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Chinese automation Congress (CAC)

作者： Y. Z. Long Y. W. Jian Z. T. Liu School of Automation China University of Geosciences WuHan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems WuHan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

As a supporting technology in the field of human-computer interaction, speaker localization method has been a research hotspot in recent years. However, the existing single-mode speaker location methods cannot meet the requirements of stability and rapidity. For improve the accuracy and effective positioning range of speaker localization system, a multi-modal panoramic speaker localization method is proposed in this paper. Firstly, the coarse position of the speaker was preliminarily obtained by sound source localization. Then, according to the initial positioning of the speaker, whether the image used for face recognition need to be stitched is decided. What’s more, the position of speaker is calculated by face detection and calibration. Finally, the results of voice and image localization are fused by coordinate transformation. The proposal is tested on self-built experimental system, and the experimental results prove the effectiveness of the proposed method.

关键词： Location awareness Image resolution Image edge detection Face recognition Standardization Cameras Robustness

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A fault diagnosis method based on multi-feature fusion and broad learning system

A fault diagnosis method based on multi-feature fusion and b...

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

作者： Yan Wang Wenkai Hu Weihua Cao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665401166

Reliable fault diagnosis is of practical significance for process safety in modern industrial facilities. This article proposes a data-driven fault diagnosis method based on multi-feature fusion and broad learning. The contributions are twofold: First, a systematic multi-feature extraction approach is presented to extract long-term trend features, short-term trend features, and binary-valued alarm signals; second, a broad learning system based fault diagnosis method is proposed to diagnose faults based on multi-feature fusion and to update the diagnosis model in an incremental manner. The proposed method has a strong nonlinear modeling capability and can also update the diagnosis model incrementally when unseen fault types are detected. The efficacy of the proposed method is demonstrated by simulations with the benchmark Tennessee Eastman (TE) process.

关键词： Fault diagnosis Learning systems Systematics Fault detection Data preprocessing Benchmark testing Feature extraction

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Identification of root cause alarms by detecting correlations and time delays between alarm variables

Identification of root cause alarms by detecting correlation...

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Chinese automation Congress (CAC)

作者： Xin Cheng Wenkai Hu Weihua Cao Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Under an abnormal situation in process operations, it is important to find out the root cause, so as to bring the system back to normal timely. In a typical modern industrial facility, there are configured a large number of alarms. Usually, the presence and propagation of a fault may lead to a series of alarms, which hold certain correlations. Therefore, analyzing alarm correlations can help to track the prorogation of faults among alarm variables and thus find out the root cause. This paper proposes a systematic alarm root cause analysis method based on the detection of correlations and time delays between alarm variables. First, two types of alarm correlations based on time stamps of alarm events are defined and the calculation methods are provided. Then, alarms are determined to be correlated or not by comparing with designed thresholds. Last, a causal matrix is formed to present the causal relations between alarms based on the directions of time delays. The effectiveness of the proposed method is demonstrated by both a numerical example and the benchmark Tennessee Eastman model.

关键词： Root cause analysis Correlation Systematics automation Delay effects Benchmark testing Industrial facilities

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A tuning strategy for microwave filter using variable universe adaptive fuzzy logic system

A tuning strategy for microwave filter using variable univer...

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Chinese automation Congress (CAC)

作者： Sai Peng Weihua Cao Leyu Bi Yan Yuan Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Microwave filters are the core frequency selection device in 5G base station, which play an important role in the field of communication. The errors of design and processing of microwave filter make it difficult to meet the specific requirements of frequency selection, thus the tuning process before delivery is significant. However, the tuning process relies heavily on skilled workers, resulting in low tuning efficiency and high cost. The automatic tuning method based on fuzzy logic does not depend on the model and has strong applicability. It has great practical value to the production trend of multi-variety, small batch and customization of microwave filters. In this paper, a variable universe adaptive fuzzy tuning method is proposed. First, intelligent optimal contraction-expansion factors based on fuzzy inference are proposed according to expert knowledge. Then, the input universe and output universe are multiplied, and the initial rule is transformed into more effective new rules through the transformation which is adaptive to the variable universe. Last, the effectiveness of the proposed tuning method is verified by simulations.

关键词： Fuzzy logic Adaptation models Adaptive systems Design methodology Production Microwave communication Microwave theory and techniques

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Large, complex, and Realistic Safety Clothing and Helmet Detection: Dataset and Method

arXiv

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arXiv 2023年

作者： Yu, Fusheng Li, Jiang Wang, Xiaoping Wu, Shaojin Zhang, Junjie Zeng, Zhigang The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Institute of Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China The Hubei Key Laboratory of Brain-Inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Detecting safety clothing and helmets is paramount for ensuring the safety of construction workers. However, the development of deep learning models in this domain has been impeded by the scarcity of high-quality datasets. In this study, we construct a large, complex, and realistic safety clothing and helmet detection (SFCHD) dataset. SFCHD is derived from two authentic chemical plants, comprising 12,373 images, 7 categories, and 50,552 annotations. We partition the SFCHD dataset into training and testing sets with a ratio of 4:1 and validate its utility by applying several classic object detection algorithms. Furthermore, drawing inspiration from spatial and channel attention mechanisms, we design a spatial and channel attention-based low-light enhancement (SCALE) module. SCALE is a plug-and-play component with a high degree of flexibility. Extensive evaluations of the SCALE module on both the ExDark and SFCHD datasets have empirically demonstrated its efficacy in enhancing the performance of detectors under low-light conditions. The dataset and code are publicly available at https://***/lijfrankopen/SFCHD-SCALE. Copyright © 2023, The Authors. All rights reserved.

