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Chinese Automation Congress (CAC)

作者： Aoyun Ma Dewei Li Yugeng Xi Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

The hydrogen gas turbine can be the key technology for carbon-neutral in the future. The flexibility of gas turbine under various operation conditions is an important issue. A state-space model of hydrogen gas turbine with different hydrogen volume ratio mixed fuel is constructed based on Rowen model, and a full-dimensional state observer is designed to obtain the states of state-space model. The model predictive control method based on amplitude decaying aggregation strategy is presented to stabilize the rotational speed of hydrogen gas turbine under various constraints, which are to ensure the safety of operation. The number of variables contained in the optimization problem to be solved online is reduced by aggregation strategy. The simulation results confirmed that the presented method works well, and the effects of the hydrogen volume ratio for the performance of hydrogen gas turbine are discussed.

关键词： Hydraulic turbines Solid modeling Computational modeling Hydrogen Velocity control Predictive models Observers

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Modeling, Simulation, and Parameter Design of Actuation Mechanisms Based on New Magnetic control Materials

Modeling, Simulation, and Parameter Design of Actuation Mech...

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

作者： Ruixuan Shen He Tian Guanqiao Zhao Ziliang Zhu Jiangping Li Chao Liang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) Tianjin China Tianjin Sanyuan Power Equipment Manufacturing Co. Ltd Tianjin China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

With the rapid advancement of technology, the reliability and efficiency of power systems have become increasingly critical. In power systems, pole-mounted circuit breakers play a vital role. This paper presents a design scheme for an actuation mechanism of a pole-mounted circuit breaker based on new magnetic control materials. By analyzing the working principle of this actuation mechanism, a mathematical model was constructed, and a corresponding virtual prototype model was established using multi-body dynamics simulation software ADAMS and the dynamics mathematical model of this type of actuation mechanism. Key performance parameters of the circuit breaker were optimized using a quantum genetic algorithm. Simulation experiments verified that the proposed parameter settings achieved a closing time of 7.6 ms, demonstrating significant improvements in circuit breaker performance. The results of this study are of great importance for the optimization design and performance enhancement of circuit breakers in power systems.

关键词： Vacuum systems Circuit breakers Power system dynamics Mathematical models Software systems simulation Integrated circuit modeling Magnetic circuits Optimization Genetic algorithms

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Exploring the Reform of Mechanical Drawing Teaching and Undergraduate Training Based on the “Integration of Competition-Oriented Education and Industry-University Collaboration”

Exploring the Reform of Mechanical Drawing Teaching and Unde...

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International Conference on Educational and Information Technology (ICEIT)

作者： Zhang Runfeng Ming Yankun Liu Zhenzhong Wu Jianguo Wang Xiaofei Sun Yanfang 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 Hanhailanfan Marine Technology Co. Ltd. Tianjin China

ISBN: (数字)9798350372663

ISBN: (纸本)9798350372670

This study aims to explore the reform of mechanical drawing teaching and the undergraduate training model with the goal of cultivating high-quality mechanical engineering undergraduate students. Grounded in the concepts of “synergy between science and education” and “integration of competition-oriented education and industry-university collaboration,” this research places talent cultivation as the central focus, linking it with discipline construction and emphasizing scientific research. The study promotes the reform of a collaborative education mechanism known as “integration of competition-oriented education and industry-university collaboration,” effectively establishing a multi-level and multi-dimensional undergraduate training model for mechanical engineering students that incorporates the “dual mentor system” and integrates theory, practice, and application. To apply this model in teaching practice, this research has undertaken the reform of traditional engineering drawing education, specifically addressing the issue of the gap between theory and practice in conventional teaching approaches. The proposed training program not only facilitates the development of innovative mechanical engineering professionals but also offers insights for the reform of undergraduate teaching models in the context of constructing “new engineering disciplines”.

关键词： Training Couplings Technological innovation engineering drawings Collaboration Mechanical engineering Machinery

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Point Cloud based Motion State Estimation Method for Autonomous Driving

Point Cloud based Motion State Estimation Method for Autonom...

