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2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Lin, Meihan Xu, Qimin Lu, Xuanzhao Zhang, Jinglong Chen, Cailian Shanghai Jiao Tong University Department of Automation Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Co-design of control and communication is critical to enhancing the control performance of industrial Cyber-Physical System (ICPS). However, the stochastic features of non-deterministic communication strategies in existing works limit control performance improvement. This paper proposes a centralized-control and deterministic-transmission co-design architecture for multi-subsystem ICPS over Time-Sensitive Network (TSN). Packet-wise no-wait transmission scheduling is devised to enable fine-grained scheduling for deterministic delays of the control system data. An integrated system model for the co-design architecture is constructed by integrating scheduling variables into the control system model, which enables simultaneous optimization of the control and transmission strategies for improving the feasible solution space and control performance. Co-design problem based on the integrated model is formulated as mixed-integer non-linear programming (MINLP) problem. A Tabu-search-based heuristic algorithm is proposed to obtain near-optimal solutions efficiently for the co-design problem. Simulation results demonstrate that the proposed method effectively improves control performance compared with best-effort transmission without co-design. © 2022 IEEE.

关键词： Scheduling

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A Method for Detecting the Reducers' Grease Failure Based on Vibration Signal Analysis

A Method for Detecting the Reducers' Grease Failure Based on...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Wang, Ditong Zhang, Hong Zheng, Ying Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan China Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350337754

Real time detection of the lubricating grease's effectiveness is the best method to solve wear faults, which can achieve the purpose of predictive maintenance and improve the service life of mechanical equipment. A new online detection method for gearbox lubricating grease failure is proposed to address the issues about long offline detection cycles and high labor costs associated with phased sampling analysis. Compared with online detection methods such as inductive and photoelectric, our method is difficult to detect the specific physicochemical parameters of the grease. However, it has the advantage of simple operation without touching the grease or changing the structure of the tested object. It only needs to attach the vibration sensor table to the mechanical arm reducer to measure and analyze the vibration signal. This article briefly analyzes the impact of grease failure on vibration signals, and then we introduce a novel approach that uses support vector machines along with feature extraction through wavelet packet decomposition for our detection methodology. Next transfer the commonly used spectral image recognition algorithms for temporal signal classification to achieve failed grease detection as a baseline and compare with our traditional machine learning methods. The experimental findings indicate that the recognition accuracy of both methods are above 90%, with traditional machine learning performing better on this task. © 2023 IEEE.

关键词： Support vector machines

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Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1766-1768页

作者： Zhongbo Sun Shijun Tang Jiliang Zhang Junzhi Yu the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE College of Information Science and Engineering Northeastern UniversityShenyang 110819China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t... 详细信息

关键词： directional programming hardware

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Multi-octave two-color soliton frequency comb in integrated chalcogenide microresonators

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Frontiers of Optoelectronics 2024年第4期17卷 91-104页

作者： Huanjie Cheng Guosheng Lin Di Xia Liyang Luo Siqi Lu Changyuan Yu Bin Zhang Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electrical and Information TechnologySun Yat-sen UniversityGuangzhou 510275China Photonics Research Center Department of Electronic and Information EngineeringThe Hong Kong Polytechnic UniversityKowloonHong KongChina

Mid-infrared(MIR)Kerr microcombs are of significant interest for portable dual-comb spectroscopy and precision molecular sensing due to strong molecular vibrational absorption in the MIR ***,achieving a compact,octave-spanning MIR Kerr microcomb remains a challenge due to the lack of suitable MIR photonic materials for the core and cladding of integrated devices and appropriate MIR continuous-wave(CW)pump ***,we propose a novel slot concentric dual-ring(SCDR)microresonator based on an integrated chalcogenide glass chip,which offers excellent transmission performance and flexible dispersion engineering in the MIR *** device achieves both phase-matching and group velocity matching in two separated anomalous dispersion regions,enabling phase-locked,two-color solitons in the MIR region with a commercial 2-μm CW laser as the pump ***,the spectral locking of the two-color soliton enhances pump wavelength selectivity,providing precise control over soliton *** leveraging the dispersion characteristics of the SCDR microresonator,we have demonstrated a multi-octave-spanning,two-color soliton microcomb,covering a spectral range from 1156.07 to 5054.95 nm(200 THz)at a-40 dB level,highlighting the versatility and broad applicability of our *** the proposed multi-octave MIR frequency comb is relevant for applications such as dual-comb spectroscopy and trace-gas sensing.

