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International Conference on Network and Information Systems for Computers (ICNISC)

作者： Yunqi Chen Jin Xu Measurement and Control Technology Research Institute China Coal Technology Engineering Group Chongqing Research Institute Chongqing China School of Big Data & Software Engineering Chongqing University Chongqing China

ISBN: (纸本)9781665453523

Coal is the most important basic energy supporting the development of the national economy, safe production and effective supervision and management are of great significance. Currently, the coal mine safety monitoring system can be monitored locally, but it cannot help the supervision department to realize the remote supervision and centralized supervision. Establishing a corresponding coal mine safety monitoring network system has become a urgent need of coal mine safety supervision. In the paper, we first study the service-oriented architecture(SOA), and describes the windows communication foundation(WCF) technology, the technology is a main way to achieve SOA architecture. Then combined with WCF technology, the function and logic structure of coal mine safety monitoring network system are designed. Finally, the network system of mine monitoring system based on SOA was realized in the background of a mine monitoring system networking project of a company.

关键词： Economics Companies Computer architecture Coal Safety Coal mining Service-oriented architecture

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UAV-Assisted IoT Data Collection Scheme for IRS-Enabled Backscatter communication Networks

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green communications and Networking 2025年

作者： Han, Shuai Wang, Jinming Xu, Sai Wang, Shiji Li, Cheng Harbin Institute of Technology School of Electronics and Information Engineering China 5GIC and 6GIC GuildfordGU2 7XH United Kingdom Southeast University National Mobile Communications Research Laboratory Nanjing211111 China Beijing Aerospace Measurement and control Technology CO.LTD Beijing China Simon Fraser University School of Engineering Science BurnabyBCV5A 1S6 Canada

Data collection schemes assisted by unmanned aerial vehicle (UAV) play a key role in Internet-of-Things (IoT) networks. Nonetheless, the massive IoT devices bring new challenges, especially the high energy consumption. The backscatter communication (BackCom) technique can utilize ambient signals for passive transmission, thus being applicable to IoT systems. Due to its numerous reflecting elements, Intelligent Reflecting Surface (IRS) can accomplish backscatter with high beamforming gain. Thus, IRS is suitable to alleviate the double-fading effect, which significantly restrains the development of BackCom networks. This paper utilizes the IRS-based BackCom technique to achieve efficient IoT data collection with the help of a UAV. The UAV provides carriers for multiple IRSs, which can emit data through backscatter. Then, the UAV collects the backward data dynamically. To maximize the collected data, the UAV's transmit power, trajectory, and the IRS's beamformers are jointly optimized. The optimization is realized through an alternative algorithm based on block coordinate descent (BCD) and reinforcement learning (RL). The Lagrangian dual transformation and semi-definite relaxation (SDR) approaches are employed to address the non-convexity of the problem effectively. Finally, simulation results demonstrated the effectiveness and feasibility of the proposed optimization scheme in the introduced system model. © 2017 IEEE.

关键词： Reinforcement learning

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Heterogeneous Multi-Robot Cooperative Welding Task Allocation Based on Task-Centered Optimization: An Industrial Case Study

SSRN

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SSRN 2023年

作者： Liu, Wenbo Kuang, Zhian Zhou, Bo Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shanghai Friendess Electronic Technology Shanghai201100 China

In this article, the complex task assignment, scheduling and planning of complex heterogeneous multi-robot welding process are studied. For large workpiece welding tasks that involve complex heterogeneous multi-robot task allocation under different internal and external constraints, the traditional multi-robot task allocation (MRTA) framework is extended to a novel and unified heterogeneous multi-robot (H-MRTA) framework, and a hierarchical optimization algorithm is proposed. Firstly, an optimization model based on the H-MRTA framework is established. Taking into account constraints such as accessibility, collision and welding process, the optimization objectives are formulated by combining the total welding time and the task balance between robots. Then, to obtain the optimal solution, a stepwise optimization algorithm is devised to solve the MRTA problem from top to bottom in two layers: working area division problem and multi-robot path planning problem. For the working area division problem, a task-centered optimization model is proposed, which aims to balance the workload among robots, and is solved by branch-and-bound method. For the multi-robot path planning problem, multiple process constraints are considered and the total working time is minimized as the objective function. The effectiveness of the optimization algorithm is verified by a case study on the welding task of a large plate element in a ship hull. compared to two other state-of-the-art algorithms, the proposed optimization algorithm achieves a task allocation scheme with a shorter welding time, a shorter waiting time and a higher welding productivity, which demonstrates the effectiveness and feasibility of the stepwise optimization-based task allocation algorithm for complex heterogeneous multi-robot. © 2023, The Authors. All rights reserved.

关键词： Industrial robots

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Adaptive Sliding Mode control for Force Tracking Using Nonlinear Observer

Adaptive Sliding Mode Control for Force Tracking Using Nonli...

