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2024 International Conference on intelligent Communication, Sensing and Electromagnetics, ICSE 2024

作者： Du, Heng Cang, Huaiming Bai, Yiwen Wang, Xinyi Beijing Elephant Technology Co. Ltd Beijing China School of Transportation Science and Engineering Beihang University Beijing102206 China State Key Lab of Intelligent Transportation System Beijing100191 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350354935

In the field of railway transportation, with the continuous improvement of train running speed and the continuous increase of operating mileage, it becomes particularly important to ensure the safety and integrity of small-Target infrastructure along the railway train. Although many small-Target detection methods have been proposed, the research on small-Target infrastructure detection along rail trains is very rare. To solve this problem, this paper proposes a small-Target infrastructure detection network with spatial tracking and multi-level feature extraction based on Yolov8n. The experimental results show that ST-YOLO has a 3.6% mAP improvement on the OSDaR23 dataset compared to the baseline Yolov8n, and shows significant advantages over other state-of-The-Art methods. © 2024 IEEE.

关键词： Railroads

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A hardware acceleration Framework of Reconfigurable Edge Modules for Convolutional Neural Networks

A hardware acceleration Framework of Reconfigurable Edge Mod...

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Annual Conference of Industrial Electronics Society

作者： Yiming Qiao Zidi Jia Shixiang Li Lei Ren Beihang University Beijing China Zhongguancun Laboratory State Key Laboratory of Intelligent Manufacturing System Technology Beihang University Beijing China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Edge computing exploits node devices situated in close proximity to terminals to deliver distributed computing services directly to users, with FPGAs serving as the predominant platform. With the amplification in volume and intricacy of deep learning models, effectively deploying these models on FPGA devices introduces substantial challenges. To counter this predicament, this paper introduces an FPGA-based hardware acceleration framework for reconfigurable edge devices tailored for Convolutional Neural Networks (CNNs). Initially, a method for dynamically quantizing network models is devised to markedly curtail model memory consumption. Subsequently, a meticulously engineered hardware acceleration unit is formulated to attain augmented computing parallelism via meticulous temporal redesign. Finally, model deployment on FPGA devices for inference verification is showcased utilizing fully connected and convolutional neural networks as exemplars. On the MNIST dataset, the FPGA inference unit attains remarkable accuracy and computational efficiency in comparison to CPUs and GPUs

关键词： Industrial electronics Solid modeling Computational modeling Memory management Parallel processing Convolutional neural networks Distributed computing Field programmable gate arrays Hardware acceleration Edge computing

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10-Hertz squeezed light source generation on the cesium D_(2)line using single photon modulation

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Frontiers of physics 2023年第3期18卷 167-174页

作者： Guan-Hua Zuo Yu-Chi Zhang Gang Li Peng-Fei Zhang Peng-Fei Yang Yan-Qiang Guo Shi-Yao Zhu Tian-Cai Zhang State Key Laboratory of Quantum Optics and Quantum Optics Devices Collaborative Innovation Center of Extreme OpticsInstitute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China College of Physics and Electronic Engineering Shanxi UniversityTaiyuan 030006China Department of Physics Zhejiang UniversityHangzhou 310027China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China

Generation of squeezed light source is a promising technique to overcome the standard quantum limit in precision ***,we demonstrate an experimental generation of quadrature squeezing resonating on the cesium D_(2)line down to 10 Hz for the first *** maximum squeezing in audio frequency band is 5.57 ***,we have presented a singlephoton modulation locking to control the squeezing angle,while effectively suppressing the influence of laser noise on low-frequency *** whole system operates steadily for *** generated low-frequency squeezed light source can be applied in quantum metrology,light–matter interaction investigation and quantum memory in the audio frequency band and even below.

关键词： squeezed state optical parametric amplifier low-frequency squeezing

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Improved rate and cycling performances of Na_(3)V_(2)(PO_(4))_(2)F_(2)O by Ti^(3+/4+)doping with two oxidation states for sodium cathodes

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Transactions of Nonferrous Metals Society of China 2025年第1期35卷 243-256页

作者： Xiao-fei SUN Anastase NDAHIMANA Ling-zhi WANG Zi-kang WANG Quan-sheng LI Wei TANG Min-xing YANG Xue-song MEI State Key Laboratory for Manufacturing System Engineering Xi’an Jiaotong UniversityXi’an 710049China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China Shaanxi Key Laboratory of Intelligent Robots Xi’an Jiaotong UniversityXi’an 710049China School of Chemical Engineering and Technology Xi’an Jiaotong UniversityXi’an 710049China