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International Conference on Advanced Mechatronic systems (ICAMechS)

作者： Tao Jiang Enzhi Zhu Sidong Wu Linshuai Zhang Shuoxin Gu Lin Xu Qian Wang Xianggui Tang School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu

Generally, motion vector information primarily stems from moving objects, while static objects contribute minimally to the estimation task. Traditional approaches for motion vector estimation typically rely on scene flow methods that depend on deep models to extract features from individual points at a high cost. These methods then acquire flow information through complex matching mechanisms or feature decoding. Such approaches are computationally expensive and exhibit substantial latency. Moreover, they neglect the importance of motion objects in motion vector estimation and the interference from static objects. Therefore, this paper introduces a novel method that first performs point cloud motion segmentation and subsequently estimates motion vectors. This approach focuses on leveraging point cloud information annotated with motion objects to estimate three-dimensional scene flow more effectively. By employing motion segmentation, we can obtain annotations for moving objects, enabling greater emphasis on the estimation of motion vectors for more challenging cases. In our experiments conducted on the KITTI dataset, the proposed method demonstrates superior performance compared to existing scene flow estimation methods. Specifically, without considering motion segmentation errors, the error in the motion direction is only 0.0363 m/s, showcasing better performance. Additionally, our method achieves an error of 0.076 m for three-dimensional endpoint error (EPE3D), showcasing distinct advantages over current scene flow networks.

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A PSO-RBF neural network for BOD multi-step prediction in wastewater treatment process

A PSO-RBF neural network for BOD multi-step prediction in wa...

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2021 China Automation Congress, CAC 2021

作者： Liu, Yonglei Li, Wenjing Faculty of Information Technology Beijing University of Technology Beijing Institute of Artificial Intelligence Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665426473

The single-step prediction of the effluent biochemical oxygen demand (BOD) in wastewater treatment process (WWTP) cannot provide the information for future trends, which will affect the decision-making for subsequent control strategies in WWTP. To solve this problem, a radial basis function (RBF) neural network soft-sensing model based on PSO algorithm (PSO-RBF) is proposed for multi-step prediction of the biochemical oxygen demand (BOD) in WWTP. First, we propose an RBF model for multi-step prediction based on MIMO strategy. Then, the PSO algorithm is used to optimize the RBF parameters. Finally, the proposed model is applied to a four-step BOD prediction in WWTP. Experimental results show that this model can better predict BOD in multiple steps compared to traditional models. © 2021 IEEE

关键词： Forecasting

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Analysis of Strengthening Mechanism and Thermal Stability of M23c6 and Laves Phase in a Ferrite Matrix

SSRN

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SSRN 2023年

作者： Jin, Tiejian Shen, Junjie Ruan, Taotao Zhang, Dechang Xu, Yu Ren, He 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 strengthening of ferrite matrix steel depends on the strengthening mechanism and thermal stability of M23C6 and Laves phases. This study investigated M23C6(Fe,Cr)23C6 and Laves(Fe2Nb) phase-strengthened ferritic steels. The creep microstructure, the interface structure, and the nanoindentation creep behavior of the second phase were studied. Results showed that the dislocation density in (Fe,Cr)23C6 strengthened ferritic steel after creep is lower than Fe2Nb strengthened ferritic steel. The dislocations in the crept (Fe,Cr)23C6 strengthened ferritic steel are straight without accumulation, significantly bending. The dislocations bend and entangle, forming dislocation walls in the crept Fe2Nb-strengthened ferritic steel. The orientation relationships between (Fe,Cr)23C6/Fe2Nb and ferrite matrix are [001]α-Fe//[011](Fe,Cr)23C6, (020)α-Fe//(71[[EQUATION]])(***)23C6,[001]α-Fe//[5[[EQUATION]]]Fe2Nb,(01[[EQUATION]])α-Fe//(03[[EQUATION]])Fe2Nb. The atomic interface mismatch between M23C6/Fe2Nb and the ferrite matrix is 20% of the semi-coherent interface and 1.6% of the coherent interface. The thermal stability of Fe2Nb is better than (Fe,Cr)23C6. The creep stress exponents of (Fe,Cr)23C6 and Fe2Nb in the ferrite matrix are 4.4 and 12.2, respectively. The alloy’s creep deformation follows dislocation climbing over the second phase. Second-phase Fe2Nb strengthening played a more significant role than (Fe,Cr)23C6 in enhancing the ferrite matrix. The results provide a theoretical foundation for developing ferritic heat-resistant steel based on Laves (Fe2Nb) phase strengthening. © 2023, The Authors. All rights reserved.

关键词： Creep

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Surface Defect Detection Based on Deep Learning and Collaborative Cloud-edge Computation 7

Surface Defect Detection Based on Deep Learning and Collabor...

