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

作者： Ouyang, Bing Zhang, Chao Wu, Le Liu, Guiyi Wu, Yangbiao Xu, Shuai School of Mechanical Engineering Inner Monglia University of Science and Technology Baotou014010 China Inner Monglia Key Laboratory of Intelligent Diagnosis and Control of Mechatronic System Baotou014010 China

ISBN: (纸本)9783031734069

This paper presents a novel solution for bearing fault diagnosis based on a Broad Learning System with multi-domain feature selection. Currently, the diagnosis of bearing faults is beset with numerous challenges, including operation under complex and fluctuating conditions, the subtlety of early fault indicators, noise interference in measurement signals, variations in operational conditions, and a broad spectrum of potential fault types. These factors collectively contribute to the complexity of accurately identifying and classifying bearing faults. The Broad Learning System introduced in this paper, by integrating multi-domain feature selection, enhances the model's capability to extract and utilize relevant features from noisy or incomplete data, potentially increasing diagnostic accuracy in suboptimal sensor environments. By leveraging features across multiple domains, the method based on the Broad Learning System can capture a wider array of fault characteristics, thereby broadening its applicability across various types of bearing faults and operational conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Roller bearings

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SMTC-CL: Continuous Learning via Selective Multi-Task Coordination for Adaptive Signal Classification

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IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1664-1681页

作者： Hao, Xiaoyang Yang, Shuyuan Liu, Ruoyu Feng, Zhixi Peng, Tongqing Huang, Bincheng Xidian University Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education School of Artificial Intelligence Xi'an710071 China Avic Xi'an Flight Automatic Control Research Institute China MeiTuan China China Electronics Technology Group Corporation Institute of Information Science and Technology China

Continuously adaptive signal classification in complex electromagnetic environments is a desired property of realistic intelligent systems. However, the limitation of most existing signal processing tasks and methods lies in their assumption of fixed categories and invariant distributions. In contrast, humans naturally acquire knowledge continuously from data streams, enhancing their capabilities through cross-task knowledge integration and learning from the past. Inspired by this, we propose a continuous learning (CL) method based on selective multi-task coordination (SMTC) to deal with ever-changing task categories and distributions in practical electromagnetic environments (denoted as SMTC-CL). Firstly, we propose a signal task distribution comparison (TDC) method that leverages intra-domain density and inter-domain divergence. TDC selectively activates multiple old tasks to collaboration with the current incremental new task. Secondly, we propose the SMTC method. By revisiting potential collaborative tasks from the past using TDC and formulating different selection strategies based on the context, continuous learners can achieve mutual benefits between past and current tasks in SMTC learning. SMTC can partially alleviate catastrophic forgetting and enable continuous learners to adapt to the changing electromagnetic environment. Based on the signal automatic modulation classification (AMC) and real-world specific emitter identification (SEI) datasets, extensive experimental results validate the effectiveness of our proposed method on a variety of CL scenarios, including varying signal task categories, distributions, and their combinations. © 2015 IEEE.

关键词： Contrastive Learning

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A spintronic memristive circuit on the optimized RBF-MLP neural network

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Chinese Physics B 2022年第11期31卷 272-283页

作者： Yuan Ge Jie Li Wenwu Jiang Lidan Wang Shukai Duan School of Artificial Intelligence Southwest UniversityChongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China

A radial basis function network(RBF)has excellent generalization ability and approximation accuracy when its parameters are set ***,when relying only on traditional methods,it is difficult to obtain optimal network parameters and construct a stable model as *** view of this,a novel radial basis neural network(RBF-MLP)is proposed in this *** connecting two networks to work cooperatively,the RBF’s parameters can be adjusted adaptively by the structure of the multi-layer perceptron(MLP)to realize the effect of the backpropagation updating ***,a genetic algorithm is used to optimize the network’s hidden layer to confirm the optimal neurons(basis function)number *** addition,a memristive circuit model is proposed to realize the neural network’s operation based on the characteristics of spin *** is verified that the network can adaptively construct a network model with outstanding robustness and can stably achieve 98.33%accuracy in the processing of the Modified National Institute of Standards and technology(MNIST)dataset classification *** experimental results show that the method has considerable application value.

