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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Qie, Kaiming Wang, Yuanyuan Lin, Fuliang Zhao, Ruizheng Yang, Han Beijing Institute of Control and Electronic Technology Science and Technology on Information Systems Engineering Laboratory Beijing China School of Automation Chongqing University Chongqing China

ISBN: (纸本)9798350346671

Aiming at the demand of distributed energy production management system for intelligent operation and maintenance, considering the problems in current log analysis method, we propose an intelligent log analysis technology for distributed energy production management system. This technology applies distributed log framework to achieve the collection, storage, analysis and display of various equipment and service logs in the energy production management system. On the one hand, we use log anomaly detection technology to realize the anomaly detection of single node and the generating of log anomaly alarm, On the other hand, we use rule reasoning technology to realize the analysis and tracing of log anomaly alarm. In addition, we combine with practical application, optimize the traditional rule matching algorithm, which improves the fault tolerance of the matching network, and gets better accuracy and efficiency of the algorithm. © 2023 IEEE.

关键词： Anomaly detection

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Sustainable materials systems for triboelectric nanogenerator

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SusMat 2024年第6期4卷 85-138页

作者： Yijun Hao Chuguo Zhang Wei Su Hongke Zhang Yong Qin Zhong Lin Wang Xiuhan Li School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijingChina State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijingChina School of Materials Science and Engineering Georgia Institute of TechnologyAtlantaGeorgiaUSA

Benefiting fromthe high sensitivity and electromechanical conversion efficiency,triboelectric nanogenerators(TENGs)are widely used in various fields of selfpowered sensing and mechanical energy harvesting,which have great potential for application in future smart Internet of *** development of sustainable triboelectric materials with high-performance has a vital impact on the construction of TENG devices that combine high-output performance and environmental friendliness,which have a positive impact on the sustainable development of *** review systematically and comprehensively summarizes the latest research work on TENG’s sustainable ***,an overall overview is provided based on the composition of the materials,including amino acids,polysaccharides,and synthetic polymer,and the representative research works are further classified and summarized in *** addition,the latest research progress of TENG with sustainable materials in the fields of self-powered sensing and mechanical energy harvesting applications is also ***,the overviews are provided for the various challenges in the current development of TENG’s sustainable material,and the related outlooks are offered on the corresponding development strategies and directions of this field in the future.

关键词： amino acids polysaccharides sustainable materials synthetic polymers triboelectric nanogenerators

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Feature Enhancement Method for Multimodal Nighttime Pedestrian Detection 7

Feature Enhancement Method for Multimodal Nighttime Pedestri...

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7th International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2023

作者： Wang, Yonggui Zhu, Zhongpan Li, Jian Wang, Zhipeng Chang, Qi He, Bin School of Electronic Information and Artificial Intelligence Shanxi University of Science & Technology Xi'an China College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9798350382877

Nighttime Pedestrian Detection in Low-Light Conditions poses a challenging task, as previous processing methods often introduced noise and limited model generalization due to the low image quality in low-light conditions. This study presents a feature enhancement algorithm tailored for multimodal nighttime pedestrian detection, harnessing the advantages of infrared and visible light data. Our approach utilizes an adaptive weight fusion algorithm and a spatial detail module for multimodal fusion and spatial detail feature extraction, respectively, to accomplish the nighttime pedestrian detection task. Experimental results demonstrate that our method, compared to the baseline algorithm, achieves performance improvements of 3.3%, 11.9%, and 4.5% on the LLVIP dataset. © 2023 IEEE.

关键词： Feature extraction

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TRGR: Transmissive RIS-aided Gait Recognition Through Walls

TRGR: Transmissive RIS-aided Gait Recognition Through Walls

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Huang, Yunlong Liu, Junshuo Zhang, Jianan Mi, Tiebin Shi, Xin Qiu, Robert Caiming Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan China North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9798350351255