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7th International Conference on Computer and Communications, ICCC 2021

作者： He, Shunjie Yang, Bo Zhu, Dafeng Li, Cheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665409506

Surface defect detection is a fundamental step of quality management. Nowadays, surface defect detection system based on machine vision technology has made great progress which can gradually replace the human inspector. With the help of convolutional neural networks, the accuracy and stability of the surface defect detection algorithm are improving rapidly. However, it is difficult to process the images which have small defect areas and complex backgrounds. Furthermore, lacking defective samples and limited computation resources are also tough problems. To deal with these problems, a two-stage algorithm combined with object detection and classification networks is proposed. Transform learning and data augmentation are used to deal with the problem of lacking defect samples. Besides, a detection system based on collaborative cloud-edge computation is designed to improve the performance of the algorithm. The result shows that the proposed method has high performance and low requirements of computation resources. © 2021 IEEE.

关键词： Computer vision

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Pseudo-LiDAR for Visual Odometry

arXiv

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arXiv 2022年

作者： Deng, Huiying Wang, Guangming Feng, Zhiheng Jiang, Chaokang Wu, Xinrui Miao, Yanzi Wang, Hesheng Advanced Robotics Research Center AI Research Institute School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

As one of the important tasks in the field of robotics and machine vision, LiDAR/visual odometry provides tremendous help for various applications such as navigation, location, etc. In the existing methods, LiDAR odometry shows superior performance, but visual odometry is still widely used for its price advantage. Conventionally, the task of visual odometry mainly rely on the input of continuous images. However, it is very complicated for the odometry network to learn the epipolar geometry information provided by the images. In this paper, the concept of pseudo-LiDAR is introduced into the odometry to solve this problem. The pseudo-LiDAR point cloud back-projects the depth map generated by the image into the 3D point cloud, which changes the way of image representation. Compared with the stereo images, the pseudo-LiDAR point cloud generated by the stereo matching network can get the explicit 3D coordinates. Since the 6 Degrees of Freedom (DoF) pose transformation occurs in 3D space, the 3D structure information provided by the pseudo-LiDAR point cloud is more direct than the image. Compared with sparse LiDAR, the pseudo-LiDAR has a denser point cloud. In order to make full use of the rich point cloud information provided by the pseudo-LiDAR, a projection-aware dense odometry pipeline is adopted. Most previous LiDAR-based algorithms sampled 8192 points from the point cloud as input to the odometry network. The projection-aware dense odometry pipeline takes all the pseudo-LiDAR point clouds generated from the images except for the error points as the input to the network. While making full use of the 3D geometric information in the images, the semantic information in the images is also used in the odometry task. The fusion of 2D-3D is achieved in an image-only based odometry. Experiments on the KITTI dataset prove the effectiveness of our method. To the best of our knowledge, this is the first visual odometry method using pseudo-LiDAR. Copyright © 2022, The Authors. A

关键词： Pipelines

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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International Conference on Communication Technology (ICCT)

作者： Junpeng Yin Yusun Fu Haobo Huang Jinhui Tang Ningbo Artificial Intelligence Institute Shanghai Jiao Tong University Ningbo China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China School of Electronic Information and Electrical Engineering the Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme.

关键词： Codes Error analysis Metaverse Distribution strategy Spatial audio Bit rate Symbols Communications technology Protection Spatial resolution

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Surgical Gesture Recognition in Open Surgery Based on 3DCNN and SlowFast

Surgical Gesture Recognition in Open Surgery Based on 3DCNN ...

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IEEE Information Technology, Networking, Electronic and Automation control Conference

作者： Yutao Men Jian Luo Zixian Zhao Hang Wu Feng Luo Guang Zhang Ming Yu 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 Systems Engineering Institute Academy of Military Sciences People's Liberation Army Tianjin China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

In the field of computer-aided medicine, automated surgical gesture recognition is an important research direction. Its main applications include automated skills assessment, intraoperative guidance, and education and training systems. Current research has focused on robotic surgery, and there is less research on surgical gestures for open surgery. Therefore, in this study, a new simulated open surgery dataset was developed, and a series of surgical gestures for open surgery were defined for closure the abdomen surgery with the cooperation of professional doctors. In addition, this paper uses the classical algorithm 3DCNN and SlowFast model in the field of action recognition to perform offline recognition of surgical gestures for open surgery on the dataset. 3DCNN uses R3D and R(2+1)D models. The experimental results show that on the self-built open surgical dataset, the R3D model has the best surgical gesture recognition results, with an accuracy rate of 90.4%, a precision rate of 90.5%, and a recall rate of 90.0%.

关键词： Training Automation Accuracy Surgery Gesture recognition Medical services Information technology Robots Abdomen

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