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5th International Conference on Advanced engineering Theory and Applications, AETA 2018

作者： Gavlas, Antonin Koziorek, Jiri Rakay, Robert Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava 17. listopadu 15 Ostrava70833 Czech Republic Department of Automation Control and Human Machine Interactions Faculty of Mechanical Engineering Technical University of Košice Park Komenského 8 Košice042 00 Slovakia

ISBN: (纸本)9783030149062

An article is based on comparing of data processing within PLC and MCU with using Cloud platforms. The last advances in computation and communication technologies are taking shape in the form of IoT (Internet of Things), M2M (Machine to Machine) technology, Industry 4.0 and Cyber Physical Systems. Internet of Things connects an enormous number of devices. Devices within IoT need small number of sensors and control data, but with numerous messages. Today Cloud services work with the volume of these data and support large scale IoT systems. In this paper we would like to represent a comparison of solutions Industrial and Commercial IoT. The proposed systems use one of the newest communication protocols MQTT. © Springer Nature Switzerland AG 2020.

关键词： Internet of things

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Ultrasound Array Scanning for Oil-gas-water Three-phase Flow Measurement Based on Plane Wave

Ultrasound Array Scanning for Oil-gas-water Three-phase Flow...

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第三十九届中国控制会议

作者： Sheng Tian Chao Tan Feng Dong Tianjin Key Laboratory of Process Measurement and Control School of Electrical Engineering and Automation Tianjin University

In order to extract the size and distribution of discrete phases in oil-gas-water three-phase flow, a method that combines an ultrasonic array sensor with plane wave scanning is proposed and studied through numerical simulation. A frequency-domain simulation model is established. The size of the transmitting aperture that can generate plane wave is optimized from four elements to eight elements. Under the action of an ultrasonic plane wave, the curves that could express the relationship between the ultrasound attenuation coefficient（UAC） and the receiving element position of the oil bubble and gas bubble are plotted. We found that these curves have their own inherent variation rules. With transmitting aperture position shift, the UAC curve trend of the gas bubble changes significantly, but the UAC curve trend of the oil bubble has little change. The difference of oil bubble diameter will cause the UAC curve shape of the three-phase flow consistent with the curve shape of oil-water two-phase flow or gas-water two-phase flow. The relationship about the curves of the receiving element position between the variation of UAC could distinguish the spacing between the oil bubble and gas bubble. The transmitting/receiving aperture size for the three-phase flow measurement is selected as four elements/four elements or five elements/five elements, and the excitation-measurement mode is determined. This research lays a foundation for improving the accuracy of image reconstruction in the ultrasound process tomography for multiphase flow.

关键词： Ultrasound array scanning oil-gas-water three-phase flow plane wave information extraction

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3D Human Motion Prediction Based on Graph Convolution Network and Transformer

3D Human Motion Prediction Based on Graph Convolution Networ...

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Chinese automation Congress (CAC)

作者： Chaofei Gao Tian Wang Mengyi Zhang Aichun Zhu Peng Shi Hichem Snoussi School of Automation Science and Electrical Engineering Beihang University Beijing China Institute of Artificial Intelligence Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China School of Computer Science and Technology Nanjing Tech University Nanjing China School of Mathematics and Computer Science Fujian Normal University Fujian China Institute Charles Delaunay-LM2S University of Technology of Troyes Troyes France

ISBN: (纸本)9781665426480

Extracting, recognizing and predicting human actions from image information plays an essential part in the fields of human intention understanding, behavior emergency avoidance and automatic driving. In recent years, with deep learing method developing rapidly, the methods of behavior detection and intention understanding for human actions are also glowing with new vitality. In this paper, based on spatial-temporal synchronous graph convolution network and multi-head self-attention mechanism, a new method of human skeleton action recognition and prediction is proposed. By extracting the spatial features of short-term time series at the same time, we can predict the long-term time series actions, and also we have achieved satisfactory experimental results. Our experiment is based on Human3.6M dataset for training and testing. At the end of the paper, we put forward the limitations of the current research and some future research directions.

