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IEEE International Conference on Automation Science and engineering (CASE)

作者： Qihang Fang Gang Xiong Xiuqin Shang Sheng Liu Bin Hu Zhen Shen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Fault diagnosis is a vital technique to pinpoint the machine malfunctions in manufacturing systems. In recent years, the deep learning techniques greatly improve the fault detection accuracy, but there still remain some problems. If one fault is absent in the training data or the fault signal is disturbed by severe noise interference, the fault classifier may misjudge the health state. This problem limits the reliability of the fault diagnosis in real applications. In this paper, we enhance the fault diagnosis method by using Bayesian Convolutional Neural Network (BCNN). A Shannon entropy-based method is presented to quantify the prediction uncertainty. The BCNN turns the deterministic predictions to probabilistic distributions and enhances the robustness of the fault diagnosis. The uncertainty quantification method helps to indicate the wrong predictions, detect unknown faults, and discover the strong disturbances. Then, a fine-tuning strategy is applied to enhance the model performance further. The potential usability of the proposed method in monitoring the motors of 3D printers is studied. And the experiment is conducted on a motor bearing dataset provided by Case Western Reserve University. The proposed BCNN achieves 99.82% fault classification accuracy over nine health conditions. Its robustness is verified by comparing the testing accuracy with three other methods on the noisy datasets. And the uncertainty quantification method successfully detects the outlier inputs.

关键词： Fault diagnosis Uncertainty Bayes methods Circuit faults Robustness Predictive models Noise measurement

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Mathematical modeling of the synthesis process of vinyl acetate 5

Mathematical modeling of the synthesis process of vinyl acet...

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5th International Scientific and Practical Conference on Virtual Simulation, Prototyping and Industrial Design 2018, VSPID 2018

作者： Arapov, D. Tikhomirov, S. Podvalny, S. Denisenko, V. Avcinov, I. Higher Mathematics and Information Technology Voronezh State University of Engineering Technologies 19 Revolution Avenue Voronezh394036 Russia Information and Control Systems Voronezh State University of Engineering Technologies 19 Revolution Avenue Voronezh394036 Russia Head of the Department of Automated and Computing Systems Voronezh State Technical University 14 Moskovsky Avenue Voronezh394026 Russia

A complete mathematical modeling of the technological process of manufacturing vinyl acetate monomer by vapor-phase method has been implemented. The model is partial differential equations of the material and energy balance and catalyst aging. An algorithm for an integrated equation based on the second-order Gregg-Bulirsh-Shter rectangle symbol has been developed. The error in modeling the process is equal (CH3COOCH=CH2) ± 5.4% rel. for the target matter, and (CO2) ± 6.4% rel. for the secondary substance The kinetic coefficients of differential equations, namely the pre-exponential factors and the activation energy have been refined. The obtained data of the modeling of the vapor-phase manufacturing process of vinyl acetate are shown in the form of tables and graphic three-dimensional dependencies of quality indicators on technological parameters. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Activation energy

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COVID-19 detection in CT images with deep learning: A voting-based scheme and cross-datasets analysis

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Informatics in Medicine Unlocked 2020年 20卷 100427页

作者： Silva, Pedro Luz, Eduardo Silva, Guilherme Moreira, Gladston Silva, Rodrigo Lucio, Diego Menotti, David Computing Department Universidade Federal de Ouro Preto (UFOP) MG Brazil Department of Control and Automation Engineering Universidade Federal de Ouro Preto (UFOP) MG Brazil Department of Informatics Universidade Federal do Parana (UFPR) PR Brazil