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Chinese control and Decision Conference, CCDC

作者： Linyan Han Haibo Du Shihua Li Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (纸本)9781665478977

This paper focuses on the development of a control scheme capable of tracking contact forces explicitly. Specifically, the nonlinear observer, admittance control and adaptive sliding mode control are integrated into a single framework. When the force sensor is absent, a nonlinear observer, which serves as a reaction force observer, can be used to estimate the contact force. Furthermore, in order to track the force profile explicitly, admittance control is introduced to transform the desired contact force into the desired position signal. An adaptive sliding mode controller is designed to track the desired position and meanwhile compensate the estimation errors of contact forces caused by nonlinear observer. The stability of the whole system under the proposed controller can be guaranteed by the Lyapunov function. Finally, several simulations are reported to demonstrate the effectiveness of the proposed approach.

关键词： Service robots Simulation Force Transforms Observers Stability analysis Trajectory

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Bi-layered coded metasurface for multi-functional hologram with broadband transmission and efficient reflection

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Chinese Optics Letters 2024年第5期22卷 8-16页

作者：朱磊李绪胜董亮谢文静尚关玉 Shah Nawaz Burokur 丁旭旻 School of Computer and Control Engineering Qiqihar UniversityQiqihar 161006China Communication and Electronics Engineering Institute Qiqihar UniversityQiqihar 161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqihar 161000China Department of Microwave Engineering Harbin Institute of TechnologyHarbin 150001China LEME UPLUniversitéParis NanterreF92410 Ville d’AvrayFrance Advanced Microscopy and Instrumentation Research Center Harbin Institute of TechnologyHarbin 150080China Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

A multi-functional full-space metasurface based on frequency and polarization multiplexing is *** metasurface unit consists of metallic patterns printed on the two faces of a single-layered dielectric *** unit cell can control electromagnetic wavefronts to achieve a broadband transmission with amplitudes greater than 0.4 from 4.4 to 10.4 ***,at 11.7 GHz and 15.4 GHz,four high-efficiency reflection channels with a reflection amplitude greater than 0.8 are also *** illuminated by linearly polarized waves,five different functions can be realized at five different frequencies,which are demonstrated by theoretical calculations,full-wave simulations,and experimental measurements.

关键词： multi-functional metasurface broadband transmission efficient reflection full space

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UKF-Based Multi-sensor Data Processing Algorithm for SLAM

UKF-Based Multi-sensor Data Processing Algorithm for SLAM

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IEEE International Conference on control Science and Systems engineering (CCSSE)

作者： Kun Xu Boheng Zhang Jiangang Li Guizhong Wang Mingjian Sun School of Information Science and Engineering Harbin Institute of Technology Weihai Weihai China Department of Control Science and Engineering Harbin Institute of Technology Harbin China Woan Technology (Shenzhen) Co. Ltd. Shenzhen China Hebei Key Laboratory of Grid Advanced Measurement and Monitor Jinyanhagong Industrial Technology Research Institute Zhangjiakou China School of Information Science and Engineering Harbin Institute of Technology Harbin China

Simultaneous localization and mapping (SLAM) algorithm is widely used in unmanned and robotic applications. SLAM usually uses sensor data, which are from the LiDAR, the inertial measurement unit (IMU) and the wheeled odometry, to build maps of the surrounding environment. However, the motion distortion of LiDAR data and the error accumulation of wheeled odometry can affect the accuracy of the front-end odometry of the SLAM algorithm, which can lead to serious errors in the maps created. Therefore, in order to solve the problem of poor map construction results of SLAM algorithm due to various types of sensor errors. we propose the traceless Kalman filtering based (UKF-based) multi-sensor data processing algorithm. Firstly, the proposed algorithm uses the UKF to fuse IMU and wheeled odometry data to reduce the cumulative error of wheeled odometry. And then the algorithm uses IMU and corrected wheeled odometry data and combines with the motion states of the robot to solve the motion distortion problem of LiDAR data. Finally, we verified the effectiveness of the proposed algorithm for wheeled odometry data correction in Gazebo simulation environment and real environment experiments, and compared the mapping effectiveness of SLAM by using the original data and the data processed by our algorithm. The experimental results show that the map construction effect of SLAM algorithm is significantly improved when using the sensor data processed by the algorithm. Experimental validation on the robot shows that the proposed algorithm has universal applicability and good compatibility.

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Fast Coding Mode Decision for Intra Prediction in VVC SCC

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IEEE Transactions on Broadcasting 2025年第2期71卷 506-516页

作者： Dayong Wang Weihong Liu Zeyu Zhou Xin Lu Jinhua Liu Hui Guo Ce Zhu Chongqing Key Laboratory on Big Data for Bio Intelligence Chongqing University of Posts and Telecommunications Chongqing China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China School of Cybersecurity Chengdu University of Information Technology Chengdu China School of Computer Science and Informatics De Montfort University Leicester U.K. School of Digital Technology Industry Shangrao Normal University Shangrao China Glasgow College and the School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

