检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

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 ...

引用

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

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Networks with Constrained Shortcut Connections 5

Convolutional Neural Networks with Constrained Shortcut Conn...

引用

5th International Conference on Computer Information Science and Application technology, CISAT 2022

作者： Du, Qiyan Zhang, Tao Department of Measurement Technology and Control Engineering School of Mechanical Engineering Sichuan University Chengdu610065 China

ISBN: (纸本)9781510660076

This paper proposes a novel network architecture to integrate features in the shallow and the deep layers. The architecture is composed of three components, including the shortcut connection, global representation operator, and regularizer. The shortcut connection alleviates the vanishing gradient problem by feeding features from the hidden layer to the classifier in the last layer. The global representation operator aims to reduce the features' dimension to mitigate the over-fitting problem. The regularizer is designed to relieve the degradation of network depth which might be caused by the shortcut connection. The results on Optical Coherence tomography (OCT) show that the proposed architecture is an effective regularization method that can mitigate the over-fitting problem. © 2022 SPIE.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Bimodal Fusion Network for Basic Taste Sensation Recognition from Electroencephalography and Electromyography 48

Bimodal Fusion Network for Basic Taste Sensation Recognition...

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Gao, Han Zhao, Shuo Li, Huiyan Liu, Li Wang, You Hu, Ruifen Zhang, Jin Li, Guang Zhejiang University State Key Laboratory of Industrial Control Technology China Changsha University of Science and Technology School of Computer and Communication Engineering China

ISBN: (纸本)9781728163277

Taste sensation can be objectively measured using electroencephalography (EEG) or electromyography (EMG). How-ever, it is still challenging to effectively utilize the complementary information from EEG and EMG signals in taste sensation recognition. This paper proposes a bimodal fusion network (Bi-FusionNet) for recognizing basic taste sensations (sour, sweet, bitter, salty, umami, and blank). Two convolutional backbones with similar structures are designed to separately extract the single-modal features of EEG and EMG. Then, EEG and EMG features are concatenated for bimodal interaction and complementarity. Finally, three loss functions are adopted: a center loss for aggregating intra-class samples, a mean squared error loss for sequence positions for minimizing the difference between signals during the stimulation, and a softmax loss for minimizing the entropy of prediction and true labels. The results on the taste sensation dataset show that bimodal fusion improves recognition performance, and Bi-FusionNet outperforms single-modal methods and other fusion methods. Bi-FusionNet paves the way for the application of multimodal fusion in taste sensation recognition. © 2023 IEEE.

关键词： Electroencephalography Electromyography Feature Fusion Taste Sensation Recognition

来源：评论

学校读者我要写书评

暂无评论

High-fidelity parametric amplification of Ince–Gaussian beams

引用

Chinese Optics Letters 2022年第11期20卷 105-109页

作者： Ding Yan Zhiyuan Zhong Tong Qi Hongying Chen Wei Gao Heilongjiang Provincial Key Laboratory of Quantum Control School of Measurement and Communication EngineeringHarbin University of Science and TechnologyHarbin 150080China

Ince–Gaussian (IG) beams, as eigenfunctions of the paraxial wave equation in elliptical coordinates, are attracting increasing interest owing to their propagation-invariant and full-field properties. Optical amplification via parametric interactions can further expand their application areas, yet it is rarely studied. In this work, we report on a high-fidelity parametric amplifier for IG beams. The nonlinear transformation of the spatial spectra of the signal and associated influences on the beam profiles of the amplified signal, under different pump structures, were theoretically and experimentally investigated. By using a perfect flattop beam as the pump, we show that the transverse structure of IG signals is well maintained,and the distortion induced by radial-mode degeneration is overcome during amplification. This proof-of-principle demonstration paves the way for a mode-independent and distortion-free amplifier of arbitrary structured light and has great significance in relevant areas, such as quantum optics, tunable infrared-laser generation, and image amplification.