Ti at the oxidation states of Ti^(3+)and Ti^(4+),was used to enhance the performance of Na_(3)V_(2)(PO_(4))_(2)F_(2)O by partially substituting *** doping Ti,the crystallographic volume is decreased due to the less radii of Ti^(3+/4+),and the valence of Ti is demonstrated identical to *** sodium insertion in Ti-doped Na_(3)V_(2)(PO_(4))_(2)F_(2)O,the two discharge plateaus split into three because of the rearrangement of local redox ***,the optimized Na_(3)V_(0.96)Ti_(0.04)(PO_(4))_(2)F_(2)O shows a specific capacity of 123 and 63 mA·h/g at 0.1C and 20C,*** 350 cycles at 0.5C,the capacity is gradually reduced corresponding to a retention of 71.05%.The significantly improved performance is attributed to the rapid electrochemical kinetics,and showcases the strategy of replacing V^(3+/4+)with Ti^(3+/4+)for high-performance vanadium-based oxyfluorophosphates.

关键词： sodium vanadium oxyfluorophosphate titanium doping cathode sodium battery energy storage

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What are Pros and Cons? Stance Detection and Summarization on Feature Request 17

What are Pros and Cons? Stance Detection and Summarization o...

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17th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2023

作者： Wang, Yawen Wang, Junjie Zhang, Hongyu Wang, Kairui Wang, Qing State Key Laboratory of Intelligent Game Beijing China Institute of Software Chinese Academy of Sciences Science and Technology on Integrated Information System Laboratory Beijing China University of Chinese Academy of Sciences Beijing China Chongqing University Chongqing China

ISBN: (纸本)9781665452236

BACKGROUND: In an online issue tracking system, e.g., GitHub Issue Tracker, feature requests and the associated comment stream provide valuable crowd-generated knowledge for requirements elicitation. To decide whether a feature request should be accepted or not, stakeholders need to identify the comments for/against the feature and understand the two-sided opinions, which is time- and effort-consuming considering the abundant information embedded in lengthy comment stream per feature request. AIMS: This paper proposes VoteBot for automatically detecting stance (for/against) and summarizing the related opinions on a feature request, which can facilitate the decision making (i.e., voting) of feature requests. To our best knowledge, such an approach is previously unexplored for crowd-based requirements elicitation. METHOD: VoteBot is a relation-aware approach, which incorporates three types of relations among the comments or among the comment sentences to better understand the discussions about feature requests. Specifically, it extracts the reply-to relation among the comments, and incorporates it into a BERT-based classifier for stance detection. It also designs a graph-based ranking algorithm, and incorporates semantic relevance and argumentative relations for stance summarization. RESULTS: The automatic evaluation on 250 feature requests with 6,598 comments from five GitHub projects, and the evaluation with practitioners on five new projects, show the promising results. CONCLUSIONS: VoteBot is effective in stance detection and stance summarization, and potentially useful for understanding feature requests and associated discussions in real-world practice. © 2023 IEEE.

关键词： Decision making

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Accurate Distance Measurement Method of Single-Phase Ground Fault of Power Grid Feeder with Load Division Based on Fault Secondary Discrimination 5

Accurate Distance Measurement Method of Single-Phase Ground ...

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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Cheng, Yunxiang Liu, Xiangbo Wang, Sen Gao, Fang Li, Hao Tao, Zhengchen State Grid Rizhao Power Supply Company Power Supply Service Command Center Rizhao China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9798350339673

In order to solve the problem of low accuracy of traditional fault location method when the feeder of distribution network contains load branches, this paper proposes an accurate fault location method for single-phase grounding fault of feeder in distribution network with load branches based on fault secondary discrimination. By analyzing the feeder fault recording data, the fault point is identified twice to determine whether the fault point occurs on the load branch. According to different fault location, the voltage of the fault point is calculated by using the voltage and current of the two ends of the fault section. The voltage of the calculated fault point should be equal. The objective function of the minimum voltage difference of the fault point is written, and the fault distance x under the minimum voltage difference is obtained. The simulation model of 10KV distribution network is built on PSCAD, which verifies the accuracy of the ranging algorithm and has certain ability to resist transition resistance, which has certain engineering practice value. © 2023 IEEE.

关键词： accurate ranging algorithms fault secondary location Load division dominates grid feeders single-phase ground fault

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A Low-complexity Decision Variables Classification Brainstorm Optimization Algorithm

A Low-complexity Decision Variables Classification Brainstor...

