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2021 China Automation Congress, CAC 2021

作者： Zhou, Long Tong, Jigang Dong, Enzeng Zhu, Lin Zhang, Jiachen Tianjin Key Laboratory For Control Theory and Applications in Complicated Systems Tianjin University of Technology Tianjin300384 China China North Industries Group 210 Reseasrch Institute Beijing China

ISBN: (纸本)9781665426473

Parkinson's disease is a common neurodegenerative disease, which seriously affects the life of patients. Whether there is an objective and reliable method to classify and identify the disease grade is of great significance in the clinical diagnosis of Parkinson's disease. In this paper, principal component analysis was used to comprehensively evaluate the degree of Parkinson's disease of 28 randomly selected subjects, establish a comprehensive scoring model of Parkinson's disease degree, and fit it according to HY grade, so as to realize the quantification of Parkinson's disease grade. Based on the data of vertical ground reaction force, 12 gait features with strong correlation are calculated as the main features to establish the scoring model. The validity of the model is verified by predicting the HY grade of another 12 subjects in the randomly selected data set. The results show that the prediction accuracy is 83.3%, which can effectively predict the Parkinson's disease level of subjects. © 2021 IEEE

关键词： Principal component analysis

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Dual-beam photothermal material trace detection method based on self-mixing interference

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Applied Optics 2025年第16期64卷 4549-4558页

作者： Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach $8.0 \times {10^{- 8}}\;{\rm mol/L}$ . This method does not require lab.ling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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Computation and analysis of aero-optic imaging deviation of a blunt nosed aircraft with Mach number 0.5—3

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Optoelectronics Letters 2023年第1期19卷 55-59页

作者： XU Liang ZHAO Shiwei XUE Wei WANG Tao Tianjin Key Laboratory for Control Theory&Applications in Complicated Systems School of Electrical Engineering and AutomationTianjin University of TechnologyTianjin300384China China Academy of Aerospace Science and Innovation Beijing100083China School of Intelligent Engineering Sun Yat-sen UniversityGuangzhou510275China

Aero-optic imaging is a kind of optical effect,which describes the imaging deviation on the imaging *** this paper,the effect of the change of Mach number of blunt aircraft on the aero-optic imaging deviation is *** imaging deviations of Mach number 0.5—3 are analyzed *** results show that with the increase of Mach number,imaging deviation increases gradually,and the increase rate is gradually *** deviation slope decreases gradually with the increase of Mach number,and gradually tends to be zero,suggesting that imaging deviation is not sensitive to the change of the larger Mach *** other words,the Mach number of smaller changes can lead to larger imaging *** the Mach number of the aircraft increases,the slope of the imaging offset tends to be closer and closer to *** the Mach number of the aircraft increases to a certain extent,the change of the imaging offset will not have much ***,in order to reduce the impact of flight speed on imaging migration,the aircraft should fly at a higher Mach number.

关键词： deviation closer number

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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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Motor Imagery and Mental Arithmetic Classification Based on Transformer Deep Learning Network

Motor Imagery and Mental Arithmetic Classification Based on ...

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyuan Ye Jigang Tong Sen Yang Yinghui Chang Shengzhi Du Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion Tianjin China Department of Electrical Engineering Tshwane University of Technology Pretoria South Africa

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

Non-invasive electroencephalography (EEG) signals find widespread application in brain-computer interfaces (BCI), with paradigms such as motor imagery (MI), mental arithmetic (MA) and emotion recognition being particularly common. This study aims to explore feature extraction and classification methods for MI and MA tasks. We employed convolutional neural networks (CNN) combined with Transformer networks and Fasternet Block to extract features. Through our reaearch, we obtained features for MI and MA tasks, and used softmax classification for binary classification of these tasks. We conducted on a publicly availab.e dataset consisting of data from 29 subjects. The experimental results demonstrate that our method achieved high classification accuracy in MI and MA tasks. The final accuracy rates for MI and MA tasks were 88.67% and 91.23%, respectively.

关键词： Accuracy Mechatronics Feature extraction Brain modeling Transformers Motors Electroencephalography

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EEG Signal Driving Fatigue Detection based on Differential Entropy

EEG Signal Driving Fatigue Detection based on Differential E...

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IEEE International Conference on Mechatronics and Automation

作者： Danyang Wang Jigang Tong Sen Yang Yinghui Chang Shengzhi Du Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion Tianjin China Department of Electrical Engineering Tshwane University of Technology Pretoria South Africa

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

With the gradual increase of vehicle penetration rate, driving safety has become a problem that people pay attention to, and traffic accidents caused by fatigue are mostly, therefore, it is meaningful to devote ourselves to research on the method of detecting driving fatigue so as to achieve safety warning. Based on this, in this paper, we collect the EEG signals of the experimenter through driving simulation, then extract the features through differential entropy, classify the features with GBDT, and finally determine the fatigue level of the subject with the classification results. We use our method to analyse the difference with sample entropy and fuzzy entropy at the feature level, and with KNN and SVM at the classification level. The comparison shows that our method has significant accuracy in EEG-based fatigue *** can be used accurately in extraction methods through its properties, and differential entropy-based GBDT methods may be useful in detecting driver fatigue.