关键词： optical parametric amplification Ince–Gaussian beam high fidelity perfect flattop beam

来源：评论

学校读者我要写书评

暂无评论

The Battery Management System With DNN Deployed in STM32

The Battery Management System With DNN Deployed in STM32

引用

2024 China Automation Congress, CAC 2024

作者： Liang, Dongfeng Xiong, Ling Li, Wei Xiao, Ji School of Information Science and Engineering Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan China Wuhan University of Science and Technology Electronic Control Equipment Co. Ltd Wuhan China

ISBN: (纸本)9798350368604

Accurate prediction of the state of charge (SOC) is crucial for extending the lifespan of batteries. While traditional ampere-hour integration methods are simple and practical, they suffer from large cumulative errors and are not well-suited for complex application scenarios. This paper presents a smart battery management system based on the STM32F407VET6 microcontroller, which incorporates a deep neural network (DNN) to effectively model the nonlinear relationship between key parameters such as current, voltage, and SOC. The system features autonomous operation without requiring a host computer, enabling precise measurement of remaining battery capacity and real-time data display on an OLED screen. Furthermore, it supports data transmission in industrial environments via an RS485 module using the Modbus RTU protocol, as well as communication through CAN bus and ESP8266-MQTT for IoT applications. Experimental results demonstrate that this system can accurately predict battery SOC while facilitating multiplatform data communication. © 2024 IEEE.

关键词： State of charge

来源：评论

学校读者我要写书评

暂无评论

Structural Electrochemical Characteristics of GO, ZnO and GO/ZnO Nanocomposite for Detecting Sulfamethoxazole in Tablet 3

Structural Electrochemical Characteristics of GO, ZnO and GO...

引用

3rd International Conference on Electrical, Electronics, Information and communication Technologies, ICEEICT 2024

作者： Padmalaya, G. Athmanesan, T. Senthilkumar, P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Electrical and Communication Department of Electronics and Communication Engineering Tamil Nadu Avadi600062 India Pondicherry University Government of India Centre for Pollution Control and Environmental Engineering School of Engineering and Technology Puducherry Kalapet605014 India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369083

In this research work, a GO-ZnO nanocomposite-based electrochemical sensor was used as a modified electrode for enhanced electrochemical behavior. The electrochemical sensor characteristics were analyzed using cyclic and impedance voltammetry. Cyclic voltammetry confirmed the electrochemical behavior of the modified electrode. The cyclic voltammograms for GO, ZnO and GO-ZnO nanocomposite were investigated, and observed that peaks are highly independent on behavioral potential peaks. Their physio-chemical characteristics were analyzed using X-ray diffraction (XRD) analysis and HR-scanning electron Microscopy. On examining the electrochemical characteristics of obtained nanomaterials found to exhibit its behavior towards electrochemical sensor applications for detecting sulfamethoxazole. © 2024 IEEE.

关键词： Cyclic voltammetry

来源：评论

学校读者我要写书评

暂无评论

Research on emotional space for movie and TV drama videos

引用

The Journal of China Universities of Posts and Telecommunications 2022年第5期29卷 73-82页

作者： Li Yujie Zhang Jingjing Jiang Wei Wang Chunxiao 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 School of Computer and Cyber Sciences Communication University of ChinaBeijing 100024China

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding(t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.

关键词： emotional space movie and TV drama videos subjective evaluation words semantic analysis fusion space

来源：评论

学校读者我要写书评

暂无评论

Research on Named Entity Recognition for Oral History Text

Research on Named Entity Recognition for Oral History Text

引用

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

作者： Hu, Chaoyu Bai, Shilei Zhang, Mengfei Communication University of China School of Information and Communication Engineering Beijing China Beijing Key Laboratory of Modern Entertainment Technology Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing China

ISBN: (纸本)9798350380347

Oral history involves conveying experienced events through spoken narratives, typically preserved and later studied by converting spoken language into text. Named entity recognition (NER) is the recognition of meaningful named entities in text, such as person names, locations, organizations, etc. Conducting NER research on oral history text is significant as it not only facilitates the verification of named entities by researchers but also allows for the extraction of key information from texts through named entities. By collecting oral history corpus, we establish an oral history text dataset, manually annotating all texts with six entity labels and repeatedly verifying them manually. Utilizing the concept of machine reading comprehension (MRC), a semantic fusion module was added, integrating label information into text information using a cross-attention mechanism, and decoding the corresponding entity labels through span decoding. The final model performs well on the oral history text dataset and also showed good performance on general Chinese datasets. © 2024 IEEE.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：