Currently, screen content video applications are widely used in our daily lives. As the latest Screen Content Coding (SCC) standard, Versatile Video Coding (VVC) SCC employs a quad-tree plus nested multi-type tree (QTMT) coding structure and various screen content coding modes (CMs). This design enhances the coding efficiency of VVC SCC but also results in a highly complex coding process, which significantly hinders the broader adoption of screen content video technology. Consequently, improving the coding speed of VVC SCC is highly desirable. In this paper, we propose a fast CM and transform decision algorithm for Intra prediction in VVC SCC. Specifically, we initially use Convolutional Neural Networks (CNNs) to predict content types for all Coding Units (CUs). Subsequently, we predict candidate CMs for CUs based on the CM distributions of different content types. We then select the Sum of Absolute Transformed Difference (SATD) as a feature and use a naive Bayes classifier to skip unlikely Intra mode early. Finally, we terminate Block-based Differential Pulse-Code Modulation (BDPCM) early and then select the best transform type in Intra mode prediction to improve coding speed. Experimental results demonstrate that the proposed algorithm improves coding speed by an average of 39.28%, with the BDBR increasing by 0.80%.

关键词： Encoding Copper Prediction algorithms Classification algorithms Transforms Electronic mail Standards Complexity theory Training Partitioning algorithms

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Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged Photonic-Electrical Silicon Transceiver for High-speed Optical Interconnects

Deep Neural Network Enhanced Chip-on-board Hybrid-Packaged P...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Qin, Jun Yang, Qipeng Han, Changhao Zhou, Yan Zhang, Yunhao Wu, Yichen Sun, Yu Lu, Junde Liu, Siming Li, Yueqin Sun, Jian Min, Miao Hu, Weiwei He, Zhixue Wang, Lei Yu, Shaohua Shu, Haowen Wang, Xingjun Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology University Beijing100192 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States Peking University Yangtze Delta Institute of Optoelectronics Nantong226010 China Peng Cheng Laboratory Shenzhen518055 China State Key Laboratory of Information Photonics and Optical Communications BUPT Beijing100876 China

We explore implementing a multilevel deep neural network to enhance the performance of a 4-channel photonic-electrical hybrid-packaged silicon transceiver. Stable transmission and reception of 150 Gbps/λ PAM4 signals... 详细信息

关键词： Optical interconnects

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Experimental Study on Flame Behaviors and Dynamic Parameters Induced by Hydrogen Jet Fire in an Enclosed Compartment

SSRN

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SSRN 2023年

作者： Huang, Zhiwei Jin, Hao Ma, Hongsheng Yu, Xing Li, Yang Wang, Changjian School of Civil Engineering Hefei University of Technology Anhui Hefei230009 China Anhui International Joint Research Center on Hydrogen Safety Hefei230009 China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of Education Hefei230009 China

Hydrogen is thought of as one of the most superior future energy carriers due to its clean, low-carbon and extensive sources. However, the broad combustion range and low ignition energy of hydrogen can cause potential safety hazards, even hydrogen jet fires. Currently, an array of hydrogen jet flame experiments was performed in an enclosed compartment with internal dimensions of 1.82m (L) × 1.99m (W) × 1.85m (H), using different nozzle diameters and stagnation pressures. The results indicate that the combustion process can be divided into four stages, including growth stage, relatively stable stage, stretching stage, and self-extinguishing stage. Both the average gas temperature slope and the maximum average gas temperature are linearly proportional to the stagnation pressure. The oxygen concentration in an enclosed compartment decreases rapidly with increasing stagnation pressure. The self-extinguishing time is positively correlated with the mass of oxygen and negatively correlated with the mass flow rate. Based on thermal equilibrium analysis, the correlations for average gas temperature rise and oxygen concentration were proposed. © 2023, The Authors. All rights reserved.

关键词： Gas temperature

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Acoustic Emission Recognition Based on a Two-Streams Convolutional Neural Network

引用

Computers, Materials & Continua 2020年第7期64卷 515-525页

作者： Weibo Yang Weidong Liu Jinming Liu Mingyang Zhang School of Information and Communication Engineering Nanjing Institute of TechnologyNanjing211167China School of Information and Control Engineering China University of Mining and TechnologyXuzhou221000China School of Information Science and Engineering Southeast UniversityNanjing211100China Department of Electrical and Computer Engineering National University of Singapore119077Singapore

The Convolutional Neural Network(CNN)is a widely used deep neural *** with the shallow neural network,the CNN network has better performance and faster computing in some image recognition *** can effectively avoid the problem that network training falls into local *** present,CNN has been applied in many different fields,including fault diagnosis,and it has improved the level and efficiency of fault *** this paper,a two-streams convolutional neural network(TCNN)model is *** on the short-time Fourier transform(STFT)spectral and Mel Frequency Cepstrum Coefficient(MFCC)input characteristics of two-streams acoustic emission(AE)signals,an AE signal processing and classification system is constructed and compared with the traditional recognition methods of AE signals and traditional CNN *** experimental results illustrate the effectiveness of the proposed *** with single-stream convolutional neural network and a simple Long Short-Term Memory(LSTM)network,the performance of TCNN which combines spatial and temporal features is greatly improved,and the accuracy rate can reach 100%on the current database,which is 12%higher than that of single-stream neural network.

关键词： Convolutional neural network acoustic emission fault detection

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