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2024 International Conference on measurement, communication, and Virtual Reality, MCVR 2024

作者： Han, Chuang Gao, Mengran Heilongjiang Province Laboratory of Laser Spectroscopy Technology Application Harbin University of Science and Technology Harbin China School of Measurement-Control Technology and Communication Engineering Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781510691773

This paper combines the L-shaped array and two parallel linear arrays to propose an N-shape array configuration. For the N-shape array, the multiple signal classification (MUSIC) algorithm is utilized for DOA estimation under far-field conditions. When the signal source is in the far-field region, the signal arriving at the array elements can typically be represented as a plane wave. By utilizing the array manifold matrices of the L-shaped array and two parallel linear arrays, the array manifold matrix for the N-shape array is derived, which is then used for DOA estimation via the MUSIC algorithm. Simulation results indicate that the N-shape array can effectively achieve DOA estimation of signals in far-field conditions using the MUSIC algorithm. © 2025 SPIE.

关键词： Matrix algebra

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Edge Node Cooperation and Resource Sharing in Mobile Edge Computing 15

Edge Node Cooperation and Resource Sharing in Mobile Edge Co...

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15th IEEE International Conference on Wireless communications and Signal Processing, WCSP 2023

作者： Meng, Anqi Gao, Xiaozheng Huang, Yuting Xu, Zhan Shang, Jiadong Ministry of Education Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Beijing China Ministry of Information Industry Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Beijing China Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (纸本)9798350324662

As edge computing undergoes ongoing development propelled by the advancements in Internet of Things and mobile communication technologies, the issue of edge node cooperation and resource sharing needs to be investigated. In this paper, the issue of edge node cooperation and resource sharing is modeled as a two-layer framework. In the lower layer, a heuristic matching algorithm between users and edge nodes is developed, and a resource sharing algorithm among edge nodes in the same coalition is proposed. In the upper layer, a coalition formation algorithm is designed based on the coalition game. Simulation results show that the proposed algorithms reduce the network cost effectively compared with non-cooperative scheme. © 2023 IEEE.

关键词： coalition game mobile edge computing resource sharing

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Hand medical monitoring system based on machine learning and optimal EMG feature set

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Personal and Ubiquitous Computing 2023年第6期27卷 1991-2007页

作者： Yu, Mingchao Li, Gongfa Jiang, Du Jiang, Guozhang Tao, Bo Chen, Disi Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

Considering that serious hand function damage will greatly affect the daily life of patients, its recovery mainly depends on the regular inspection and manual training of medical staff, and medical monitoring based on bioelectric signals can largely replace manual re-examination as autonomous rehabilitation technology. So, for the rationality of feature selection and the diversity of classifier design in the gesture recognition process based on electromyography (EMG) signals, this paper proposes a hand medical monitoring system based on feature selection method of feature subset average recognition rate and optimal machine learning algorithm selection, which mainly depends on the prediction of hand movement. At the same time, since most experiments are conducted in different non-public proprietary databases, the comparison between various gesture recognition methods can only be analyzed to a certain extent. Therefore, this paper uses the DB1 dataset in the large publicly available NinaPro database and combines with presently well-known 11 time-domain (TD) features and 5 frequency domain (FD) features, then uses the support vector machine (SVM) classifier to comparative analysis total 136 feature combinations under various feature numbers. Under the premise of ensuring the overall recognition rate of electromyography gesture, this method will be able to reduce the number of features in feature set, according to the change of the average remove redundant features, and construct an optimal reduced EMG feature set. Finally, through the four common hand motion classifiers based on machine learning: SVM, back propagation neural network, linear discriminant analysis, and K-nearest neighbor, this paper tests and verifies the separability of the optimal reduced EMG feature set, and based on this, selects the optimal hand motion classifier to build the optimal hand motion recognition system, improve the hand medical monitoring system, and provide technical reference for the c

关键词： Discriminant analysis

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Design and Implementation of a Cascade control System for Continuous Process Based on control Logix 5571 PLC 3

Design and Implementation of a Cascade Control System for Co...

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3rd International Conference on communication, Computing and Industry 4.0, C2I4 2022

作者： Kumaresan, K. Mohanraj, R. Thomas, Ruban Deepa, R. Madhumita, S. Nithishkumar, K. Bannari Amman Institute of Technology Electronics and Instrumentation Engineering Sathyamangalam India Sri Sairam Engineering College Instrumentation and Control Engineering Chennai India Vel Tech Multi Tech Engineering College Electronics and Communication Engineering Chennai India CMR Institute of Technology Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9781665474979