关键词： radial basis function network(RBF) genetic algorithm spintronic memristor memristive circuit

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Knowledge Graph-Based Image Recognition Transfer Learning Method for On-Orbit Service Manipulation

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space(science & technology) 2021年第1期2021卷 164-172页

作者： Ao Chen Yongchun Xie Yong Wang Linfeng Li Beijing Institute of Control Engineering BeijingChina Science and Technology on Space Intelligent Control Laboratory BeijingChina

Visual perception provides state information of current manipulation scene for control system,which plays an important role in on-orbit service *** the development of deep learning,deep convolutional neural networks(CNNs)have achieved many successful applications in the field of visual *** CNNs are only effective for the application condition containing a large number of training data with the same distribution as the test data;however,real space images are difficult to obtain during large-scale ***,deep CNNs can not be directly adopted for image recognition in the task of on-orbit service *** order to solve the problem of few-shot learning mentioned above,this paper proposes a knowledge graph-based image recognition transfer learning method(KGTL),which learns from training dataset containing dense source domain data and sparse target domain data,and can be transferred to the test dataset containing large number of data collected from target *** average recognition precision of the proposed method is 80.5%,and the average recall is 83.5%,which is higher than that of ResNet50-FC;the average precision is 60.2%,and the average recall is 67.5%.The proposed method significantly improves the training efficiency of the network and the generalization performance of the model.

关键词： Service Visual manipulation

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Memristor-based multi-synaptic spiking neuron circuit for spiking neural network

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Chinese Physics B 2022年第4期31卷 225-233页

作者： Wenwu Jiang Jie Li Hongbo Liu Xicong Qian Yuan Ge Lidan Wang Shukai Duan College of Artificial Intelligence Southwest UniversityChongqing 400715China National&Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing 400715China Brain-inspired Computing and Intelligent Control of Chongqing Key Laboratory Chongqing 400715China Chongqing Brain Science Collaborative Innovation Center Chongqing 400715China

Spiking neural networks(SNNs) are widely used in many fields because they work closer to biological ***,due to its computational complexity,many SNNs implementations are limited to computer ***,this paper proposes a multi-synaptic circuit(MSC) based on memristor,which realizes the multi-synapse connection between neurons and the multi-delay transmission of pulse *** synapse circuit participates in the calculation of the network while transmitting the pulse signal,and completes the complex calculations on the software with ***,a new spiking neuron circuit based on the leaky integrate-and-fire(LIF) model is designed in this *** amplitude and width of the pulse emitted by the spiking neuron circuit can be adjusted as *** combination of spiking neuron circuit and MSC forms the multi-synaptic spiking neuron(MSSN).The MSSN was simulated in PSPICE and the expected result was obtained,which verified the feasibility of the ***,a small SNN was designed based on the mathematical model of *** the SNN is trained and optimized,it obtains a good accuracy in the classification of the IRIS-dataset,which verifies the practicability of the design in the network.

关键词： memristor multi-synaptic circuit spiking neuron spiking neural network(SNN)

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Hand medical monitoring system based on machine learning and optimal EMG feature set

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Personal and Ubiquitous Computing 2023年第6期27卷 1991-2007页

作者： Yu, Mingchao Li, Gongfa Jiang, Du Jiang, Guozhang Tao, Bo Chen, Disi Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China Precision Manufacturing Research Institute Wuhan University of Science and Technology Wuhan430081 China Research Center of Biologic Manipulator and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China 3D Printing and Intelligent Manufacturing Engineering Institute Wuhan University of Science and Technology Wuhan430081 China School of Computing University of Portsmouth PortsmouthPO1 3HE United Kingdom

Considering that serious hand function damage will greatly affect the daily life of patients, its recovery mainly depends on the regular inspection and manual training of medical staff, and medical monitoring based on bioelectric signals can largely replace manual re-examination as autonomous rehabilitation technology. So, for the rationality of feature selection and the diversity of classifier design in the gesture recognition process based on electromyography (EMG) signals, this paper proposes a hand medical monitoring system based on feature selection method of feature subset average recognition rate and optimal machine learning algorithm selection, which mainly depends on the prediction of hand movement. At the same time, since most experiments are conducted in different non-public proprietary databases, the comparison between various gesture recognition methods can only be analyzed to a certain extent. Therefore, this paper uses the DB1 dataset in the large publicly available NinaPro database and combines with presently well-known 11 time-domain (TD) features and 5 frequency domain (FD) features, then uses the support vector machine (SVM) classifier to comparative analysis total 136 feature combinations under various feature numbers. Under the premise of ensuring the overall recognition rate of electromyography gesture, this method will be able to reduce the number of features in feature set, according to the change of the average remove redundant features, and construct an optimal reduced EMG feature set. Finally, through the four common hand motion classifiers based on machine learning: SVM, back propagation neural network, linear discriminant analysis, and K-nearest neighbor, this paper tests and verifies the separability of the optimal reduced EMG feature set, and based on this, selects the optimal hand motion classifier to build the optimal hand motion recognition system, improve the hand medical monitoring system, and provide technical reference for the c