关键词： Training Three-dimensional displays Image recognition Convolution Time series analysis Feature extraction Transformers

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Transfer learning and specaugment applied to SSVEP based BCI classification

arXiv

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arXiv 2020年

作者： Bassi, Pedro R.A.S. Rampazzo, Willian Attux, Romis Department of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas UNICAMP Campinas SP13083-970 Brazil

Objective: We used deep convolutional neural networks (DCNNs) to classify electroencephalography (EEG) signals in a steady-state visually evoked potentials (SSVEP) based single-channel brain-computer interface (BCI), which does not require calibration on the user. Methods: EEG signals were converted to spectrograms and served as input to train DCNNs using the transfer learning technique. We also modified and applied a data augmentation method, SpecAugment, generally employed for speech recognition. Furthermore, for comparison purposes, we classified the SSVEP dataset using Support-vector machines (SVMs) and Filter Bank canonical correlation analysis (FBCCA). Results: Excluding the evaluated user's data from the fine-tuning process, we reached 82.2% mean test accuracy and 0.825 mean F1-Score on 35 subjects from an open dataset, using a small data length (0.5 s), only one electrode (Oz) and the DCNN with transfer learning, window slicing (WS) and SpecAugment's time masks. Conclusion: The DCNN results surpassed SVM and FBCCA performances, using a single electrode and a small data length. Transfer learning provided minimal accuracy change, but made training faster. SpecAugment created a small performance improvement and was successfully combined with WS, yielding higher accuracies. Significance: We present a new methodology to solve the problem of SSVEP classification using DCNNs. We also modified a speech recognition data augmentation technique and applied it to the context of BCIs. The presented methodology surpassed performances obtained with FBCCA and SVMs (more traditional SSVEP classification methods) in BCIs with small data lengths and one electrode. This type of BCI can be used to develop small and fast systems. © 2020, CC BY-NC-ND.

关键词： Brain computer interface

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Visuotactile Sensor Enabled Pneumatic Device Towards Compliant Oropharyngeal Swab Sampling

arXiv

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arXiv 2023年

作者： Li, Shoujie He, Mingshan Ding, Wenbo Ye, Linqi Wang, Xueqian Tan, Junbo Yuan, Jinqiu Zhang, Xiao-Ping Tsinghua Shenzhen International Graduate School Shenzhen518055 China The Department of Mechanical Engineering Seoul National University Seoul Korea Republic of The Department of Intelligent Control Qianyuan Institute of Science Hangzhou310024 China Clinical Research Center The Seventh Affiliated Hospital Sun Yat-sen University Guangdong Shenzhen518107 China The Department of Electrical Computer and Biomedical Engineering Ryerson University TorontoONM5B 2K3 Canada

Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining the visuo-tactile sensor and the pneumatic actuator-based gripper. Here, a concave visuo-tactile sensor called CoTac is first proposed to address the problems of high cost and poor reliability of traditional multi-axis force sensors. Besides, by imitating the doctor’s fingers, a soft pneumatic actuator with a rigid skeleton structure is designed, which is demonstrated to be reliable and safe via finite element modeling and experiments. Furthermore, we propose a sampling method that adopts a compliant control algorithm based on the adaptive virtual force to enhance the safety and compliance of the swab sampling process. The effectiveness of the device has been verified through sampling experiments as well as in vivo tests, indicating great application potential. The cost of the device is around 30 US dollars and the total weight of the functional part is less than 0.1 kg, allowing the device to be rapidly deployed on various robotic arms. Videos, hardware, and source code are available at: https://***/view/swab-sampling/. Copyright © 2023, The Authors. All rights reserved.

关键词： Pneumatic actuators

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Min-max fuzzy model predictive tracking control of boiler-turbine system for ultra-supercritical units

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Journal of Southeast University(English Edition) 2021年第1期37卷 42-51页

作者： Chen Chen Pan Lei Kwang Y.Lee Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast UniversityNanjing 210096China School of Energy and Environment Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering Baylor UniversityWacoTX 76798-7356USA

To improve the control performance of nonlinear ultra-supercritical(USC)thermal power units,an improved min-max fuzzy model predictive tracking control(FMPTC)strategy is ***,a T-S fuzzy model is established to approximate the dynamics of the nonlinear boiler-turbine ***,based on an extended fuzzy model containing state variables and output variables,a min-max FMPTC is derived for output regulation while ensuring the closed-loop system stability and the inputs in their given *** greater controller design freedom,the developed controller adopts a new state-and output-based objective *** addition,the observer estimation error is regarded as a bounded disturbance,ensuring the stability of the entire closed-loop control *** results on a 1000 MW USC boiler-turbine model illustrate the effectiveness of the proposed approach.