关键词： Support vector machines Mechatronics Nearest neighbor methods Fatigue Feature extraction Entropy Electroencephalography

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Multilevel Decomposition Time Aggregation Graph Convolution Networks for Skeleton-Based Action Recognition

Multilevel Decomposition Time Aggregation Graph Convolution ...

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IEEE International Conference on Mechatronics and Automation

作者： Wenhua Li Enzeng Dong Jigang Tong Sen Yang Zufeng Zhang Wenyu Li Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology 391 Binshui West Road Tianjin China College of Artificial Intelligence Nankai University 94 Weijin Road Tianjin China

Skeleton-based human action recognition has become a popular topic among researchers. This is because using skeletal data provides a robust solution to problems encountered in complex environments, such as changes in perspective and background interference. The robustness of skeletal data enables recognition methods to focus on more specific and relevant features. We propose a model called multilevel decomposition time aggregation graph convolution network (MDT-GCN), which utilizes a multilevel graph convolution kernel to capture higher-order spatial dependence relationships between joints. This is achieved by decomposing a human topology graph into smaller graphs, each of which has its own graph convolution kernel. To further enhance the performance of our model, we employ a two-flow framework and channel topology refinement strategy. Our experiments on the NTU-RGB+D60 and NTU-RGB+D120 datasets demonstrate that our MDT-GCN network outperforms the previous algorithm and significantly improves the accuracy of action recognition.

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Differential Enhancement and Commonality Fusion for RGBT Tracking

Differential Enhancement and Commonality Fusion for RGBT Tra...

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IEEE International Conference on Mechatronics and Automation

作者： Jianrong Yang Enzeng Dong Jigang Tong Sen Yang Zufeng Zhang Wenyu Li Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology 391 Binshui West Road Tianjin China College of Artificial Intelligence Nankai University 94 Weijin Road Tianjin China

Target tracking is a fundamental task and an important part in the field of computer vision. The image information contained in the visible (RGB) modality and thermal infrared (T) modality has differences. RGBT tracking utilizes this difference to fuse the information of the two modalities, fully combining the uniqueness and complementarity of the information of the two modalities. How to maximize the uniqueness of individual modalities in RGBT tracking and how to effectively combine the complementarity of the two modalities is the key issue in RGBT tracking. For the combination of the uniqueness and complementarity of the two modalities, a novel Differential Enhancement and Commonality Fusion Network (DECFNet) is designed in this paper, in which the main components include a feature enhancement module for the visible modality and a feature enhancement module for the thermal infrared modality, as well as a fusion module that effectively fuses the information of both. The results on three RGB T tracking benchmark datasets demonstrate the effectiveness of the proposed method.

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Rapid calibration method for 3d laser scanner

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Recent Patents on Engineering 2020年第2期14卷 234-241页

作者： Liu, Bin Qiao, Qian Han, Fangfang Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin City300384 China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin City300384 China

Background: The 3D laser scanner is a non-contact active-sensing system, which has a number of applications. Many patents have been filed on the technologies for calibrating 3D laser scanner. A precise calibration method is important for measuring the accuracy of the 3D laser scanner. The system model contains three categories of parameters to be calibrated which include the camera intrinsic parameters, distortion coefficients and the light plane parameters. Typically, the calibration process is completed in two steps. Based on Zhangs method, the calibration of the camera intrinsic parameters and distortion coefficients can be performed. Then, 3D feature points on the light plane should precisely be formed and extracted. Finally, the points are used to calculate the light plane parameters. Methods: In this paper, a rapid calibration method is presented. Without any high precision auxiliary device, only one coplanar reference target is used. By using a group of captured images of the coplanar reference target placed in the field of view arbitrarily, calibration can be performed in one step. Based on the constraint from the planes formed by the target in different directions and the camera imaging model, a large amount of 3D points on the light plane can easily be obtained. The light plane equation in the camera coordinates system can be gathered by executing plane fitting to the 3D points. Results: During the experimental process, the developed 3D laser scanner was calibrated by the proposed method. Then, the measuring accuracy of the system was verified with known distance in vertical direction of 1mm with sequential shifting motion generated by precision translation stage. The average value of the measured distances was found to be 1.010mm. The standard deviation was 0.008mm. Conclusion: Experimental results prove that the proposed calibration method is simple and reliable. © 2020, Bentham Science Publishers. All rights reserved.

关键词： Calibration

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Study on a Two-layer Path Planning Method of Spherical Multi-robot 20

Study on a Two-layer Path Planning Method of Spherical Multi...

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

作者： Li, Chenqi 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 Key Laboratory of Convergence Medical Engineering Systems and Healthcare Technology The Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology No.5 Zhongguancun South Street Beijing100081 China

ISBN: (纸本)9798350320831

A path planning method based on a two-layer coordination system is proposed for the compatibility requirement of path planning global optimum and local coordination in a spherical multi-robot system. In the first layer of the algorithm, the global path quality is improved by proposing a nonlinear sine factor and a sparrow search algorithm with improved levy flight strategy to plan the global collision-free optimal path for each robot. In the second layer, a rolling window method is used to determine the possible collision positions of each robot in the system, and a priority-based conflict resolution strategy is proposed to complete the local coordination of the path near the corresponding position. The experimental results show that the path planning method enables the robots to drive along the global optimal path, but still can carry out flexible and orderly local path coordination, which effectively improves the path planning performance of the system. © 2023 IEEE.

关键词： Multipurpose robots

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