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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Qiao, Qi Wang, Hongjun School of Mechanical Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Beijing International Science Cooperation Base of High-End Equipment Intelligent Perception Beijing100192 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100192 China

ISBN: (纸本)9783031494208

Aiming at the problems of difficulty in fault data collection and scarcity of fault samples in gas turbine rotor fault diagnosis, a gas turbine rotor fault diagnosis model based on VIT model and transfer learning is proposed. Firstly, the acquired one-dimensional vibration signal is converted into a two-dimensional time–frequency image by continuous wavelet transformation as the input of the VIT model, and the fault diagnosis is realized through its recognition of time–frequency image and feature extraction. Using CRWU bearing dataset to pre-train the model combined with transfer learning, only the weights in the MLP Head structure are migrated by freezing the part before the MLP Head structure and using the gas turbine rotor dataset fault classification, the results show that the fault recognition accuracy reaches 99.5% after transfer learning, and the superiority of the proposed model is proved by comparative experiments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Failure analysis

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RGBD-SLAM Algorithm Based on Semantic Segmentation and Background Restoration in Dynamic Scenes

RGBD-SLAM Algorithm Based on Semantic Segmentation and Backg...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Hangrong Guo Runbang Qian Mengyuan Chen Guangqiang Gong Hao Cheng School of Electrical Engineering AnHui Polytechnic University Wuhu China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Wuhu China

To address the problem that RGBD-SLAM algorithm is difficult to effectively identify dynamic objects affecting trajectory accuracy in dynamic scenarios, improved a novel RGBD-SLAM algorithm based on Semantic segmentation and Background repair in dynamic scenarios (ISB-SLAM). This algorithm accurately marks potential dynamic objects by designing a semantic analysis module with a fusion of class embedding, decoder and patch coding to analyze the global linkage of the marked target regions and also output the analyzed target regions in categories. To reduce the impact of dynamic objects on the localization accuracy of the SLAM system, dynamic objects are judged and eliminated by multi-view geometry. The static background of the rejection region is complemented according to the multi-frame grid mapping method, which provides good feature information for SLAM map building. The experimental results show that the algorithm improves the trajectory accuracy and has a good composition capability in the public datasets TUM and BONN.

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Anomaly Detection of Logistics Packages Based on CNN and Image Recognition Technology 4

Anomaly Detection of Logistics Packages Based on CNN and Ima...

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4th IEEE International Conference on Data Science and Computer Application, ICDSCA 2024

作者： Liang, Kun Zhang, Hang School of Management Tianjin University of Technology Tianjin China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350368239

To address abnormal situations such as packaging damage, liquid leakage, and item displacement during logistics package transportation, this paper introduces Convolutional Neural Network (CNN) and image recognition technology to achieve real-time anomaly detection and alarm, improving the response speed and accuracy of the logistics system. First, by designing multiple layers of convolution and pooling layers, adding Batch Normalization layers and Dropout layers to prevent overfitting, a CNN deep learning model suitable for logistics package anomaly detection is constructed. key features are extracted through image preprocessing methods such as normalization and data enhancement to ensure that the model has high recognition adaptability to various abnormal situations such as damage and leakage. Secondly, through data enhancement methods such as rotation, scaling, brightness adjustment, and transfer learning using pre-trained models, the model's adaptability in different lighting, angles, and occlusion conditions is improved. Finally, the model is applied to actual monitoring, and real-time alarms are issued for abnormalities such as damage and leakage, which are then fed back to the system closed-loop management. This method is significantly better than traditional methods in terms of detection accuracy and response speed. Under natural light environment, the model detection accuracy is as high as 98.4%, reducing false positives and false negatives. Combining CNN's anomaly detection technology effectively improves the accuracy and efficiency of logistics monitoring and provides technical support for intelligent logistics management. ©2024 IEEE.

关键词： Convolutional neural networks

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Multi-scale Object Detection Algorithm Based on Adaptive Feature Fusion 16th

Multi-scale Object Detection Algorithm Based on Adaptive Fea...

