effect of rehabilitation therapy to a great extent. Surface Electromyography (sEMG) signals are the combined effect of sEMG signals and electrical activities on nerve stem on the skin surface, which can reflect neuromuscular activities in advance and can be used to predict movement intention by sEMG signals. Therefore, this article proposes to use sEMG signals to monitor the motion information of the healthy leg in real-time, extract the characteristics of the electromyography signals, use the sEMG of the healthy leg as the control signal, reflect the motion patterns reflected by the sEMG collected from the healthy side, and then use the motion intention recognition method of Long Short Term Memory(LSTM) neural network to identify the motion intention of the prosthetic limb by identifying the motion patterns of the swing phase of the healthy side. The results indicate that the predicted maximum Root Mean Squared Error(RMSE) is 5.3729, which proves the feasibility of using LSTM model for motion intention recognition and contributes to the real-time and accuracy of lower limb exoskeleton rehabilitation. © 2023 IEEE.

关键词： Long short-term memory

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Study on control Strategy of the Vascular Interventional Surgical Robot Based on LADRC 20

Study on Control Strategy of the Vascular Interventional Sur...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Zhang, Wenqiang Guo, Jian Guo, Shuxiang Fu, Qiang Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications Complicated Systems and Intelligent Robot Laboratory Binshui Xidao Extension 391 Tianjin300384 China Shenzhen Institute of Advanced Biomedical Robot Co. Ltd. No.12 Ganli Sixth Road Jihua Street Longgang District Shenzhen518100 China Beijing Institute of Technology Key Laboratory of Convergence Medical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science No.5Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

As a medical device used in surgery, the vascular interventional surgical robot itself needs to have good control accuracy to ensure the safety of the surgery process. Given this security problem, this paper selects the Line Active Disturbance Rejection control (LADRC) as the control strategy of the vascular interventional robot, aiming at improving the master-slave tracking accuracy of the vascular interventional robot. This article compares the LADRC and PID(Proportional-Integral-Derivative) control strategies through simulation and experiments. The experimental results show that LADRC has good control performance for master-slave tracking and can be applied to the vascular interventional surgical robots. © 2023 IEEE.

关键词： Robotic surgery

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Tissue Surface-enhanced Raman Spectroscopy Combined with Machine Learning Algorithms for Rapid Detection of Alveolar Echinococcosis

Tissue Surface-enhanced Raman Spectroscopy Combined with Mac...

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system Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Jiahui Huang Xiangxiang Zheng Guodong Lv Xiaojing Li Guohua Wu Liang Xu Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin China State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central Asia The First Affiliated Hospital of Xinjiang Medical University Urumqi China School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

Alveolar echinococcosis (AE) remains a serious worldwide public health problem as a very harmful human tapeworm disease. Rapid and accurate diagnosis of AE is crucial for treatment and postoperative recovery. This study explored the applicability of tissue surface Raman spectroscopy (SERS) combined with machine learning for rapid AE detection. Specifically, liver tissue section samples were obtained by creating an AE mouse model and SERS spectra were acquired. Five kinds of machine learning methods were used to construct AE diagnosis model, among which the linear kernel support vector machine (SVM) model had the best classification result, and the accuracy rate reached $95.7 \%$. Then, the linear SVM model was subjected to feature significance analysis, which demonstrated that the biochemicals corresponding to the spectra of 641,716 and $1372 \mathrm{~cm}^{-1}$ might be potential biomarkers. Gaussian noise is further added to test the noise interference resistance of different machine learning algorithms, and it is found that SVM with Gaussian radial basis function (RBF) kernel function has better noise interference resistance. The results show that tissue SERS spectroscopy combined with SVM algorithm for rapid detection of AE has a promising application.

关键词： Support vector machines Analytical models Machine learning algorithms Accuracy Biological system modeling Surface resistance Raman scattering Interference Machine learning Kernel

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