检索结果-内蒙古大学图书馆

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Liu, Chang Lu, Yong Zhang, Lina Fan, Liyun Harbin Engineering University Harbin China Beijing Automation Control Equipment Institute Beijing China

ISBN: (纸本)9789811966125

Parameter setting is one of the long-standing grand challenges of the metaheuristic algorithm filed. The effect of the optimization algorithm will mainly depend on the setting of the algorithm-dependent parameters. The best result for solving the optimization problems can be achieved by the optimal setting of the algorithm’s parameter. In this paper, we investigate the parameter setting problem of firefly algorithm. The sufficient simulation results are showed that with proper setting of the parameter firefly algorithm can converge efficiently and accurately. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optimization

来源：评论

学校读者我要写书评

暂无评论

Optimal Scheduling of an Independent Electro-Hydrogen System with Hybrid Energy Storage Using a Multi-Objective Standardization Fusion Method

引用

Energy engineering 2025年第1期122卷 63-84页

作者： Suliang Ma Zeqing Meng Mingxuan Chen Yuan Jiang School of Electrical and Control Engineering North China University of TechnologyBeijing100144China ChinaThree Gorges Technology Co. Ltd.Beijing100032China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China

In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is ***,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical *** deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s *** optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization *** proposed method better balances all optimization objective functions and reduces the impact of their *** the cost of BESS decreases by approximately 30%,its participation deepens by about 1 ***,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase *** study aims to provide a more reasonable approach to solving multi-objective optimization problems.

关键词： Electro-hydrogen system multi-objective optimization standardization method hybrid energy storage system

来源：评论

学校读者我要写书评

暂无评论

HKB-YOLO: transmission line fire detection method based on hierarchical feature fusion

引用

International Journal of Security and Networks 2024年第4期19卷 188-198页

作者： Ying, Zhilei Meng, Yanan Chen, Ruoxi Lou, Jianlou School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin 132022 China Department of Automation Jilin Institute of Chemical Technology Jilin 132022 China School of Computer Engineering Northeast Electric Power University Jilin 132012 China

Timely transmission line fire inspections are vital for power system safety. Although deep learning models are widely used for flame detection, struggle with small target recognition due to background interference and are vulnerable to input data perturbations, posing security risks. This study introduces a hierarchical feature fusion method based on the you only look once Version 8 (YOLOV8) framework. It employs high-performance GPU network version 2 (HGNetV2) to enhance small-target feature extraction while reducing computational complexity. A spatial pyramid pooling-fast module with large separable kernel attention is designed to highlight key features and suppress background noise. The proposed bidirectional slim neck structure (BiSlimneck) reduces feature loss. Adversarial training enhances the model’s robustness. Experimental results show a 1.4% accuracy improvement, with a reduction in parameters and complexity by 18.3% and 21.6%, respectively. After adversarial training, the accuracy of the network in the face of attacks increased by 10% compared to the pre-training. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Premixed flames

来源：评论

学校读者我要写书评

暂无评论

The Study of Materials for Electric Field Protection of Power Transformer Testing 9

The Study of Materials for Electric Field Protection of Powe...

引用

9th International Conference on engineering, Applied Sciences, and Technology, ICEAST 2023

作者： Meesuk, Peerawat Bunpakdee, Prajak Sorn-In, Sirirat Bansomdejchaopraya Rajabhat Univrtsity Electrical Engineering and Automation Control System Program Faculty of Engineering and Industrial Technology Bangkok Thailand

ISBN: (纸本)9798350322040

This paper proposes the analysis of the material can be protected from transformer testing and presents a mathematical model of the power transformer. In this research, transformers were study in four protective materials, wood, rubber, glass and acrylic that are used in between the electric field measurement and the transformer. By simulating the test results of a transformer with a voltage of 230 kV. Computer-based simulation utilizing the finite element method (FEM) is exploited as a tool for visualizing electric fields distribution volume a power transformer. The simulation results showed that the material with the best protection against the electric field was wood insulation and the best installation location was a distance of 5 m from the transformer. © 2023 IEEE.

关键词： Finite element method

来源：评论

学校读者我要写书评

暂无评论

GRU combined model based on multi-objective optimization for short-term residential load forecasting

引用

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Detecting physical laws from data of stochastic dynamical systems perturbed by non-Gaussianα-stable Lévy noise

引用

Chinese Physics B 2023年第5期32卷 337-342页

作者：陆凌弘志李扬刘先斌 State Key Laboratory of Mechanics and Control for Mechanical Structures College of Aerospace EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China School of Automation Nanjing University of Science and TechnologyNanjing 210094China

Massive data from observations,experiments and simulations of dynamical models in scientific and engineering fields make it desirable for data-driven methods to extract basic laws of these *** present a novel method to identify such high dimensional stochastic dynamical systems that are perturbed by a non-Gaussianα-stable Lévy *** explicitly,firstly a machine learning framework to solve the sparse regression problem is established to grasp the drift terms through one of nonlocal Kramers–Moyal *** the jump measure and intensity of the noise are disposed by the relationship with statistical characteristics of the *** examples are then given to demonstrate the *** approach proposes an effective way to understand the complex phenomena of systems under non-Gaussian fluctuations and illuminates some insights into the exploration for further typical dynamical indicators such as the maximum likelihood transition path or mean exit time of these stochastic systems.

