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8th International Conference on Power Energy Systems and Applications, ICoPESA 2024

作者： Zhang, Sen Hu, Weihao Cao, Xilin Zhao, Yincheng Liu, Rundong Ma, Haojie Zhan, Wei Li, Mingxuan School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Sichuan Provincial Key Lab of Power System Wide Area Measurement and Control Chengdu China School of Management and Economics Beijing Institute of Technology Beijing China SPIC Southwest Energy Research Institute Chengdu China

ISBN: (纸本)9798350351668

To achieve the economic operation of a multi-energy micro grid under multiple uncertain environments, this study introduces a novel two-stage robust scheduling approach, encompassing both day-ahead planning and real-time adjustments. First, the multi-energy micro grid day-ahead economic dispatch model is constructed based on the prediction scenarios, and integrated demand response is considered to increase the flexibility of the system. Afterwards, the strategy is adjusted in the real-time phase, considering the uncertainty of energy production and consumption. The Column-and-Constraint Generation algorithm is employed to resolve the above two-stage issues effectively, and the optimal economic operation strategy of the MEMG is obtained. Finally, a case study demonstrates the economy and robustness of the proposed methodology. © 2024 IEEE.

关键词： Demand response

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MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE BASED ON MONTE-CARLO TREE SEARCH 10

MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Dai, Juan Jing, Yanzhang Su, Zhong Zhu, Cui Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science & Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China School of Automation Beijing Information Science & Technology University Beijing China School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

With the rapid development of artificial intelligence technologies, multi-robot cooperative processing tasks are becoming more and more common in various applications. However, traditional single-robot planning algorithms show obvious limitations in dealing with complex social interactions and dynamic environments in the real world. To address this challenge, this paper applies Monte Carlo Tree Search (MCTS) to multi-robot path planning and proposes a collaborative obstacle avoidance motion planning algorithm based on MCTS. Specifically, the algorithm prunes the Monte Carlo tree by excluding cases that do not meet the robot speed constraints and potential collisions, which significantly improves the computational speed and success rate of the algorithm, making it applicable to the multi-robot path conflict problem. In addition, we design a policy space that conforms to the robot's operation and a cost function that meets the requirements of robot path planning to plan an efficient cooperative path for each robot. Through a series of simulation experiments, we demonstrate the algorithm's path planning and obstacle avoidance performance in a variety of conflict scenarios. The results show that the method is highly cooperative and effective in complex environments. © The Institution of engineering & technology 2024.

关键词： Cost functions

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Fault Diagnosis Method of Rolling Bearings under Different Working Conditions Based on Federated Feature Transfer Learning 3

Fault Diagnosis Method of Rolling Bearings under Different W...

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3rd International Conference on Sensing, measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2022

作者： Kang, Shouqiang Yang, Jiawei Sun, Yulin Wang, Yujing Wang, Qingyan Mikulovich, V.I. School of Measurement-Control and Communication Engineering Harbin University of Science and Technology Harbin China Belarusian State University Minsk Belarus

ISBN: (纸本)9781665492812

A rolling bearing fault diagnosis method based on the federated feature transfer learning is proposed for the low accuracy of the diagnosis model in the presence of large differences in data distribution under different working conditions, difficulty in obtaining labeled data and non-sharing of data among different users. This method performs wavelet transformation on the time domain vibration data of rolling bearings to obtain a time-frequency diagram. The priori labeled public data and the multi-user island private data are regarded as the source domain and the target domain. The multi-representation feature extraction structure is introduced to improve the original residual network. Based on an improved residual network and multi-representation features in the source domain and the target domain, every local model and a federated global model are constructed. Through verification of bearing data, the proposed method can establish an effective fault diagnosis model with high fault diagnosis accuracy. It can integrate the knowledge of isolated island data without sharing data among multiple users. © 2022 IEEE.

关键词： Different working conditions domain adaptation fault diagnosis feature transfer learning federated learning

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User Cooperative Receiving Scheme of Misaligned OAM Signals for UAV Emergency communications 14

User Cooperative Receiving Scheme of Misaligned OAM Signals ...

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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Zhou, Yanguo Chen, Ruirui Xu, Keyue Feng, Rui Ding, Jicun Lin, Jinyang China Academy of Electronics and Information Technology National Engineering Laboratory for Risk Perception and Prevention Beijing China China University of Mining and Technology School of Information and Control Engineering Xuzhou China North University of China State Key Laboratory of Dynamic Measurement Technology Taiyuan China Xuzhou First Peoples Hospital Xuzhou China

ISBN: (纸本)9798350361889

For the massive users in post-disaster scenario, unmanned aerial vehicle (UAV) can rapidly establish emergency communications, and orbital angular momentum (OAM) can significantly improve spectrum efficiency (SE). Due to hollow divergence and alignment requirement, it is hard for users to receive OAM signals by using antenna-limited devices. For UAV emergency communications with line-of-sight link, we propose the user cooperative receiving (UCR) scheme, which can realize 2 OAM mode multiplexing communications for users at long distance. Two cooperative users (CUs) are chosen, and the waist radius is adjusted to guarantee the maximum intensity at two CUs. The OAM beam steering is designed to eliminate the inter-mode interference of misaligned OAM signals caused by the antenna misalignment. Simulation results demonstrate that the proposed UCR scheme can obtain higher SE than the traditional scheme due to the effective reception of misaligned OAM signals for UAV emergency communications. © 2024 IEEE.