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16th Chinese Conference on Biometric Recognition, CCBR 2022

作者： Xu, Yue Wang, Fengsui Xie, Zhenglei Wang, Yunlong School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Anhui Key Laboratory of Detection Technology and Energy Saving Devices Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Wuhu241000 China

ISBN: (纸本)9783031202322

Aiming at the problem that each detection feature layer of the single-shot multibox detector (SSD) algorithm does not perform feature fusion and the detection effect is poor, an adaptive feature fusion SSD model is proposed. Firstly, the location of the shallow feature map and the multi-scale receptive field on the deep feature map are added, and the scaling and adaptive fusion of different scale feature maps are carried out to improve the representation ability of detail information. Secondly, the feature layer of the same scale can provide different ranges of feature information, transfer the specific features with detailed information to the abstract features with semantic information, and use the global average pool to guide learning and expand the expression ability of features. After training and testing on the PASCAL VOC data set, the detection accuracy reaches 80.6% and the detection speed reaches 60.9 fps, which verifies the robustness and real-time performance of the algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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Fast PL-SLAM Algorithm Based on Improved keyframe Extraction Strategy

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2022年第3期50卷 608-618页

作者： Chen, Meng-Yuan Ding, Ling-Mei Zhang, Yu-Kun School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High‑end Equipment Wuhu241000 China

To address the problems that PL-SLAM(Point and Line Simultaneous Localization And Mapping) algorithm uses point and line features at the same time in dense scenes, which cause redundancy in feature calculation, and misses keyframe selection during curve motion, an IFPL-SLAM(Improved keyframe extraction strategy-based Fast PL-SLAM) algorithm is proposed. The algorithm introduces an information entropy-guided bit tracking decision, evaluates the priority extracted feature points using information entropy, and decides the fusion of point and line features based on the evaluation results, which avoids data redundancy caused by the simultaneous use of point and line features in dense texture scenes and improves the real-time performance of the algorithm. At the same time, in order to avoid missing keyframes during curve motion, the inverse index keyframe selection strategy is used to supplement the keyframes missed during curve motion, which improves the accuracy and positioning precision of the closed loop. The test results on the publicly available KITTI dataset and TUM dataset show that the running time of the algorithm proposed is reduced by 16.0% compared to the PL-SLAM algorithm, and the localization accuracy is increased by 23.4% compared to PL-SLAM, which exhibits a good mapping capability. © 2022, Chinese Institute of Electronics. All right reserved.

关键词： Redundancy

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Optical sorting:past,present and future

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光：科学与应用（英文版） 2025年第5期14卷 1188-1234页

作者： Meng Yang Yuzhi Shi Qinghua Song Zeyong Wei Xiong Dun Zhiming Wang Zhanshan Wang Cheng-Wei Qiu Hui Zhang Xinbin Cheng Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China MOE Key Laboratory of Advanced Micro-Structured Materials Shanghai 200092China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China Shanghai Frontiers Science Center of Digital Optics Shanghai 200092China Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore

Optical sorting combines optical tweezers with diverse techniques,including optical spectrum,artificial intelligence(AI)and immunoassay,to endow unprecedented capabilities in particle *** comparison to other methods such as microfluidics,acoustics and electrophoresis,optical sorting offers appreciable advantages in nanoscale precision,high resolution,non-invasiveness,and is becoming increasingly indispensable in fields of biophysics,chemistry,and materials *** review aims to offer a comprehensive overview of the history,development,and perspectives of various optical sorting techniques,categorised as passive and active sorting *** begin,we elucidate the fundamental physics and attributes of both conventional and exotic optical *** then explore sorting capabilities of active optical sorting,which fuses optical tweezers with a diversity of techniques,including Raman spectroscopy and machine ***,we reveal the essential roles played by deterministic light fields,configured with lens systems or metasurfaces,in the passive sorting of particles based on their varying sizes and shapes,sorting resolutions and *** conclude with our vision of the most promising and futuristic directions,including Al-facilitated ultrafast and bio-morphology-selective *** can be envisioned that optical sorting will inevitably become a revolutionary tool in scientific research and practical biomedical applications.