In modern industrial automation, one of the most frequent control systems in process industries is cascade control. If, in addition to the main process variable, additional system variables are measured and given back as secondary process variables, generating subordinate control loops, a cascade control system can be constructed. The integrated cascade control system based on Logix 5571 was developed to resolve the problem of nonlinear and more time delays in chemical process. Steam pressure, steam temperature, air/fuel ratio, drum level, and drum flow are all sensitive to variations in working conditions when considering the primary variables of the continuous chemical process. A temperature process is master control and a steam flow process is slave control have become so integrated. This paper used the velocity form algorithm in PID to optimize the values and design a cascade enhanced proportional integral derivative controller (PIDE) to solve the large time delay in chemical processes. The real-time monitoring, a process parameter actual values and configure I\O tag to Human Machine Interface (HMI) using a factory talk automation software. The logix structure of cascade control loops is especially important for obtaining quick dynamics and proper behavior in all real-world operating modes. In the field of industrial control, which uses PLC Modbus TCP/IP to communicate between one master station and more slave stations. © 2022 IEEE.

关键词： Cascade control Continues process Logix 5571 Modbus TCP\IP PIDE

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Slow Feature Thermography for Non-Destructive Evaluation of Defects in Composite Materials 13

Slow Feature Thermography for Non-Destructive Evaluation of ...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Liu, Kaixin Zhong, Xin Chen, Ping Dai, Yun Liu, Yi North University of China The State Key Lab for Electronic Testing Technology China North University of China Department of Information and Communication Engineering Taiyuan030051 China College of Mechanical Engineering Nantong Vocational University Nantong226007 China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China

ISBN: (纸本)9798350361674

In recent years, various methods for processing and analyzing thermographic data have been applied in non-destructive testing to improve the visibility of defects. Representatively, traditional linear dimensionality reduction methods (e.g. principal component analysis) have achieved good results in thermographic data analysis. In this work, a slow feature thermography (SFT) method for non-destructive evaluation of defects in composite materials. Thermographic data can be regarded as a continuous time series generated by an infrared imager at different moments. Slow feature analysis algorithm is subsequently used to extract slow features of the thermal image sequence. Slow features refer to features that are unchanged or slowly changing in time-series data, such as the background of a thermal image. By extracting the slow features of data, the inhomogeneous background, noise and defect features contained in thermal images can be effectively distinguished. Test results on carbon fiber reinforced polymer specimens demonstrate the feasibility and effectiveness of the SFT method. © 2024 IEEE.

关键词： Carbon fiber reinforced plastics

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Evolving LSTM Networks for Time-Series Classification in EdgeIoT

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Mathematical Problems in engineering 2023年第1期2023卷

作者： Cui, Pei Li, San Jiang, Kaina Liu, Zhendong Sun, Xingkai Science and Technology on Underwater Test and Control Laboratory Dalian China Wuhan Maritime Communication Research Institute Wuhan China Dalian Institute of Measurement and Control Technology Dalian China Beijing Huahang Radio Measurement Institute Beijing China

We proposed a novel approach to evolve LSTM networks utilizing intelligent optimization algorithms and address time-series classification problems in EdgeIoT. Meanwhile, a new optimizer called cultural society and civilization (CSC) algorithm is proposed to reduce the probability of stagnated in the local optima and increase the convergence speed. The suggested method could relieve the problem that the traditional data mining and pattern extraction methods cannot guarantee high accuracy and are hard to deploy on terminal devices. The proposed CSC algorithm and CSC-optimized LSTM model is examined on benchmark problems and demonstrates remarkable superiority over traditional methods and can be applied to support EdgeIoT for learning and processing. © 2023 Pei Cui et al.

关键词： Data mining

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Incoherent spectral imaging based on Bessel beams 2

Incoherent spectral imaging based on Bessel beams

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2nd Advanced Imaging and Information Processing Conference, AIIP 2024

作者： Cheng, Xukun Yu, Xuelian Wang, Zhengxian Yin, Hao Zhao, Lihang Li, Jia Niu, Jia Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China Shanxi Key Laboratory of Quantum Information and Quantum Optoelectronic Devices School of Physics Xi’an Jiaotong University Xi’an710049 China Daheng New Epoch Technology Inc. Beijing100085 China

ISBN: (纸本)9781510683068

Spectral resolution is crucial for achieving precise and high-quality imaging and analysis in imaging systems. Coded aperture correlation holography system face challenges in distinguishing objects at different wavelengths due to their limited spectral resolution. This paper presents a method that combines Bessel beams with a lens phase mask to encode an object's spatial and spectral information into a hologram. Reconstruction is achieved by cross-correlating with the point spread hologram for each wavelength, enabling precise imaging under multi-wavelength conditions. Simulation results show that this method only requires recording a single object hologram at the same wavelength, eliminating the need for multiple recordings. It also offers high spectral sensitivity and spectral resolution. This method is expected to further advance the application of spectral imaging technology in fields such as high-resolution imaging and microscopic endoscopy. © 2024 SPIE.

