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6th International Conference on System Reliability and Safety engineering, SRSE 2024

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

ISBN: (纸本)9798350356083

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. © 2024 IEEE.

关键词： Weibull distribution

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Data Security Storage Mechanism Based on Blockchain Network

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Computers, Materials & Continua 2023年第3期74卷 4933-4950页

作者： Jin Wang WeiOu Wenhai Wang RSimon Sherratt Yongjun Ren Xiaofeng Yu School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410004China School of Control Science and Engineering Zhejiang UniversityHangzhou310058China School of Systems Engineering The University of ReadingReadingRG66AYUK School of Computer Engineering Research Center of Digital Forensics of Ministry of EducationNanjing University of Information Science&TechnologyNanjing210044China School of Business Nanjing UniversityNanjing210093China

With the rapid development of information technology,the development of blockchain technology has also been deeply *** performing block verification in the blockchain network,if all transactions are verified on the chain,this will cause the accumulation of data on the chain,resulting in data storage *** the same time,the security of data is also challenged,which will put enormous pressure on the block,resulting in extremely low communication efficiency of the *** traditional blockchain system uses theMerkle Tree method to store *** verifying the integrity and correctness of the data,the amount of proof is large,and it is impossible to verify the data in batches.A large amount of data proof will greatly impact the verification efficiency,which will cause end-to-end communication delays and seriously affect the blockchain system’s stability,efficiency,and *** order to solve this problem,this paper proposes to replace the Merkle tree with polynomial commitments,which take advantage of the properties of polynomials to reduce the proof size and communication *** realizing the ingenious use of aggregated proof and smart contracts,the verification efficiency of blocks is improved,and the pressure of node communication is reduced.

关键词： Blockchain cryptographic commitment smart contract data storage

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Lighting control with Myo armband based on customized classifier

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The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 106-116页

作者： Jiang Yujian Yang Xue Zhang Junming Song Yang Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

This paper focuses on gesture recognition and interactive lighting *** collection of gesture data adopts the Myo armband to obtain surface electromyography(sEMG).Considering that many factors affect sEMG,a customized classifier based on user calibration data is used for gesture *** this paper,machine learning classifiers k-nearest neighbor(KNN),support vector machines(SVM),and naive Bayesian(NB)classifier,which can be used in small sample sets,are selected to classify four gesture *** performance of the three classifiers under different training parameters,different input features,including root mean square(RMS),mean absolute value(MAV),waveform length(WL),slope sign change(SSC)number,zero crossing(ZC)number,and variance(VAR)are tested,and different input channels are also *** results show that:The NB classifier,which assumes that the prior probability of features is polynomial distribution,has the best performance,reaching more than 95%***,an interactive stage lighting control system based on Myo armband gesture recognition is implemented.

关键词： Myo armband gesture recognition surface electromyography customized classifier lighting control

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A Method for Constructing an Olfactory Dataset Based on fNIRS 9

A Method for Constructing an Olfactory Dataset Based on fNIR...

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9th International Conference on Systems and Informatics, ICSAI 2023

作者： Li, Wei He, Haobo Li, Guang Kuang, Lidan Zhang, Jin Changsha University of Science and Technology School of Computer and Communication Engineering Changsha410076 China Zhejiang University School of Control Science and Engineering Hangzhou310027 China

ISBN: (纸本)9798350383706

Biomimetic olfaction models have been applied to various fields such as image recognition, text classification, electroencephalography (EEG) recognition, and spatio-temporal sequence prediction. However, the challenge of obtaining olfactory data complicates the construction of olfactory datasets, ultimately resulting in a scarcity of applications for biomimetic olfaction models in olfactory tasks. In this work, we begin by conducting a comprehensive comparison of existing biomimetic olfactory models from various aspects such as structure, degree of biomimicry, and performance. Following this, prefrontal lobe olfactory data from ten subjects were collected for three different odors using functional Near-Infrared Spectroscopy (fNIRS). Finally, the data underwent denoising through the use of various data processing methods, and the quantity of the olfactory dataset was expanded. The olfactory dataset constructed in this study can be used to evaluate the performance of biomimetic olfactory models in processing olfactory tasks, which may aid in advancing the development of these models in real-world olfactory applications. © 2023 IEEE.

