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IEEE International Conference on mechatronics and Automation

作者： Guangyin Nie Xinhua Zhao Yihan Ren Liang Liu 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)9798350388077

ISBN: (纸本)9798350388084

Pipes in various are dominated in in the process of industrial production. To avoid the pipeline leak due to inner corrosion, it is essential to develop pipe inspection mechanisms to detect the wall thickness of the pipes used in production. The paper presents three kinds of out-pipe detection mechanisms (ODM) for different petrochemical pipeline detection demands based on eddy current testing (ECT) method. A linear inspection mechanism with fixed length is firstly proposed to detect defects of straight pipe. Secondly, a rotary inspection mechanism is designed for pipeline weld detection. Besides, an out-pipe scanning wheeled robotic mechanism is developed to detect wall thickness of pipes and avoid small obstacles such as valves on the pipelines. Lastly, detection experiments and simulations are carried out to verify the effectiveness of the designed out-pipe detection mechanisms.

关键词： mechatronics Welding Pipelines Production Inspection Valves Petrochemicals

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Kinematic modeling and simulation of a 5-DOF hybrid mechanism for active vibration isolation

Kinematic modeling and simulation of a 5-DOF hybrid mechanis...

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IEEE International Conference on mechatronics and Automation

作者： Xiaoqing Qiu Yue Ma Zijie Wang Bin Li Lin Pin Doudou Duan 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)9798350388077

ISBN: (纸本)9798350388084

Vibration generated by road bumps can cause secondary injury to patients. The risk of secondary injury can be significantly reduced by attaching an active suspension system to isolation medical beds. In this paper, a five DOFs (degree of freedoms) hybrid mechanism is designed by combining a 3-P(UU) 2 mechanism and a 2-PUS mechanism through a universal joint, leading to 3T2R movement capabilities to reduce the vibration. The kinematic models are firstly established to evaluate the displacement, velocity and acceleration of the hybrid mechanism. On this basis, a typical trajectory is planned to simulate the movement capabilities of the mechanism by using the trapezoidal acceleration curve motion law. Finally, the effectiveness of the kinematic models is verified by compared the results with those simulated by SolidWorks. The research results of this paper provide a solid foundation to the dimensional synthesis of the hybrid mechanism.

关键词： Vibrations Performance evaluation Solid modeling Roads Kinematics Solids Vectors

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A clock synchronization method for EtherCAT master

A clock synchronization method for EtherCAT master

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2023智能制造与机械动力学学术大会

作者： Libo Cao Taiyong Wang Yongbin Zhang Songhui Jia Chong Tian Ying Tian Qingjian Liu School of Mechanical Engineering Tianjin University Renai College Tianjin University Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of Technology

EtherCAT has been widely applied in the motion control domain due to its advantages of the fast response speed,low CPU usage and good synchronization *** the distributed clock synchronization mechanism shows strong performance between the slaves,the clock synchronization method between the master clock and the reference clock is still open for users to choose,and there are few studies in this *** paper proposed a novel clock synchronization mechanism between the master of CNC system and the reference slave which also call servo motor of drive *** mechanism relies on sync0 of the reference servo ***0 is very stable and almost no time jitter,which is a dozen *** clock of the master of the numerical control system(CNC) adjusted the trigger moment of the interpolation period adaptively and dynamically to realize synchronization between master and reference servo motor taking sync0 as *** addition,the proposed method almost hardly add computational load and modify the EtherCAT frames by adding four bytes only without increasing an excessive communication load in the interpolation *** synchronization mechanism fills the gap of distributed clock synchronization which is the synchronization mechanism between reference servo motor and the other servo *** are preformed to verify the synchronization *** results demonstrate that the jitters of EtherCAT frames are measured to be only 112ns and 95.5 ns.

关键词： the CNC system synchronization reference slave sync0

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Significant Wave Height Prediction Based on VMD-SA-MLP-BP

Significant Wave Height Prediction Based on VMD-SA-MLP-BP

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2023 China Automation Congress, CAC 2023

作者： Wu, Yining Zhang, Runfeng Liu, Fang Liu, Zhenzhong Wu, Jianguo Dong, Haonan School of Mechanical Engineering Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education China Yichang Research Institute of Testing Technology Yichang443003 China Tianjin Hanhailanfan Marine Technology Co. Ltd. Tianjin300457 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350303759