关键词： Discriminant analysis

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A time-coded multi-concentration microfluidic chemical waveform generator for high-throughput probing suspension single-cell signaling

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Chinese Chemical Letters 2022年第6期33卷 3091-3096页

作者： Yiran Guo Peng Chen Zhaolong Gao Yiwei Li Shunji Li Xiaojun Feng Bi-Feng Liu The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics and Molecular Imaging Key Laboratory Systems Biology ThemeDepartment of Biomedical EngineeringCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

The cellular response to the complex extracellular microenvironment is highly dynamic in time and type of extracellular *** reconstructing this process and analyzing the changes in receptor conformation on the cell membrane surface and intracellular or intercellular signaling has been a major challenge in analytical chemistry and biophysical *** this paper,a time-coded multiconcentration microfluidic chemical waveform generator was developed for the dynamic signaling probing with single-cell array of high temporal resolution,high throughput,and multi-concentration combination *** on innovative microchannel structure,sophisticated external control methods and multiplexing technology,the system not only allowed for temporally sequential permutations of the four concentrations of stimuli(time code),but also generated pulsed and continuous waveforms at different frequencies in a highly controllable ***,the single-cell trap array was set up to efficiently capture cells in suspension,dramatically increasing throughput and reducing experiment preparation *** maximum frequency of the platform was 1 Hz,and one cell could be stimulated at multiple *** show the ability of the system to investigate rapid biochemical events in high throughput,pulse stimulation and continuous stimulation of different frequencies and different time codes,combined with four concentrations of histamine(HA),were generated for probing G protein-coupled receptor(GPCR)signaling in He La ***,statistical analysis was performed for the mean peak height and mean peak area of the cellular *** believe that the time-coded multi-concentration microfluidic chemical waveform generator will provide a novel strategy for analytical chemistry,biophysics,cell signaling,and individualized medicine applications.

关键词： Microfluidics Dynamic stimulation Time code High-throughput Single-cell array

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Energy management of solid oxide fuel cell/lithium battery hybrid system

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CSEE Journal of Power and Energy Systems 2022年 1-14页

作者： Li, Dong Zhong, Xiao Bo Xu, Yuan Wu Wei, Chong Yang Zhao, Song Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

The research of fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However, the lower efficiency of energy management has been a critical factor that obstruct the commercialization of hybrid system. In this work, based on finite element ideas, a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for lithium battery, previous energy management studies generally only focused on state of charge, however, state of health is also a key parameter for lithium battery. In this paper, considering the strong coupling between variables we use particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system, a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally, our algorithm is verified by Dspace simulation platform. The result shows that the hybrid system with the energy management strategy not only meets the real-time sharply changing demand but also ensures the hybrid system working efficiently and safely. © 2022 China Electric Power Research Institute. All rights reserved.

关键词： Hybrid systems

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Autonomous picking robot for elongated fruits and vegetables 3

Autonomous picking robot for elongated fruits and vegetables

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3rd International Conference on Electrical, Electronics, and Information Engineering, EEIE 2024

作者： Gao, Yang Shuai, Wei Cui, Guowei Wu, Peichen Gan, Lin Chen, Xiaoping Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Foshan Industrial Technology Research Institute Guangdong Academy of Sciences China School of Computer Science and Technology University of Science and Technology of China Hefei230026 China

ISBN: (纸本)9781510688179

This paper presents the design and implementation of an autonomous picking robot specifically for harvesting elongated fruits such as loofahs and bitter melons. The robot utilizes a tracked chassis to navigate field terrains, equipped with IMU and GNSS modules for navigation and positioning. Mounted on the chassis is a 6-degree-of-freedom robotic arm designed for picking actions, with a combination of a flexible gripper and electric scissors at its end to enhance picking efficiency and safety. Two RGBD cameras are used for global and local perception, while the YOLO model is employed for fruit recognition and localization. Experimental results demonstrate that the robot can complete a full picking cycle in an average of 20 seconds and temporarily store the harvested fruits in an onboard storage bin. Overall, this picking robot significantly reduces labor costs and improves the efficiency and quality of field operations and fruit harvesting. © The Authors.

关键词： Grippers

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Optimal Cooperative Secondary control for Islanded DC Microgrids via a Fully Actuated Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 405-417页

作者： Yi Yu Guo-Ping Liu Yi Huang Peng Shi IEEE Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and TechnologyShenzhen 518055China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China School of Electrical and Mechanical Engineering the University of AdelaideSA 5005Australia Research and Innovation Centre Obuda University1034 BudapestHungary

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

关键词： DC microgrids distributed control high-order fully actuated system approach linear quadratic regulator microgrid modeling secondary control

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