关键词： Holograms

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AUV Underwater Docking Guidance Method Based on Rotating Current Field

AUV Underwater Docking Guidance Method Based on Rotating Cur...

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2024 OES China Ocean Acoustics, COA 2024

作者： Liu, Jiahui Wang, Zuoshuai Yang, Wentie Liu, Lanyi Xu, Yidong Harbin Engineering University College of Information and Communication Engineering Harbin China Wuhan Second Ship Design and Research Institute Hubei Key Laboratory of Marine Electromagnetic Detection and Control Wuhan China Hygon Information Technology Co. Ltd. Wuhan China Yantai Research Institute of Harbin Engineering University Yantai China

ISBN: (纸本)9798350340297

Autonomous underwater vehicles (AUV) have been increasingly employed in marine resource exploration and development tasks;however, maintaining of long-term operations requires energy supplementation, which mandates docking with platforms. To address the challenges of AUV docking in intricate oceanic environments, this study proposes a novel docking guidance solution, grounded in the rotating current field mechanism. This approach employs multiple pairs of dipoles to transmit fixed phase difference signals, thereby creating a stable and uniform low-frequency current field region. Furthermore, based on the signal amplitude and phase characteristics relative to position, this paper introduces three AUV docking guidance methods able to achieve precise positioning and expedite the docking process. Experimental findings demonstrate that the proposed docking guidance method offers notable advantages in terms of positioning accuracy and feasibility of implementation, thus presenting a novel technical avenue for AUV underwater docking guidance. © 2024 IEEE.

关键词： Marine navigation

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Underwater Electric Dipole Source Localization Based on Hybrid Particle Swarm Optimization-Gravitational Search Algorithm

Underwater Electric Dipole Source Localization Based on Hybr...

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2024 OES China Ocean Acoustics, COA 2024

作者： Liu, Jiahui Yang, Wentie Wang, Zuoshuai Chen, Jiong Xu, Yidong College of Information and Communication Engineering Harbin Engineering University Harbin China Wuhan Second Ship Design and Research Institute Hubei Key Laboratory of Marine Electromagnetic Detection and Control Wuhan China SiEngine Technology Co. Ltd. Wuhan China Yantai Research Institute of Harbin Engineering University Yantai China

ISBN: (纸本)9798350340297

The localization process of the underwater electric dipole source involves solving the global optimal solution of a nonlinear function, which necessitates a multidimensional search and remarkable computational resources. Challenges including slow solution speed and the risk of missing the global optimal solution also exist. To address these challenges, in this study, a global search and localization method based on normalized electric field amplitude, which simultaneously matches and solves the target source position and dipole moment, is proposed. Moreover, the particle swarm optimization (PSO) algorithm is integrated with the gravitational search (GSA) algorithm to propose the improved time-varying inertia-weighted PSO and GSA hybrid optimization algorithm (TVIW-PSO-GSA), enabling rapid optimization and solution of underwater electric dipole source localization. The proposed algorithm exhibits strong convergence capabilities while ensuring local search accuracy. The simulation results reveal that the proposed algorithm achieves faster convergence speed and more accurate estimation performance when compared with traditional optimization algorithms. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Transformer based Online Continuous Multi-Target Tracking with State Regression 12

Transformer based Online Continuous Multi-Target Tracking wi...

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12th IEEE International Conference on control, Automation and Information Sciences, ICCAIS 2023

作者： Wei, Xinwei Chen, Linxiu Zhang, Chenyu Lin, Yiru Zhang, Linao Liu, Xiaokai Jiang, Jixiang Yi, Wei University of Electronic Science and Technology of China School of Information and Communication Engineering China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China University of Electronic Science and Technology of China Research Institute of Electronic Science and Technology China

ISBN: (纸本)9798350328783

Multi-target Tracking (MTT) is the process of processing received measurements to maintain estimates of the current status of multiple targets, with important applications to autonomous driving, aerial reconnaissance, underwater operations, and others. In the model-based setting, Bayesian filtering can provide the theoretical optimal estimate in a single target scenario. However, in complex situations, uncertain factors such as changes in the number of targets will cause the amount of calculation to increase exponentially, resulting in a decline in tracking accuracy. To solve that problem, model-free methods based on deep-learning provide an attractive alternative, especially the state-of-the-art architecture Transformer based encoder-decoder prediction model, which outperforms the Bayesian filters in the single frame prediction tasks. However, when switching to continuous tracking, these algorithms need to be trained separately frame by frame to adapt to the new tasks. Still, there is no correlation between their predictions from different frames, which prevents them from fully utilizing all the measurements. In this paper, we propose an end-to-end Transformer based MTT method with state autoregression, which allows the model to have the capability of online continuous tracking and make total use of the entire trajectory. The results show that the proposed model is a great extension from single-frame prediction to online continuous tracking. © 2023 IEEE.

关键词： Forecasting

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