关键词： Image recognition

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Zero-Sample Multiple Fault Diagnosis of Diesel Engine Based on Attribute Prediction 43

Zero-Sample Multiple Fault Diagnosis of Diesel Engine Based ...

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43rd Chinese control Conference, CCC 2024

作者： Su, Qian Lv, Xuantao Qiu, Zhengxing Liu, Zhenxing Wuhan University of Science and Technology Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan430081 China Wuhan University of Science and Technology School of Information Science and Engineering/School of Artificial Intelligence Wuhan430081 China Wuhan Maritime Communication Research Institute Wuhan430205 China

ISBN: (纸本)9789887581581

A zero-sample fault diagnosis method based on fuzzy fault feature representation for attribute prediction is proposed to address the challenge of insufficient fault data samples covering all types of multiple faults in actual diesel engine operations. Through simulation analysis of single and multiple fault operational states of diesel engines using AVL-boost ledR simulation software, along with the variation patterns of single fault thermodynamic parameters and the coupling patterns of multiple faults, category information for multiple fault diagnosis is provided. Gaussian membership functions are employed to describe fault features, and an SVM attribute trainer is established using single fault data to predict attribute values for multiple faults without data samples. The nearest neighbor search algorithm is utilized to infer the most suitable multiple fault category. Experimental results demonstrate that the proposed method exhibits excellent performance in the diagnosis of multiple fault in diesel engines, with a prediction accuracy of 96.62% for fault attributes and a final multiple fault diagnosis accuracy of 97.31%, thereby providing a basis for zero-sample multiple fault diagnosis in diesel engines. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Diesel engines

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Fixed-Time Consensus-Based Nash Equilibrium Seeking

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 267-269页

作者： Mengwei Sun Jian Liu Lu Ren Changyin Sun the Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the School of Artificial Intelligence and the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationAnhui UniversityHefei 230601China

Dear Editor,This letter examines the fixed-time stability of the Nash equilibrium(NE)in non-cooperative *** propose a consensus-based NE seeking algorithm for situations where players do not have perfect information and communicate via a topology *** proposed algorithm can achieve NE in a fixed time that does not depend on initial conditions and can be adjusted in advance.

关键词： Fixed seeking letter

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Multipath planning based on multimodal optimization slime mold algorithm

Multipath planning based on multimodal optimization slime mo...

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2024 International Conference on Culture-Oriented Science and technology, CoST 2024

作者： Gao, Luli Ren, Hui Communication University of China School of Information and Communication Engineering Bejing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Ministry of Culture and Tourism Bejing China Beijing Key Laboratory of Modern Entertainment Technology Communication University of China Bejing China

ISBN: (纸本)9798350380347

Multipath planning aims to find multiple optimal paths simultaneously, and its essence is a multimodal optimization problem. In recent years, swarm intelligence (SI) optimization algorithms have provided effective solutions for multimodal optimization. In this paper, the multimodal optimization slime mold algorithm (MOSMA) based on master-slave structure and local search strategy (LS) is proposed to solve multipath planning problems in small cultural complex. Firstly, a local search strategy is introduced to eliminate the influence of the 'centerbias' operator and improve the quality of solutions. Secondly, the master-salves structure is introduced to preserve the diversity of the population and enable it to simultaneously locate multiple solutions. Finally, the performance of MOSMA is analyzed on several multimodal functions, and an example of path planning in a small cultural complex is given. © 2024 IEEE.