Waves seriously impact port construction, worldwide route planning, military activities, and wave power generation. To improve the accuracy of significant wave height prediction, we proposed a novel prediction method, a multi-layer perceptron combined with a backpropagation adjustment (MLP-BP) prediction model that combines mutation mode decomposition (VMD) and a simulated annealing optimization algorithm (SA). Firstly, we use the variable modulus method to decompose the significant wave height sequence data and transform the wave height sequence into multiple different sub-modes (IMF) to reduce the complexity and non-stationarity of the data. Secondly, the simulated annealing algorithm (SA) is used to optimize the weight and bias of the MLP-BP neural network to find the optimal parameter configuration and improve the performance and generalization ability of the prediction model. Finally, the decomposed sub-modal components of each significant wave height sequence are inserted into the MLP-BP neural network and the predicted values of each element are summed to obtain the final significant wave height prediction. The prediction results of the SSA-MLP-BP, PSO-MLP-BP, SA-MLP-BP, and VMD-SA-MLP-BP were compared and demonstrated that the VMD-SA-MLP-BP model performed best. The MAE, MAPE, MSE, RMSE, and R2 of the prediction evaluation indexes were 0.036 m, 11.7%, 0.004 m2, 0.067 m, and 0.983, respectively, which performed well in predicting significant wave height. © 2023 IEEE.

关键词： Variational mode decomposition

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Human Activity Recognition Based on a Modified Capsule Network

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Mobile Information systems 2023年第1期2023卷

作者： Zhu, Shanying Chen, Wei Liu, Fulong Zhang, Xiaotao Han, Xiupeng 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 Tianjin China

Human activity recognition (HAR) has attracted considerable research attention in the past decade with the development of wearable sensor technology and deep learning algorithms. However, most of the existing HAR methods ignored the spatial relationship of features, which may lead to recognition errors. In this paper, a novel model based on a modified capsule network (MCN) is proposed to accurately recognize various human activities. This novel model is composed of a convolution block and a capsule block, which can achieve end-to-end intelligent recognition. In the meantime, the spatial information among features is preserved through a dynamic routing process. To validate the effectiveness of the model, a human activity dataset is constructed by placing an inertial measurement unit (IMU) on the calf of the volunteers to collect their activity data in daily life, including walking, jogging, upstairs, downstairs, up-ramps, and down-ramps. The recognition accuracy of this novel approach can reach 96.08%, which performs better than the convolutional neural network (CNN) with an accuracy of 91.62%. In addition, it is evaluated on two public datasets named WISDM and UCI-HAR, and the accuracies achieve 98.21% and 95.28%, respectively, which presents higher accuracy than the reported results obtained from benchmark algorithms like CNN. The experimental results show that the proposed model has better activity detection capability and achieves outstanding performance for HAR. © 2023 Shanying Zhu et al.

关键词： Convolution

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A Study of Soil Modelling Methods Based on Line-Structured Light——Preparing for the Subsoiling Digital Twin

SSRN

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SSRN 2024年

作者： Li, Xia You, Birong Wang, Xuhui Zhao, Zhipeng Qi, Tianyu Xu, Jinyou Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Centre for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

The virtual model serves as the foundation for constructing a digital twin system. In order to provide technical guidance for the construction of a digital twin system for subsoiling, this study employed the line structured light method for soil model generation. Field experiments and indoor experiments were conducted separately, using the extreme value method, grayscale centroid method, and Steger algorithm to extract the laser centrelines in the experiments. The results show that the extreme value method and grayscale centroid method have almost the same processing time when dealing with two types of images, which are 1.9ms and 18ms respectively. The Steger algorithm has a significant difference in processing time when dealing with indoor and field images, with the processing time being longer for indoor images, approximately 300ms. Regarding memory usage, there is a large difference when the extreme value method processes two sets of images. Therefore, the grayscale centroid method is the most suitable method for centreline extraction in a digital twin system for subsoiling. When performing 3D reconstruction, the camera shooting frequency is positively correlated with the reconstruction effect, while the moving speed is negatively correlated with the reconstruction effect. Of course, the reconstruction effect is also related to the performance of the binocular camera used. In addition, the processing time for each image during reconstruction is within 1ms, indicating that the method of line laser 3D reconstruction can solve the problem of soil modelling in subsoiling digital twin. © 2024, The Authors. All rights reserved.