关键词： present future past optical sorting

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Fire detection method based on lightweight YOLOv4

Fire detection method based on lightweight YOLOv4

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2022 International Workshop on Automation, Control, and Communication engineering, IWACCE 2022

作者： Wang, Huilin Xu, Xiaoguang Hao, Xuyao Li, Mengnan Wang, Qi School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Anhui Polytechnic University Anhui Wuhu241000 China Anhui Wuhu241000 China

ISBN: (纸本)9781510660915

A fire detection model with improved YOLOv4 is proposed for mobile devices with limited computing resources and less accurate object localization. Firstly, the network model of YOLOv4 object detection algorithm is modified, and a depthwise separable convolution network is used instead of traditional convolution in the feature extraction network part to realize the lightweight of fire detection model. Then the Loss function is optimized to solve the problem of inaccurate object detection frame localization. The experimental results show that compared with YOLOv4, the improved algorithm reduces the model parameter by 60.7 % and the detection speed increases by 27.9 %. It is more favorable for the model to be equipped on mobile devices. © 2022 SPIE. All rights reserved.

关键词： Convolution

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Polarization‑entangled photon‑pair source with van der Waals 3R‑WS_(2) crystal

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eLight 2024年第1期4卷 99-106页

作者： Jiangang Feng Yun‑Kun Wu Ruihuan Duan Jun Wang Weijin Chen Jiazhang Qin Zheng Liu Guang‑Can Guo Xi‑Feng Ren Cheng‑Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Optical Science and Engineering and Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433China

Ultracompact entangled photon sources are pivotal to miniaturized quantum photonic *** der Waals(vdW)nonlinear crystals promise efficient photon-pair generation and on-chip monolithic integration with nanophotonic ***,it remains challenging to generate maximally entangled Bell states of photon pairs with high purity,generation rate,and fidelity required for practical ***,we realize a polarization-entangled photon-pair source based on spontaneous parametric down conversion in an ultrathin rhombohedral tungsten disulfide(3R-WS2)*** vdW entangled photonic source exhibits a high photon-pair purity with a coincidenceto-accidental ratio of above 800,a generation rate of 31 Hz,and two maximally polarization-entangled Bell states with fidelities exceeding 0.93 and entanglement degree over *** results stem from scalable optical nonlinearity,enhanced second-order susceptibility by electronic transitions,and a well-defined symmetry-enabled selection rule inherent in *** polarization entangled photon source can be integrated with photonic structures for generating more complex entangled states,thus paving an avenue for advanced quantum photonic systems toward computation and metrology.

关键词： purity maximal Polarization

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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A population randomization-based multi-objective genetic algorithm for gesture adaptation in human-robot interaction

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Science China(Information Sciences) 2021年第1期64卷 188-200页

作者： Luefeng CHEN Wanjuan SU Min LI Min WU Witold PEDRYCZ Kaoru HIROTA School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

In recent years, vision-based gesture adaptation has attracted great attention from many experts in the field of human-robot interaction, and many methods have been proposed and successfully applied, such as particle swarm optimization and genetic algorithm. However, the reduction of the error and energy consumption of a robot while paying attention to more subtle attitude changes is very important and *** view of these problems, we propose a population randomization-based multi-objective genetic *** gesture signal is processed with a slight change by imitating the biological evolution mechanisms. In the proposed algorithm, a random out-of-order matrix is added in the process of population evolution synthesis to prevent the premature grouping convergence of the new population. The weights of the objective function and the elite retention strategy are adopted, and the most adaptable individuals in each generation are inherited directly in the next generation without any recombination or mutation. To verify the effectiveness of the algorithm, preliminary application experiments are performed on the gesture adaptation of a robotic arm. The results are compared with the original signal, and the comparison shows that by using the proposed method, the energy consumption is reduced, and the end error is decreased to less than 3 mm while ensuring the tracking effect of the robotic arm. These obtained results meet the communication requirements for human-robot interactions such as handshakes. Moreover, the proposed method has better performance, uses less energy, and has a smaller tracking error than the particle swarm optimization, the single-objective genetic algorithm, and the traditional multi-objective genetic algorithm. A preliminary application experiment indicates that the robotic arm can adapt to human gestures in real time.

关键词： multi-objective genetic algorithm gesture adaptation human-robot interaction

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