关键词： Optimization algorithms

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Fault Diagnosis of Quadrotor UAV Propeller with Local-Global Attention-Based Graph Neural Networks 13

Fault Diagnosis of Quadrotor UAV Propeller with Local-Global...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wang, Zhiwei Liang, Shaojun Sun, Ye Yang, Yi Wang, Yanwei Zheng, Ying School of Artificial Intelligence and Automation Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China School of Ordnance Sergeant Army Engineering University Wuhan430075 China School of Mechanical & Electrical Engineering Wuhan Institute of Technology Wuhan430073 China

ISBN: (纸本)9798350361674

With the wide application of Quadrotor Unmanned Aerial Vehicles (QUAV) in military and civilian fields, its flight reliability problem has become a hot research topic. The propellers, which are the important components relating to the performance of QUAV, play a central role in safe flight. Traditional data-driven fault diagnosis methods of QUAV are based on Euclidean distance, which cannot effectively capture the interrelationship of multiple variables. In this paper, we treat the fault diagnosis of QUAV propeller as a node classification problem in non-Euclidean infinite dimensional space by introducing the method of Local-Global Attention-based Graph Neural Network (LGA-GNN). First, the graph topology is constructed using the KNN method based on the real flight log of the QUAV. Then, the local and global attention strategies are integrated to form a graph-based collaborative feature extraction model. Finally, a unified end-to-end fault diagnosis framework tailored for QUAV is proposed. In the experiment section, real flight data of QUAV with different propeller fault conditions are collected, and the effectiveness and superiority of the proposed method are verified by comparing with other methods based on real data. © 2024 IEEE.

关键词： Graph neural networks

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Research on Fault Prediction and Health Management of Power Supply Board Method Based on Mahalanobis Distance 43

Research on Fault Prediction and Health Management of Power ...

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43rd Chinese control Conference, CCC 2024

作者： Li, Jiaying Su, Qian Qiu, Zhengxing Zhao, Min Liu, Zhenxing Wuhan University of Science and Technology School of Information Science and Engineering School of Artificial Intelligence Wuhan430081 China Wuhan University of Science and Technology Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan430081 China Wuhan Maritime Communication Research Institute Wuhan430205 China

ISBN: (纸本)9789887581581

In recent years, with the widespread application of complex electronic systems in large aircraft, high-speed railways, and ocean-going vessels, research on fault prediction and health management of electronic systems has become increasingly important. Traditional fault detection techniques bring cumbersome detection processes, high maintenance costs, and economic losses caused by repairs. To address electronic system faults and health issues caused by load status, capacitor failure, and temperature effects in power supply boards, a feature extraction method based on probability density modeling is adopted to establish a health evaluation index for power supply boards, thereby achieving health assessment and fault prediction for electronic circuit boards. The proposed method in this paper can effectively reduce the frequency of periodic monitoring and maintenance, provide guidance for the production and ordering cycle of replacement parts, and avoid the occurrence of post-repair maintenance. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Electronic System Fault Detection Health Management Mahalanobis Distance

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3D Simulation and Leakage Detection Technique for Deep Foundation Pits Based on Electric Field 10

3D Simulation and Leakage Detection Technique for Deep Found...

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10th International Conference on Environmental and engineering Geophysics, ICEEG 2023

作者： Chen, Hui Chen, Yufeng Deng, Juzhi Gao, Jianglin Wang, Suo Yu, Hui Zhang, Guokun School of Geophysics and Measurement-control Technology East China University of Technology Jiangxi Nanchang China Jiangxi Academy of Water Science and Engineering Jiangxi Nanchang China

To solve the problems of poor accuracy, poor anti-interference ability and unclear distribution of leakage electric field response characteristics of the traditional ground DC method for leakage detection of underground diaphragm walls in foundation pits, this paper proposes a deep foundation pit leakage detection technology based on the electric field. Secondly, it constructed the multi-field coupling equations and boundary conditions of the leakage electric field coupled with the leakage flow field and ion diffusion field, and then realized the three-dimensional forward evolution of the leakage electric field of the pit using the nonstructural mesh dissection method and the finite-element-infinite-element discretization method. Finally, physical model experiments and numerical simulations are used to confirm the reliability and accuracy of the foundation pit leakage detection technology and system. The results shows that monitoring the continuous change of the electric field for a period of time, the electric field detection technology for foundation pit leakage can effectively identify the location of hidden leakage and overcome the site's strong industrial interference, resulting in a new technical solution for foundation pit leakage detection. © Published under licence by IOP Publishing Ltd.

关键词： Electric fields

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