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2024 International Conference on Applied Mathematics, Modelling and Statistics Application, AMMSA 2024

作者： Li, Qiyue Qiu, Lipeng Zhou, Aoran Wu, Yali Wang, Ziren Department of Information and Control Engineering Xi'An University of Technolog Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China State Key Laboratory of Metal Extrusion and Forging Equipment Technology China National Heavy Machinery Research Institute Co. Ltd. Xi'an710016 China

In the complex optimization scenarios of real life, we often need to not only weigh the conflicts between multi-objectives but also face the challenges brought by large-scale decision variables. When the scale of decision variables increases sharply, the search space will expand exponentially, which makes it difficult for the algorithm to traverse the whole search space under limited resources, so that the number of local optimal solutions increases sharply. The so-called 'dimension disaster' appears. To effectively deal with this problem, this paper proposes a large-scale multi-objective brainstorm optimization algorithm (LMaOBSO) based on low complexity decision variable classification method and improved penalty boundary intersection strategy. The algorithm uses a low-complexity tree sorting variable classification method to divide the decision variables into converges and diversity variables quickly. At the same time, the convergent variables are optimized by the improved penalty boundary crossover strategy to solve the problems existing in large-scale optimization problems. © Published under licence by IOP Publishing Ltd.

关键词： Disasters

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Research on Identification Strategy of Fault-Sensitive Frequency for Planetary Gearboxes

Research on Identification Strategy of Fault-Sensitive Frequ...

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

作者： Xie, Ruitong Zhang, Mian Chen, Jiwei Zhu, Songsong Wang, Zhiyuan Zhao, Mengxiong Xiang, Hongbiao Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

Planetary gearboxes find extensive application in wind power generation, aerospace, industrial production and other fields. Harsh operational conditions and prolonged periods of continuous work often lead to various gear damages. Therefore, it is important to continuously monitor the health status of planetary gearboxes. However, the fault-sensitive frequencies of planetary gearboxes used in the existing signal models and fault diagnosis indicators are calculated theoretically or searched artificially. In response to this, this paper proposes a strategy for identifying fault-sensitive frequencies in planetary gearboxes intelligently by combining spectral amplitude analysis with three models: Random Forest (RF), Support Vector Machine (SVM) and Deep Neural Network (DNN). Experiments are carried out to verify the effectiveness and superiority of the proposed strategy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Deep neural networks

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An Order Demodulation Analysis Method for Planetary Gearboxes

An Order Demodulation Analysis Method for Planetary Gearboxe...

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

作者： Chen, Jiwei Xie, Ruitong Zhu, Songsong Zhao, Mengxiong Wang, Zhiyuan Zhang, Mian Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechanical System Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Binshuixidao 391 Xiqing District Tianjin300384 China State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan430072 China

ISBN: (纸本)9783031694820

In addressing challenges such as the speed change of planetary gearbox (PG) during operation and the complexity in extracting fault features, an order demodulation analysis method based on order tracking (OT) and variational mode decomposition (VMD) is proposed. Non-stationary time domain signals are transformed into relatively stable angular domain signals through angular resampling. The intrinsic mode function (IMF) is obtained by demodulation of the angular multi-component signal using the VMD method. The instantaneous order of a proper IMF is calculated via Hilbert Transform. The sensitive single component is selected by matching the meshing order and the central order of the instantaneous order. Finally, the amplitude of the characteristic order components extracted from the instantaneous order spectrum was used as features and Support Vector Machine (SVM) was employed for the classification of four different conditions in the sun gear. Comparing the results of the proposed method with Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), the experimental results demonstrate the effectiveness of the proposed method in diagnosing PGs under non-stationary conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Epicyclic gears

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The work region and total work capability of integrated energy system: Concepts, models, and mechanisms

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Applied Energy 2025年 394卷

作者： Zhou, Tianshuo Wang, Dan Jia, Hongjie Xiao, Jun Li, Yizhe Cheng, Hao State Key Laboratory of Intelligent Power Distribution Equipment and System Tianjin University Nankai District Tianjin300072 China Key Laboratory of Smart Energy & Information Technology of Tianjin Municipality Tianjin300072 China

Exergy is the quantification of the work capability of energy. Accurately characterizing the limits and scope of the work potential within an integrated energy system (IES) is a crucial foundation for achieving energy-quality matching, hierarchical utilization, and enhancing the level of energy utilization. Based on the "region" method, this paper first establishes a work region model for the IES. It demonstrates a linear mapping relationship between the operating point of the work region and that of the operation region, and proves the isometric, similarity, and nonlinear geometric transformation relationships between the work region and the operation region in a multi-dimensional space. Furthermore, an improved dichotomy method is proposed as a solution for determining the security boundary of the work region, balancing both computational accuracy and efficiency. Subsequently, a model for the maximum total work capability (TWC) and the TWC curve of the IES is established. Based on the mathematical relationship between TWC and total supply capability (TSC), three methods for calculating the maximum TWC are proposed. Finally, through three typical case studies, the operation region and TSC were used as comparison benchmarks to validate the accuracy and superiority of the proposed model and method, revealing the phenomenon of local work capability decay under different operating conditions. The research presented in this paper contributes to the collaborative development of energy quantity and quality in IES, providing essential theoretical and technical support for the planning, operation, and energy market transactions of IES. © 2025 Elsevier Ltd

关键词： Conformal mapping

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