Gait recognition with radio frequency (RF) signals enables many potential applications requiring accurate identification. However, current systems require individuals to be within a line-of-sight (LOS) environment and struggle with low signal-to-noise ratio (SNR) when signals traverse concrete and thick walls. To address these challenges, we present TRGR, a novel transmissive reconfigurable intelligent surface (RIS)-aided gait recognition system. TRGR can recognize human identities through walls using only the magnitude measurements of channel state information (CSI) from a pair of transceivers. Specifically, by leveraging transmissive RIS alongside a configuration alternating optimization algorithm, TRGR enhances wall penetration and signal quality, enabling accurate gait recognition. Furthermore, a residual convolution network (RCNN) is proposed as the backbone network to learn robust human information. Experimental results confirm the efficacy of transmissive RIS, highlighting the significant potential of transmissive RIS in enhancing RF-based gait recognition systems. Extensive experiment results show that TRGR achieves an average accuracy of 97.88% in identifying persons when signals traverse concrete walls, demonstrating the effectiveness and robustness of TRGR. © 2024 IEEE.

关键词： Channel state information

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Event-Based Adaptive control for MIMO Nonlinear Systems Against Deception Attacks via a Single Parameter Learning Method 7th

Event-Based Adaptive Control for MIMO Nonlinear Systems Aga...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Tian, Yongjie Zhao, Ning Zhao, Xudong College of Control Science and Engineering Bohai University Jinzhou121013 China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Liaoning Dalian116024 China

ISBN: (纸本)9789819733279

This article proposes an adaptive neural network (NN) control scheme for MIMO nonlinear systems with unknown deception attacks. Based on the dynamic surface technology and the backstepping method, the unknown term composed of the sensor attack signals, the error term generated by NN and the disturbance can be regarded as an uncertain parameter. In addition, by combining the adaptive technology with the single parameter learning method (SPLM), the uncertain parameter will be transformed into a linear parameterized form with only one unknown uncertain parameter, thereby significantly reducing the computational complexity in the recursive process. Furthermore, the event-triggered control strategy with dynamic characteristics can be integrated into the control design to reduce the transmission of data. Theoretical analysis demonstrates that the proposed control algorithm ensures boundedness of all signals in the closed-loop system, and the Zeno phenomenon is eliminated. Ultimately, a numerical simulation is employed to validate the effectiveness of the proposed NN adaptive control scheme. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Closed loop systems

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An Efficient Bidirectional Weighted Global Feature Extraction Algorithm for Steel Surface Defects

An Efficient Bidirectional Weighted Global Feature Extractio...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Taoyuan Xie, Gang Xie, Xinlin Li, Linjuan Zhang, Haoxue Liang, Yu School of Electronic Information Engineering Taiyuan University of Science and Technology Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan China

ISBN: (纸本)9798350303759

Focus on the drawbacks of slow detection speed, and poor detection accuracy for small objects in existing strip steel surface defect detection methods, we propose an efficient bidirectional weighted global feature extraction algorithm for steel surface defects. Firstly, the backbone feature extraction network is consisted of BNCSP-TR(BottleNeckCSP with transformer) blocks to enhance global information and optimize the extraction ability of small object features. Secondly, the enhancement in the network's accuracy for detecting small-sized defects is achieved through the design of BiFPN-Light (lightweight bidirectional weighted feature pyramid network) for multi-scale feature fusion. Finally, a more efficient and concise decoupled detection head called Eff-DcHead is designed to solve the contradiction between classification tasks and regression tasks. Extensive experimental results illustrate that the mAP of our algorithm on NEU-DET reaches 82.4%, which is 4.1% higher than the original algorithm. Simultaneously, the algorithm achieves a detection speed of 92.1 FPS, catering to the demands of industrial environments. © 2023 IEEE.

关键词： Surface defects

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Multi-Path Spatial Detail-Aware Network for Semantic Segmentation

Multi-Path Spatial Detail-Aware Network for Semantic Segment...

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2023 China Automation Congress, CAC 2023

作者： Wang, Quanyi Xie, Xinlin Si, Haoyue Wang, Jianan Fang, Liang Xie, Gang School of Electronic Information Engineering Shanxi Key Laboratory of Advanced Control and Equipment Intelligence Taiyuan University of Science and Technology Taiyuan China

ISBN: (纸本)9798350303759

In the existing semantic segmentation, small objects and slender strip objects that are easy to blend into the surrounding background are generally difficult to be accurately identified and segmented. We propose a Multi-Path Spatial Detail-Aware Network (MSDNet) for semantic segmentation of traffic scenes. Specifically, an interactive Dual-branch Parallel Complementary module (DPC) based on the Transformer-CNN framework is firstly proposed to enhance the discriminative representation of similar feature encodings between different objects. Then, a spatial detail assistant module (SDA) with attention mechanism is designed to help the network obtain more detailed spatial detail information. Moreover, a Cross-layer Feature Aggregation module (CFA) is constructed for further aligning and aggregating feature maps of different resolutions in adjacent two layers, which can improve the segmentation performance of small objects. Extensive experimental results show that the proposed method achieves the accuracy of 81.16% mean Intersection over Union (mIoU) on the challenging Cityscapes dataset. © 2023 IEEE.