Early detection and diagnosis are critical factors to control the COVID-19 spreading. A number of deep learning-based methodologies have been recently proposed for COVID-19 screening in CT scans as a tool to automate and help with the diagnosis. These approaches, however, suffer from at least one of the following problems: (i) they treat each CT scan slice independently and (ii) the methods are trained and tested with sets of images from the same dataset. Treating the slices independently means that the same patient may appear in the training and test sets at the same time which may produce misleading results. It also raises the question of whether the scans from the same patient should be evaluated as a group or not. Moreover, using a single dataset raises concerns about the generalization of the methods. Different datasets tend to present images of varying quality which may come from different types of CT machines reflecting the conditions of the countries and cities from where they come from. In order to address these two problems, in this work, we propose an Efficient Deep Learning Technique for the screening of COVID-19 with a voting-based approach. In this approach, the images from a given patient are classified as group in a voting system. The approach is tested in the two biggest datasets of COVID-19 CT analysis with a patient-based split. A cross dataset study is also presented to assess the robustness of the models in a more realistic scenario in which data comes from different distributions. The cross-dataset analysis has shown that the generalization power of deep learning models is far from acceptable for the task since accuracy drops from 87.68% to 56.16% on the best evaluation scenario. These results highlighted that the methods that aim at COVID-19 detection in CT-images have to improve significantly to be considered as a clinical option and larger and more diverse datasets are needed to evaluate the methods in a realistic scenario. © 2020 The Author

关键词： Chest radiography COVID-19 Deep learning EfficientNet Pneumonia

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Integrate and Fire Neuron Implementation using CMOS Predictive Technology Model for 32nm

Integrate and Fire Neuron Implementation using CMOS Predicti...

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Microelectronics Technology and Devices (SBMicro)

作者： Gabriel Maranhão Janaina G. Guimarães Department of Electrical Engineering Universidade de Brasília Brasília Brazil Department of Control Automation and Computing Engineering Universidade Federal de Santa Catarina Blumenau Brazil

The propose of this work is to evolve the studies on neuromorphic circuits by simulating transistors models that look the most with the ones used in commercial process. Since most of data about company models contain a restricted access, some universities provide predictions models to reproduce the real ones. In this paper we present a silicon analog integrate and fire neuron (I&F), proposed by G. Indiveri as a part of a neuromorphic device. Using 32nm CMOS technology simulated in LTspice with BSIM4v4 and applying predictive parameters provides by Predictive Technology Model (PTM), we were able to reduce the source power, to 0.9V, and chip size of the latest design which was implemented using a 180nm CMOS process at 1.8 power supply.

关键词： Neurons Predictive models Logic gates Semiconductor device modeling Transistors Mathematical model Computational modeling

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Binary stochastic filtering: A method for Neural network size minimization and supervised feature selection

arXiv

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arXiv 2019年

作者： Trelin, A. Procházka, A. Department of Solid State Engineering University of Chemistry and Technology Prague16628 Czech Republic Department of Computing and Control Engineering University of Chemistry and Technology Prague16628 Czech Republic

Binary Stochastic Filtering (BSF), the algorithm for feature selection and neuron pruning is proposed in this work. The method defines filtering layer which penalizes amount of the information involved in the training process. This information could be the input data or output of the previous layer, which directly lead to the feature selection or neuron pruning respectively, producing ad hoc subset of features or selecting optimal number of neurons in each layer. Filtering layer stochastically passes or drops features based on individual weights, which are tuned with standard backpropagation algorithm during the training process. Multifold decrease of neural network size has been achieved in the experiments. Besides, the method was able to select minimal number of features, surpassing literature references by the accuracy/dimensionality ratio. Ready-to-use implementation of the BSF layer is provided. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Weak Signal Detection with Duffing Oscillator Based on Circular Boundary Counting Method and STFT State Identification Parameter

Weak Signal Detection with Duffing Oscillator Based on Circu...