关键词： Mid-infrared Kerr microcombs Two-color soliton Multi-octave Chalcogenide glasses

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Simulation analysis of erosion characteristics of slurry pipelines based on CFD-DDPM pipeline parameters 43

Simulation analysis of erosion characteristics of slurry pip...

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43rd Chinese control Conference, CCC 2024

作者： Yuan, Haoran Wu, Jiande Xiong, Xin Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan Kunming650500 China Kunming University of Science and Technology Faculty of Information Engineering and Automation Yunnan Kunming650500 China Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Yunnan Kunming650500 China

ISBN: (纸本)9789887581581

In order to explore the impact of pipe diameter, bend-diameter ratio and bend angle on the erosion of slurry pipe, a numerical simulation method approach grounded in Computational Fluid Dynamics - Dense Discrete Phase Model (CFD-DDPM) is proposed. Firstly, the geometric models of bends with different pipe diameters, bend-diameter ratios, and bend angles are constructed;secondly, the slurry pipe erosion model based on Dense Discrete Phase Model (DDPM) is constructed;then, model validation is conducted on the slurry pipe erosion model to affirm the accuracy of the model;finally, the computational fluid dynamics method is employed to simulate the erosion and wear behavior of the pipeline, to investigate the impact of pipe diameter, bend-diameter ratio and bend angle on the erosion and wear of the slurry pipeline. At the same time, gray correlation analysis was also used to analyze the significant relationship between the three pipeline factors and erosion and wear. The results show that the main erosion area is not determined, with the change of the pipeline parameters, the most serious erosion area will move;the effect of different pipeline parameter variations on the erosion rate is different, in which the pipe diameter of the largest impact, the second largest bend-diameter ratio, the smallest impact of the bend angle. Therefore, in the design of slurry pipeline, should first consider the influence of pipe diameter factors. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Slurry pipelines

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Knowledge-Based Scene Text Recognition for Industrial Applications

Knowledge-Based Scene Text Recognition for Industrial Applic...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Deng, Guowei Tu, Jingzheng Chen, Cailian He, Jianping Le, Xinyi Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China 200240 Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai China 200240

ISBN: (纸本)9781728119489

Scene text recognition (STR) methods combined with semantic information have made great progress to recognize texts in natural scenes, most of which are daily words. However, research on mining semantic information in industrial texts attracts less attention. Since industrial texts follow a different semantic pattern defined by industry standards, it challenges many existing methods to conduct accurate semantic reasoning. In this paper, we abstract the industry standards into two aspects of prior knowledge: the grouping property and the prior lexicon. Correspondingly, a knowledge-based language model is proposed with several group-wise correlation modules and a lexicon-based reasoning module to learn semantic rules from both data and the prior knowledge. Besides, we transfer the prior knowledge into data by generating synthetic pure text datasets according to the industry standards' rules, which introduces more prior knowledge to the language model. Furthermore, a novel STR framework is presented by combining the knowledge-based language model and an attention-based vision model. For evaluation, two industrial text datasets called CIN and SB are collected from real-world industrial field surveillance. Experiments indicate that our method's word-level accuracy outperforms state-of-the-art methods with 15% and 10.61% on CIN and SB datasets respectively. © 2022 IEEE.