关键词： Semantic Segmentation

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Intensive Electromagnetic Target Association based on Multi-dimensional Characteristics Fuzzy Weighted Algorithm

Intensive Electromagnetic Target Association based on Multi-...

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International Conference on electronic Engineering and Informatics (EEI)

作者： Ye Du Qilun Yang Xuying Zhang Yuan Zuo Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In order to improve the intensive electromagnetic target association requirement for electronic reconnaissance, the multi-dimensional characteristics fuzzy weighted algorithm is proposed in this paper. On the basis of the signal deinterleaving, each dimensional electromagnetic parameter is carried out by nonlinear Euclid distance as the degree of membership firstly, and then the membership degree of different electromagnetic parameters is fuzzy weighted, finally the electromagnetic target is tracked based on the weighted membership. The simulation demonstrates that the proposed algorithm can track the intensive target with interlocking electromagnetic parameters accurately, and it has good robustness to the parameters of algorithm.

关键词： Radio frequency Target tracking Accuracy Reconnaissance Robustness Time measurement Electromagnetics Informatics

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Collision-Free Formation control of Multi-agent System with Low Oscillation 7th

Collision-Free Formation Control of Multi-agent System with ...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Li, Jingyi Han, Haoran Lv, Maolong Sun, Chenyang Cheng, Jian Glassgow School University of Electronic Science and Technology of China Chengdu611731 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Air Traffic Control and Navigation College Air Force Engineering University Xian710051 China

ISBN: (纸本)9789819733279

In recent years, multi-agent systems are becoming more complex, scalable, adaptive, and integrating machine learning for enhanced capabilities. A popular approach for addressing this challenge involves the utilisation of artificial potential functions (APF). In this article, we address the problem of obstacle avoidance and achieving a predefined formation, particularly promoting smooth trajectory generation in multi-agent formation control. We employ the APF method to enhance the smoothness of the agents’ movement paths during these tasks. Collision damping terms are generated by differentiating the gradient of APF with respect to time. Incorporating generated damping terms in the APF control, we suppress irregular fluctuations during agents’ motion procedures. To ensure stability in the multi-agent system, we design an energy-based Lyapunov function and utilise it for proof. Simulation examples are presented to validate the theoretical results and demonstrate the advantages of the proposed control algorithm. Through these simulations, it becomes evident that the collision-free formation control algorithm enhances the smoothness of the agents’ trajectories. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Radar Signal Modulation Recognition based on Multi-scale Self-correlation Combined with Layered Convolution-GRU Network

Radar Signal Modulation Recognition based on Multi-scale Sel...

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International Conference on electronic Engineering and Informatics (EEI)

作者： Qilun Yang Xuying Zhang Ye Du Yuan Zuo Science and Technology on Electronic Information Control Laboratory Chengdu China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

In order to satisfy the modulation recognition requirements for radar signal with agility pulse-width, bandwidth and modulation type, the multi-scale self-correlation combined with layered convolution-GRU network is proposed in this paper. First, the waveform is processed by multi-scale self-correlation with different accumulation points to obtain the time-amplitude and time-frequency information; Second, the local characteristics were extracted by layered convolution network respectively; Lastly, the local characteristics of each self-correlation are integrated, and the GRU network is adopted to extract the serialization representation. The proposed network combines the advantages of local characteristics of CNN and the sequence characteristics of GRU. The simulation shows that the modulation recognition accuracy is more than 95.4% over the detection sensitivity for normal, LFM, NLFM, FSK, BPSK, QPSK signals.

关键词： Time-frequency analysis Sensitivity Accuracy Convolution Modulation Radar Frequency shift keying Bandwidth Binary phase shift keying Data mining

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