关键词： Antennas

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Task Offloading and Primary Node Selection in Blockchain, Digital Twin, and MEC Enabled Internet of Vehicles 100

Task Offloading and Primary Node Selection in Blockchain, Di...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Du, Jianbo Fang, Huifang Li, Shulei Du, Pengfei Kong, Ziwen Kang, Jiawen Niyato, Dusit Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security School of Communications and Information Engineering Xi'an China Xidian University School of Communications Engineering Xi'an710071 China Tianyuan Ruixin Communication Technology Co. LTD. Xi'an710071 China Xihua University Engineering Research Center of Intelligent Airground Integrated Vehicle and Traffic Control Ministry of Education Chengdu610039 China Guangdong University of Technology School of Automation China Nanyang Technological University School of Computer Science and Engineering Singapore

ISBN: (纸本)9798331517786

In this paper, we investigate the safe task offloading and primary node selection in blockchain, digital twin (DT) and Multi-access Edge Computing (MEC) enabled Internet of Vehicles (IoV). Edge servers centers provide computing power for task processing for Mobile Vehicles (MVs), while blockchain can provide security guarantees for MVs during task offloading. Based on the above system, we propose a joint optimization scheme for vehicle task offloading decision and the Practical Byzantine Fault Tolerance (PBFT) consensus process. Due to the large number of optimization variables and constraints, the problem becomes more complex. Traditional convex optimization and dynamic programming methods are difficult to effectively solve this problem. To address this issue, we propose a deep reinforcement learning based algorithm that utilizes Proximal Policy Optimization (PPO). The experimental results show that the algorithm proposed in this paper outperforms the benchmark algorithm in terms of convergence and other aspects. © 2024 IEEE.

关键词： Dynamic programming

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A Review of Spiking Neural Network Research in the Field of Bearing Fault Diagnosis 1

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Wang, Yusen Wang, Hongjun Xie, Long Ge, Henglin Zhou, Mingyang Chen, Tao Shi, Yuxing School of Mechanical and Electrical Engineering Beijing Information Science & Technology University Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education BISTU Beijing100192 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception and Control BISTU Beijing100192 China

ISBN: (数字)9783031694837

ISBN: (纸本)9783031694820

In view of the bearing fault diagnosis problem, in order to better deal with the temporal data, extract nonlinear features, enhance the model robustness and adaptability, and realize efficient distributed computing, the spiking neural network is introduced to improve the accuracy and efficiency in the process of bearing fault diagnosis. In recent years, after a series of studies, the spiking neural network has developed in supervised learning, unsupervised learning, semi-supervised learning, and some other derived methods, such as reinforcement learning and transfer learning, for its applicable scenarios with different advantages. From the perspective of learning principle, method advantages and practical applications, we introduced several spiking neural network for bearing fault diagnosis, discussed the advantages, disadvantages and applicable scenarios of each learning method, discussed the application prospect of spiking neural network for bearing fault diagnosis, and proposed the spiking neural network for bearing fault diagnosis in future research, so as to provide reference for subsequent research. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Self-supervised learning

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Design of Accelerated Reliability Validation Plan for Smart Electrical Energy Meters under Time-Varying Environments

Design of Accelerated Reliability Validation Plan for Smart ...

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System Reliability and Safety engineering (SRSE), International Conference on

作者： Youmei Zhang Ning Li Wei Zhang Qihong Chen Lin Li Jia Qi School of Measurement–Control Technology and Communications Engineering Harbin University of Science and Technology Harbin China Marketing Service Centre of State Grid Xinjiang Electric Power Co. Urumqi China

ISBN: (数字)9798350356083

ISBN: (纸本)9798350356090

To address the challenge of validating high-quality and long-lifetime products, this study developed a model that accounts for accelerated degradation under typical time-varying environments. Utilizing data from test bases and field operations in a certain region, a model was constructed to describe the impact of temperature stress on the lifespan of smart meters over time. The Arrhenius model was employed to create an acceleration model for time-varying temperatures influencing the lifespan of the smart electrical energy meters, enabling the determination of activation energy and dynamic acceleration factors under two distinct time-varying environmental conditions. Leveraging these acceleration factors, an accelerated reliability acceptance plan was designed specifically for smart electrical energy meters with Weibull-distributed lifetimes under time-varying stress conditions.

关键词： Meters Degradation Temperature distribution Life estimation Reliability engineering Smart meters Safety Weibull distribution Time-varying systems Stress

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Research on the Wirtinger Flow algorithm based on quadratic distribution initial value 1

Research on the Wirtinger Flow algorithm based on quadratic ...