关键词： Chemical plants

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Psychological Resistance Recognition Based on Acoustic Features Extraction

Psychological Resistance Recognition Based on Acoustic Featu...

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Chinese automation Congress (CAC)

作者： Z. Lv Z. T Liu M. T. Han B. H. Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665426480

Psychological resistance can express the change of the client's psychological state, which is considered to be an important factor affecting psychological counseling. This paper proposed a method of psychological resistance recognition based on acoustic features extraction. The method includes three main steps, i.e., statistical acoustic feature extraction, feature selection, and classification. Our method uses statistical acoustic features to express psychological resistance, and analyzes the application value of high correlation features obtained from feature selection in the recognition of different psychological resistance. This method can be used to determine the high correlation features of psychological resistance adaptively, and avoid the deficiency of subjective judgment. A speech database of psychological resistance is built for research needs, in which three psychological consultants and four subjects are involved in psychological counseling with 1200 sentences in speech. The experimental results verified the effectiveness of our method.

关键词： Resistance Employee welfare Correlation automation Databases Psychology Feature extraction

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Distributed Leader-Following Impulsive Consensus of Nonlinear Multi-Agent systems with Partial Input Saturation

Distributed Leader-Following Impulsive Consensus of Nonlinea...

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Chinese automation Congress (CAC)

作者： Jiejie Lan Xiaowei Jiang Xianhe Zhang Le You School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing P. R. China School of Electrical Engineering and Automation Hubei Normal University Huangshi P. R. China

In this letter, leader-following consensus of a nonlinear MASs satisfying Lipschitz conditions with partial actuator saturation constraints is investigated First of all, an impulse control protocol which only requires local information of agents and their neighbors is proposed. Then, using Lyapunov stability theory, impulse control theory, and algebraic graph theory, sufficient conditions for the consensus of multi-agent systems are provided. Ultimately, numerical simulations are employed to show that the research findings are accurate.

关键词： Actuators Sufficient conditions Energy consumption Protocols Energy conservation Numerical simulation control systems

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Recursive estimation with compensation strategies under random access protocol and deception attacks

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IEEE Transactions on Signal Processing 2025年 73卷 1954-1965页

作者： Li, Jiaxing Caballero-Aguila, Raquel Hu, Jun Linares-Perez, Josefa Harbin University of Science and Technology Department of Applied Mathematics Harbin150080 China University of Jaén Department of Statistics and Operations Research Jaén23071 Spain Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China Harbin University of Science and Technology School of Automation Harbin150080 China University of Granada Department of Statistics and Operations Research Granada18071 Spain

In this paper, recursive least-squares linear estimation algorithms are proposed for stochastic systems influenced by uniform quantization, random access protocol (RAP) and deception attacks. With the purpose of enhancing communication efficiency and reducing unnecessary data collisions, RAP is adopted to schedule data signal transmissions that are also subject to deception attacks. In order to alleviate the side effect of missing information caused by RAP, three compensation strategies (zero-input, zero-order hold and prediction-compensation) are utilized. By resorting to an innovation method, covariance-based filters are designed and then fixed-point smoothers are obtained in light of available observations. Finally, a simulation experiment with comparisons is employed to demonstrate the effectiveness of the developed recursive estimation schemes, where the influence of attack probabilities on estimation accuracy is evaluated. © 1991-2012 IEEE.

关键词： Least squares approximations

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Social manufacturing pattern in the intelligent reform of the shoes and clothing industry 1

Social manufacturing pattern in the intelligent reform of th...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Cao, Yansong Wang, Yutong Dai, Juwu Zhu, Xihao Wang, Fei-Yue Macau Institute of Systems Engineering Macau University of Science and Technology China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Ningbo Sanbody Intelligent Technology Co. LTD Ningbo China University of Nottingham Faculty of Science and Engineering Ningbo China

ISBN: (纸本)9781665433372

Along with economic globalization, the shoes and clothing market is undergoing huge changes and is facing increasing individualized demands. To realize personalized customization, we propose a social manufacturing pattern for the shoes and clothing industry. On the customer side, we collect costumer information with the help of 3D scanning and virtual fitting. On the production side, we replace human labor with intelligent production equipment. On the enterprise management side, we construct a cloud platform to realize source maximization. Through this social manufacturing pattern, we expect to accelerate the intelligent reform of the shoes and clothing industry. © 2021 IEEE.

关键词： Shoe manufacture

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Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 237-249页

作者： Zhibin HU Jun HU Cai CHEN Hongjian LIU Xiaojian YI Department of Applied Mathematics Harbin University of Science and TechnologyHarbin150080China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and TechnologyHarbin150080China School of Automation Harbin University of Science and TechnologyHarbin150080China School of Mathematics and Physics Anhui Polytechnic UniversityWuhu241000China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314003China Tangshan Research Institute Beijing Institute of TechnologyTangshan063099China

This paper investigates the problem of outlier-resistant distributed fusion filtering(DFF)for a class of multi-sensor nonlinear singular systems(MSNSSs)under a dynamic event-triggered scheme(DETS).To relieve the effect of measurement outliers in data transmission,a self-adaptive saturation function is ***,to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization,a DETS is adopted to regulate the frequency of data *** the addressed MSNSSs,our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS;the local upper bound(UB)on the filtering error covariance(FEC)is derived by solving the difference equations and minimized by designing proper filter ***,according to the local filters and their UBs,a DFF algorithm is presented in terms of the inverse covariance intersection fusion *** such,the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers,thereby improving the estimation ***,the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is ***,the validity of the developed algorithm is checked using a simulation example.

关键词： Distributed fusion filtering Multi-sensor nonlinear singular systems Dynamic event-triggered scheme Outlier-resistant filter Uniform boundedness

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