关键词： Soils

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The Influence of Microstructural Evolution on Performance Degradation in Solid Oxide Fuel Cells

SSRN

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SSRN 2024年

作者： Shao, Yuqing Shen, Junjie Ren, He Zhao, Liwei Xue, Ziyu 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

The microstructure evolution effects performance degradation of solid oxide fuel cells (SOFCs) under elevated temperatures. The microstructural evolution, including elemental diffusion, phase changes, and Ni agglomeration, is studied via X-ray diffraction (XRD) and scanning electron microscopy energy dispersive spectrometer (SEM-EDS) techniques. The ohmic resistance and polarization impedance, including activation polarization impedance and concentration resistance, causing the performance degradation, are estimated using electrochemical impedance spectroscopy (EIS) and distribution of relaxation time (DRT) techniques. The voltage gradually decreases from 0.9 V, at the beginning of the load, to 0.75 V after 240 h of service. The formation of pores at the (La0.6Sr0.4Co0.2Fe0.8O3-δ) LSCF/(Gd0.1Ce0.9O2-δ) GDC interface and cracks at the (8 mol% Y2O3-stabilized ZrO2) YSZ/NiO-YSZ interface induce the increase in ohmic resistance. The increase in activation polarization resistance is attributed to the formation of the SrZrO3 phase and Gd2(Zr1-xCex)2O7, at the YSZ/GDC interface, and the redistribution and coarsening of Ni. The formation of Co- or Fe-based oxides in the LSCF layer slightly increases the concentration polarization impedance. © 2024, The Authors. All rights reserved.

关键词： Scanning electron microscopy

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The Influence of Hydrogen on the Recrystallization Texture of a Face Centered Cubic Metal

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SSRN 2024年

作者： Ren, He Shen, Junjie Guo, Xiangru Shao, Yuqing Zhao, Liwei 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

The evolution of an alloy’s microstructure in a hydrogen atmosphere at high temperatures is one of the important factors contributing to the degradation in the alloy’s strength. The present study aimed to clarify the influence of hydrogen on the recrystallization texture of a face centered cubic (FCC) metal. As a model of FCC metal, commercially pure nickel (Ni) was cold-rolled and then annealed separately in vacuum and hydrogen atmospheres. Subsequently, the recrystallization textures were analyzed using EBSD and XRD. Hydrogen promoted the recrystallization of -oriented deformed grains while hindering the recrystallization of -oriented deformed grains. It increased the content of {011} texture, promoted the decrease of R-Cube texture content, hindered the increase of Cube texture content， and hindered the reduction in contents of Brass, Copper, Goss, and S textures. In addition, it had an insignificant effect on {011} texture contents. Hydrogen demonstrated an anisotropic effect on the dislocation movement and density of grains with different orientations. Specifically, it impeded the dislocation movement within -oriented deformed grains while facilitating the dislocation movement within -oriented deformed grains. As a result, hydrogen induced an increase in dislocation density in -oriented grains and a decrease in dislocation density in -oriented grains. © 2024, The Authors. All rights reserved.

关键词： Hydrogen

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Exploration of Statistical Methods for Distribution of Graduation Scores in Engineering Education Professional Certification

Exploration of Statistical Methods for Distribution of Gradu...

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International Conference on Educational and Information Technology (ICEIT)

作者： Lijun Xue Haozhi Mu Yahong Xue Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China

ISBN: (数字)9798350372663

ISBN: (纸本)9798350372670

According to the requirements of the engineering education professional certification, this paper analyzes the characteristics of the graduation score data table. For the unclear scores in the table, their validity is determined by synthesizing other information. Effective method for processing this data table is provided, and a computer program is developed to directly obtain the distribution table and chart of the scores of the past three years graduates. This provides a basis for analyzing the degree of achievement of graduation requirement and meets the requirements of the engineering education professional certification.

关键词： Statistical analysis Engineering education Information technology Certification

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Logistics Demand Forecasting and Scheduling Optimization Using K-Means Clustering and Deep Q-Network

Logistics Demand Forecasting and Scheduling Optimization Usi...

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Electronics, Energy systems and Power Engineering (EESPE), IEEE International Conference on

作者： Kun Liang Hang Zhang School of Management Tianjin University of Technology Tianjin China 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)9798350389579

ISBN: (纸本)9798350389586

With the rapid development of e-commerce and supply chain management, logistics demand forecasting and scheduling optimization have become key links in improving logistics efficiency and service quality. To meet this challenge, this paper proposes a logistics demand forecasting and scheduling optimization method that combines K-Means clustering with deep Q network (DQN). Cluster analysis is used to reduce data complexity, and deep reinforcement learning is used to achieve intelligent scheduling. First, the background, challenges and research motivation of logistics demand forecasting and scheduling optimization are introduced. Secondly, the research results in related fields are reviewed, and the shortcomings of current research are pointed out. Then, the K-Means clustering algorithm, deep $\mathbf{Q}$ network theory and specific models of logistics demand prediction and scheduling optimization are elaborated. Then, the performance of the proposed method is designed and tested. The experimental results show that the proposed method can significantly improve the accuracy of logistics demand prediction, up to 0.93, optimize scheduling strategies, reduce logistics costs, and improve customer satisfaction.

关键词： Training Accuracy Costs Computational modeling Customer satisfaction Demand forecasting Clustering algorithms Predictive models Scheduling Logistics

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