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1st Advanced Imaging and Information Processing Conference, AIIP 2023

作者： Xie, Zhenfei Yu, Xuelian Wang, Zhengxian Li, Heng Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication Engineering Harbin University of Science and Technology Harbin150080 China Shenzhen Engineering Laboratory of Aerospace Detection and Imaging College of Electronic and Information Engineering Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781510671904

Phase retrieval algorithms, such as the Wirtinger Flow (WF) algorithm, are widely used in various fields. As a non-convex optimization algorithm for phase retrieval, WF is commonly employed in the reconstruction of holograms in holographic image projection. These types of algorithms typically involve two stages: an initialization stage and an iterative optimization stage. In the initialization stage, an initial value is provided, and a spectral method is used to calculate an approximate solution as the initial guess. The iterative optimization stage then utilizes the Wirtinger gradient to iteratively compute and converge the initial guess to a nearby real solution, thereby obtaining the global optimal solution. However, due to the random nature of the initial values, the computed results often exhibit significant instability. To address this issue, this paper proposes an approach based on a quadratic distribution for improving the stability of the results. In the initialization stage, the initial value is set as the quadratic distribution initial value. Then, the spectral method is applied again to calculate the initial guess. Since the quadratic distribution initial value is artificially assigned, it enhances the stability of the computed results. To validate this method, the paper applies the quadratic distribution initial value to both the initialization stage of the WF algorithm and the Truncated Amplitude Flow (TAF) algorithm. A comparison is made between the results obtained using random initial value and those obtained using the quadratic distribution initial values. The results demonstrate that compared to random initial values, the quadratic distribution initial values can achieve faster and equally accurate computation results with higher stability. Finally, this method is applied to simulation experiments of in-line digital holography, and the reconstruction results from the experiments further confirm the effectiveness of our approach. © 2023 SPIE.

关键词： Convex optimization

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Throughput-oriented associated transaction assignment in sharding blockchains for IoT social data storage

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Digital communications and Networks 2022年第6期8卷 885-899页

作者： Liping Tao Yang Lu Xu Ding Yuqi Fan Jung Yoon Kim School of Computer Science and Information Engineering Hefei University of TechnologyHefei230009China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of EducationHefei University of TechnologyHefei230009China Institute of Industry&Equipment Technology Hefei University of TechnologyHefei230009China Key Laboratory of Knowledge Engineering with Big Data(Hefei University of Technology) Ministry of EducationHefei230009China Graduate School of Game Gachon UniversitySeongnam-Si461-701South Korea

Blockchain is a viable solution to provide data integrity for the enormous volume of 5G IoT social data, while we need to break through the throughput bottleneck of blockchain. Sharding is a promising technology to solve the problem of low throughput in blockchains. However, cross-shard communication hinders the effective improvement of blockchain throughput. Therefore, it is critical to reasonably allocate transactions to different shards to improve blockchain throughput. Existing research on blockchain sharding mainly focuses on shards formation, configuration, and consensus, while ignoring the negative impact of cross-shard communication on blockchain throughput. Aiming to maximize the throughput of transaction processing, we study how to allocate blockchain transactions to shards in this paper. We propose an Associated Transaction assignment algorithm based on Closest Fit (ATCF). ATCF classifies associated transactions into transaction groups which are then assigned to different shards in the non-ascending order of transaction group sizes periodically. Within each epoch, ATCF tries to select a shard that can handle all the transactions for each transaction group. If there are multiple such shards, ATCF selects the shard with the remaining processing capacity closest to the number of transactions in the transaction group. When no such shard exists, ATCF chooses the shard with the largest remaining processing capacity for the transaction group. The transaction groups that cannot be completely processed within the current epoch will be allocated in the subsequent epochs. We prove that ATCF is a 2-approximation algorithm for the associated transaction assignment problem. Simulation results show that ATCF can effectively improve the blockchain throughput and reduce the number of cross-shard transactions.

关键词： IoT social data Blockchain Shar ding Associated transactions Transaction assi gnment

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A Digitally assisted nonlinearity suppression architecture using over-the-air beam cancelation

A Digitally assisted nonlinearity suppression architecture u...

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作者： Mu, Qin Li, Nanxi Chen, Cong Wei, Xiaozheng Wen, Rong Wu, Muqing Li, Xiang Liu, Ying School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China National Key Lab of Science and Technology on Communications University of Electronic Science and Technology of China Chengdu China School of Network and Communication Engineering Chengdu Technological University Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing China

Using a large number of power amplifiers brings serious nonlinear distortion to 5G communication systems, which becomes a challenging problem for conventional digital predistortion (DPD) to linearize signals. To address this challenge, we propose a digitally assisted nonlinearity suppression architecture for applications in multiple antenna arrays. In this architecture, we use an auxiliary array to generate a nonlinear cancelation signal to cancel with the main beam at the receiving end. We explore a two-step method to model the nonlinear signal and combine neural network to complete the modeling. In addition, we introduce a novel method for estimating and tracking the channel to update the model coefficients. To verify the proposed methods, we design a scene and compare the performance of our architecture with that of conventional DPD. Our experiments demonstrate that our proposed methods can significantly enhance the adjacent channel power leakage ratio performance by 12 dB while also optimizing in-band distortion. Moreover, our architecture outperforms conventional DPD approaches even with enhanced distortion. © 2023 John Wiley & Sons Ltd.

关键词： Power amplifiers

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