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2019 2nd International Conference on Electrical and Electronic engineering（EEE 2019）

作者： Zhi-qiang ZHU Rui-li JIA Xiao-peng YAN Ke WANG Jian HOU Science and Technology on Electromechanical Dynamic Control Laboratory School of Mechatronical Engineering Beijing Institute of Technology Beijing Jinghang Research Institute of Computing and Communication

To solve the problem of quantitative identification of the state of Duffing oscillator and determination of the critical threshold of reference amplitude, a combined weak signal detection method is proposed in this paper. The STFT statistical characteristics of Duffing oscillator in chaotic state, intermittent state and large-scale periodic state is analyzed and based on it the state identification parameter is selected to quantitatively present the state of Duffing oscillator. The step change of the number of the phase points on the boundary of circular regions in the phase plane is shown and the circular boundary counting method is proposed to determine the critical threshold. Based on above research, the algorithm of the combined weak signal detection is given, which uses Runge-Kutta algorithm to calculate the Duffing system. Simulation results show that this combined method is not only accurate at low SNR, but also robust when noise condition is variable.

关键词： Weak signal detection Duffing oscillator Circular boundary counting method State identification Determining critical value

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Disorder-induced pronounced magnetoresistive hysteresis in Josephson junctions

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Physical Review B 2025年第13期111卷 134513-134513页

作者： Yu Wu Daiqiang Huang Huanyu Zhang Anita Guarino Rosalba Fittipaldi Chao Ma Wenjie Hu Chang Niu Zhen Wang Weichao Yu Yuriy Yerin Antonio Vecchione Yang Liu Mario Cuoco Hangwen Guo Jian Shen State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai 200433 People's Republic of China Department of Physics Fudan University Shanghai 200433 People's Republic of China Shanghai Aerospace Control Technology Institute Shanghai 201109 People's Republic of China International Center for Quantum Materials Peking University Beijing 100871 People's Republic of China CNR-SPIN c/o Universitá di Salerno I-84084 Fisciano (SA) Italy College of Materials Science and Engineering Hunan University Changsha 410082 People's Republic of China Department of Physics University of Science and Technology of China Hefei Anhui 230026 Peoples Republic of China CNR-SPIN via del Fosso del Cavaliere 100 00133 Roma Italy Hefei National Laboratory Hefei 230088 People's Republic of China Zhangjiang Fudan International Innovation Center Fudan University Shanghai 201210 People's Republic of China Shanghai Research Center for Quantum Sciences Shanghai 201315 People's Republic of China Collaborative Innovation Center of Advanced Microstructures Nanjing 210093 People's Republic of China

The relation between superconductivity and time-reversal symmetry is one of the most fascinating problems in condensed-matter physics. Here we report an anomalous transport behavior in superconducting Josephson junctions induced by surface disorder. We fabricate vertical Josephson junctions using metallic superconductor (Al) and ion-bombarded Sr2RuO4. Below the superconducting transition temperature, we observe persistent magnetoresistive hysteresis behavior dependent on the disorder deposition time. Field- and temperature-dependent measurements suggest that the observed effects arise from disorder-induced anomalous flux in Sr2RuO4 which can be sensitively detected by superconducting Al. To account for the observed findings, we consider different physical scenarios such as interband surface pairing reconstruction, magnetic surface states, and vortex phases.

关键词： Hysteresis

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Formation-containment control for general linear multi-agent systems with time-varying delays and switching topologies

Formation-containment control for general linear multi-agent...

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International Conference on control and Automation (ICCA)

作者： Shiyu Zhou Yongzhao Hua Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China University of Bristol Bristol United Kingdom Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P.R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

Formation-containment control problems for general linear multi-agent systems with time-varying delays and switching topologies are studied. The leaders are required to accomplish a given time-varying formation and the followers are allowed to enter the convex envelope spanned by those of the leaders simultaneously. Firstly, formation-containment protocols based on distributed state observer with switching interaction topologies and time-varying delays are presented for leaders and followers respectively, where an edge-based state observer is presented for each follower to estimate the whole states of all the leaders under the influences of switching interaction topologies and time-varying delays. Then, formation- containment problems are transformed into asymptotic stability problems. Furthermore, an algorithm to determine the gain matrices in the protocols is given based on linear matrix inequality technique and common Lyapunov-Krasovskii stability theory. Sufficient conditions for multi-agent systems to achieve formation-containment under the designed protocol are proposed. Finally, numerical simulations are provided to demonstrate theoretical results.