关键词： ultra-supercritical boiler-turbine system T-S model min-max model predictive control output tracking linear matrix inequality

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Recursive Weighted Null-Space Fitting Method for Identification of Multivariate Systems ⁎

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IFAC-PapersOnLine 2021年第7期54卷 345-350页

作者： Mengyuan Fang Miguel Galrinho Håkan Hjalmarsson Zhejiang Engineering Laboratory of Industrial Internet Communication Technology Zhejiang Sci-Tech University Hangzhou China. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China OHB Sweden AB Kista Sweden Centre for Advanced Bio Production and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

Recursive identification of structured multivariate models is known to be difficult due to the general non-convexity of the likelihood function. In this work, we propose a recursive multivariate weighted null-space fitting method for identification of structured multivariate models. The proposed method first uses recursive least squares to estimate a high order non-parametric model, then a parametric model is obtained through weighted least squares from the non-parametric model. In this way, the method avoids directly optimizing a non-convex likelihood function and has guaranteed global convergency. Moreover, the proposed method is flexible in model structures and has the same finite sample performance as its off-line counterpart. We use simulation examples to illustrate the performance.

关键词： Recursive system identification multivariate systems weighted null-space fitting

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Distinguishing between Fault and Inrush Current in Presence of the CT Saturation: A New Method Based on Gravity Center in Time 19

Distinguishing between Fault and Inrush Current in Presence ...

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19th IEEE International Conference on Environment and electrical engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019

作者： Bagheri, Alireza Allahbakhshi, Mehdi Samet, Haidar Tajdinian, Mohsen Seifi, Alireza Dept. of Power Control Engineering Shiraz University School of Electrical and Computer Engineering Shiraz Iran

ISBN: (纸本)9781728106526

Failure in distinguishing between the internal fault and inrush phenomena in transformer especially in the presence of saturation in current transformer, may lead to mal-operation of the differential relays. This paper introduces a novel index that distinguishes inrush current from fault current even in the presence of saturation. This index utilizes the concept of gravity center mass (GCM) on the current signal and it is called gravity center in time (GCT). GCT is defined as a point that the energy of signal before and after of GCT is equal. Utilizing the concept of GCM on current signals it can be mathematically proven the proposed algorithm based on the GCT categorizes normal operation, fault condition and inrush current from each other in one cycle. The application of GCT in discrimination of internal fault and inrush current is investigated and further demonstrated for some simulation and experimental inrush and internal fault signals. The results show that proposed method classifies the disturbances quickly with notable accuracy under different conditions. © 2019 IEEE.

关键词： Gravitation

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Path Planning of Mobile Robots based on Improved Genetic Algorithm 20

Path Planning of Mobile Robots based on Improved Genetic Alg...

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2nd International Conference on Robotics, Intelligent control and Artificial Intelligence, RICAI 2020

作者： Liu, Jia Chen, Zhikang Zhang, Yunxi Li, Weixun Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China School of Science Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781450388306

In this paper, the path planning algorithm is proposed based on the improved genetic algorithm. Firstly, the global environment for the grid model on mobile robot movement is built using the grid method. Then the classic genetic algorithm is applied into the grid map of path planning, and the gray wolf optimization algorithm is used into the grid map of path planning. Thereby, the genetic algorithm is optimized by gray wolf optimization and finally applied into path planning. The improved genetic algorithm is used into path planning of mobile robots and compared with the classic genetic algorithm and the gray wolf optimization algorithm. Finally, the simulation results confirm the improved algorithm has better convergence and effectiveness and is very valuable for path planning. © 2020 ACM.

关键词： Motion planning

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Enhancing Immunity of Full-Cycle Discrete Fourier Transform Against Decaying DC Components: A Comparative Analysis 19

Enhancing Immunity of Full-Cycle Discrete Fourier Transform ...

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19th IEEE International Conference on Environment and electrical engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019

作者： Tajdinian, Mohsen Samet, Haidar Hamedi, Alireza Hadaeghi, Arsalan Bagheri, Alireza Allahbakhshi, Mehdi Seifi, Alireza School of Electrical and Computer Engineering Shiraz University Dept. of Power and Control Engineering Shiraz Iran

ISBN: (纸本)9781728106526

Decaying DC terms of the fault current signal indisputably affect the accuracy of the discrete Fourier transform (DFT) based fundamental phasor estimators of digital relays. This effects will lead to delay in the best case and mal operation in the worst case of the protective relays and it may threat the reliability and security of the power system. This paper aims to conduct a comparative analysis between some decaying DC removal filters for enhancing the immunity if full-cycle DFT against decaying DC components. This paper mainly discusses the effects of DC offsets in the fault current and CT transient responses, harmonics and off-nominal frequency on the performance of DFT. Applying different test signals and also simulated fault current, the effectiveness of the different DC removal filters in combination with DFT is investigated. Analyzing simulation results, it is observed that the DFT phasor estimator should be provided with an algorithm that removes DC offsets due to fault current and CT transient responses under harmonic, noisy and off-nominal frequency conditions. © 2019 IEEE.

关键词： Discrete Fourier transforms

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