关键词： Knowledge based systems

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A Multi-scale Framework for Out-of-Distribution Detection in Dermoscopic Images 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Huang, Zhongzheng Wang, Tao Cai, Yuanzheng Liang, Lingyu College of Computer and Data Science Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering and International Digital Economy College Minjiang University Fuzhou350108 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Wuyishan354300 China Fujian Yilian-Health Nursing Information Technology Co. Ltd. Fuzhou350003 China School of Electronic and Information Engineering South China University of Technology Guangzhou510641 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The automatic detection of skin diseases via dermoscopic images can improve the efficiency in diagnosis and help doctors make more accurate judgments. However, conventional skin disease recognition systems may produce high confidence for out-of-distribution (OOD) data, which may become a major security vulnerability in practical applications. In this paper, we propose a multi-scale detection framework to detect out-of-distribution skin disease image data to ensure the robustness of the system. Our framework extracts features from different layers of the neural network. In the early layers, rectified activation is used to make the output features closer to the well-behaved distribution, and then an one-class SVM is trained to detect OOD data;in the penultimate layer, an adapted Gram matrix is used to calculate the features after rectified activation, and finally the layer with the best performance is chosen to compute a normality score. Experiments show that the proposed framework achieves superior performance when compared with other state-of-the-art methods in the task of skin disease recognition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Chemical activation

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Automatic Recognition of Whale and Dolphin Whistles Based on Visual Feature Extraction Approach 2

Automatic Recognition of Whale and Dolphin Whistles Based on...

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2nd IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2022

作者： Wu, Wei Feng, Huibin Junejo, Naveed Ur Rehman Qiu, Yuquan Yan, Jiaquan College of Computer and Control Engineering Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China University of Lahore Department of Computer Engineering Lahore Pakistan

ISBN: (纸本)9781665442763

Automatic recognition of marine mammals plays a significant role in the protection of endangered marine species, generally utilizing their vocalizations. In this paper, we propose a novel visual feature extraction approach for whale and dolphin signals incorporating variational mode decomposition (VMD) and Hilbert transform (VMD-HT) to construct the high-resolution time-frequency signatures and using gray level co-occurrence matrix (GLCM) to extort image features. Firstly, the objected signals are decomposed by VMD algorithm into multiple intrinsic mode functions (IMFs), which can capture local frequency features precisely. Secondly, the time-frequency signature of the objected signal with high resolution is constructed by linear superposition operation of each IMF time-frequency image depicted through Hilbert transform (HT). Thirdly, the image features are extracted using GLCM. Eventually, support vector machine (SVM) is adopted to validate the classification performance of the proposed method. The experimental results verify that the resolution improvement of time-frequency image attains the correct recognition rate and the proposed method accuracy is higher than the compared method about 11.11% © 2022 IEEE.

关键词： Variational mode decomposition

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Data-driven Fault Diagnosis Method Based on Fusion of Multi-direction and Multi-source Signals 5

Data-driven Fault Diagnosis Method Based on Fusion of Multi-...

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5th International Conference on Intelligent Autonomous systems, ICoIAS 2022

作者： Yang, Yang Wang, Junda Li, Ning Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

As a pivotal mechanical component of turbine drive-chain, gearbox suffers from various accidents and fault diagnosis could remarkably enhance its reliability and maintain running safety and lifetime. Vibration-based analysis on single-channel is mainly adopted in previous diagnostic, which cannot catch full vibration inner information in gearbox sensors and bring model performance down. In this paper, a novel method based on the fusion of multi-direction and multi-source signals and the convolutional neural network (MDMS-CNN) is presented. This method can obtain multi-dimensional feature maps from MDMS and preserve the time correlation among different signal sequences. First, features from MDMS are extracted via a corrosion conversion method that converts signals into two-dimensional (2-D) gray images. Then, homologous images are spliced into same channels, while heterogeneous images are superimposed to different channels. Finally, fusion features are input into CNN for fault classification. In experiments, the method is validated on a gearbox diagnosis case. Results have shown that the proposed method achieves 99.86% recognition accuracy and faster convergence speed compared to others. © 2022 IEEE.

关键词： Failure analysis

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