关键词： Switches Delays control systems Topology Protocols Symmetric matrices Time-varying systems

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Satellites of the Broucke-Hadjidemetriou-Hénon family of periodic unequal-mass three-body orbits

arXiv

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arXiv 2020年

作者： Li, Xiaoming Liao, Shijun MOE Key Laboratory of Disaster Forecast and Control in Engineering School of Mechanics and Construction Engineering Jinan University Guangzhou510632 China Department of Earth Atmospheric and Planetary Sciences Massachusetts Institute of Technology CambridgeMA02139 United States School of Physics and Astronomy Shanghai Jiaotong University Shanghai200240 China Center of Advanced Computing School of Naval Architecture Ocean and Civil Engineering Shanghai Jiaotong University Shanghai200240 China

The Broucke-Hadjidemetriou-Hénon’s (BHH) orbits are a family of periodic orbits of the three-body system with the simplest topological free group word a, while the BHH satellites have free group words ak (k > 1), where k is the topological exponent. Janković and Dmitrašinović [Phy. Rev. Lett. 116, 064301 (2016)] reported 57 new BHH satellites with equal mass and found that at a fixed energy the relationship between the angular momentum (L) and the topologically rescaled period (T/k) is the same for both of the BHH orbits (k = 1) and the BHH satellites (k > 1). In this letter, we report 419,743 new BHH orbits (k = 1) and 179,253 new BHH satellites (k > 1) of the three-body system with unequal mass, which have never been reported, to the best of our knowledge. Among these newly-found 598,996 BBH orbits and satellites, about 33.5% (i.e., 200,686) are linearly stable and thus many among them might be observed in practice. Besides, we discover that, for the three-body system with unequal mass at a fixed energy, relationship between the angular momentum (L) and topologically rescaled period (T/k) of the BHH satellites (k > 1) is different from that of the BHH orbits (k = 1). Copyright © 2020, The Authors. All rights reserved.

关键词： Satellites

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Periodic satellite orbits of the Broucke-Hadjidemetriou-Hénon family of three-body system with unequal masses

Research Square

引用

Research Square 2020年

作者： Li, Xiaoming Liao, Shijun Department of Earth Atmospheric and Planetary Sciences Massachusetts Institute of Technology CambridgeMA02139 United States MOE Key Laboratory of Disaster Forecast and Control in Engineering School of Mechanics and Construction Engineering Jinan University Guangzhou510632 China School of Physics and Astronomy Shanghai Jiaotong University Shanghai200240 China Center of Advanced Computing School of Naval Architecture Ocean and Civil Engineering Shanghai Jiaotong University Shanghai200240 China

Triple systems are common and key objects in astronomy. The three-body problem has received much more attention in recent years1–3. All observed periodic triple stars systems4–6 belong to the Broucke-Hadjidemetriou-Hénon’s (BHH) family7–9. The BHH orbits are a family of periodic orbits of the three-body system with the simplest topological free group word10 a, while Janković and Dmitrašinović 1 gained 58 equal-mass BHH satellite orbits which have free group words ak (k > 1), where k is the topological exponent. However, the BHH satellite orbits with equal mass is lack of realistic meaning because they do not exist in practice. Here we present 419743 new BHH orbits and 179253 new BHH satellites (k > 1) for three-body system with unequal mass. Especially, 48761 among the 179253 new BHH satellites are stable and have unequal masses. It suggests that these 48761 stable BHH satellites could be found by the observation. Besides, for the three-body system with equal mass at a fixed energy, it was demonstrated that the relationship between the angular momentum (L) and topological scaled period (T/k) of the BHH satellites is the same as that of the BHH orbits1. However, we found that this does not hold for the three-body system with unequal mass. Our findings have broad impact for the astrophysical scenario: they could inspire the theoretical and observational study of the triple system, the formation of triple stars11, the gravitational waves pattern12 and the gravitational waves observation13 of the triple system. © 2020, CC BY.

关键词： Satellites

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