关键词： data-driven modelling noise-induced transitions Lévy noise Kramers–Moyal formuas

来源：评论

学校读者我要写书评

暂无评论

Design of a Digital Phase Lead-and-Lag Voltage control based on Frequency Response Approach for Single-Phase Half-Bridge DC-AC Converters 15

Design of a Digital Phase Lead-and-Lag Voltage Control based...

引用

15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： Buzzi, Henrique Eissmann Busarello, Tiago Davi Curi Péres, Adriano Dept. of Control Automation and Computing Engineering Federal University of Santa Catarina Blumenau Brazil

ISBN: (纸本)9798350314182

Grid-forming inverters is getting special attention of industries and academia due to their important role in the realization of microgrids. A crucial feature of them is to have an accurate voltage control. This paper proposes a digital phase lead-and-lag voltage control based on frequency response approach for single-phase half-bridge DC-AC converters. Initially, the system is modeled through the small-signal technique. Then, the controller is designed based on the frequency response approach. The discretization through Tustin and Backward methods are presented and compared. Moreover, designing the controller in discrete-time domain by conventional methods using the fictitious w-domain is also presented. The system is tested in a controller Hardware-in-Loop setup, where the power topology runs in the HIL402 device and the digital voltage controller runs in the TMS320FF28335 digital signal controllers. Scenarios like initialization, nonlinear load and oscillation at the DC voltage are performed. Results show the efficacy of the methodology proposed in this paper. ©2023 IEEE.

关键词： discretization Half-Bridge converter hardware-in-loop voltage control

来源：评论

学校读者我要写书评

暂无评论

Fault diagnosis of rolling bearings with noise signal based on modified kernel principal component analysis and DC‐ResNet

引用

CAAI Transactions on Intelligence Technology 2023年第3期8卷 1014-1028页

作者： Yunji Zhao Menglin Zhou Xiaozhuo Xu Nannan Zhang School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuoChina Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Henan Polytechnic UniversityJiaozuoChina

In view of the influence of aliasing noise on the effectiveness and accuracy of bearing fault diagnosis,a bearing fault diagnosis algorithm based on the spatial decoupling method of modified kernel principal component analysis(MKPCA)and the residual network with deformable convolution(DC‐ResNet)is innovatively ***,the Gaussian noise with different signal‐to‐noise ratios(SNRs)is added to the data to simulate the different degrees of noise in the actual data acquisition *** MKPCA is used to project the fault signal with different SNRs in the kernel space to reduce the data dimension and eliminate some noise ***,the DC‐ResNet model is used to further filter the noise effects and fully extract the fault features through the training of the preprocessed *** proposed algorithm is tested on the Case Western Reserve University(CWRU)and Xi'an Jiaotong University and Changxing Sumyoung Technology Co.,Ltd.(XJTU‐SY)bearing data sets with different SNR *** fault diagnosis accuracy can reach 100%within 30 min,which has better performance than most of the existing *** experimental results show that the algorithm has an excellent effect on accuracy and computation complexity under different noise levels.

关键词： artificial intelligence classification deep learning fault feature extraction

来源：评论

学校读者我要写书评

暂无评论

Digital Twin-Driven Degradation Modeling Method for control Moment Gyroscope Health Management 9

Digital Twin-Driven Degradation Modeling Method for Control ...

引用

9th IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2023

作者： Cui, Runhao Huang, Xucong Zhang, Peng Tang, Diyin Beihang University School of Automation Science and Electrical Engineering Beijing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9798350333794

Prognosis and health management (PHM) of control moment gyroscope (CMG) plays a crucial role in ensuring the operational efficiency and safety of spacecraft. In order to improve the accuracy of PHM and supplement abundant monitoring data, this paper proposes a digital twin-driven degradation modeling method, which establishes a detailed simulation model based on degradation mechanisms at the CMG component level. The digital twin model not only provides a large amount of high-quality data for performance evaluation, but also serves as an important reference for on-orbit CMG state assessment. Finally, a case of estimating virtual sensor degradation information based on reinforcement learning is used to demonstrate the effectiveness of the proposed digital twin method. © 2023 IEEE.

关键词： Gyroscopes

来源：评论

学校读者我要写书评

暂无评论

Research on LSTM-based winding state prediction method 7

Research on LSTM-based winding state prediction method

引用

2024 7th International Conference on Power Electronics and control engineering, ICPECE 2024

作者： Wang, Yiyang Guo, Haifeng Li, Jianan Liu, Xinen Li, Xiang Du, Zhongbo Shen, Yang School of Electrical and Automation Engineering Liaoning Institute of Science and Technology Benxi117004 China Liaoning Province Robot Drive Control Engineering Laboratory Benxi117004 China

Mechanical and electrical equipment is widely used in various links of the manufacturing industry and is also the key to the implementation of modern industrial technology. Winding is the core component of transformers, electromagnetic valves, motors, robots, and other mechanical and electrical equipment. The safe and reliable operation of winding is the premise for the healthy operation of industrial equipment. Therefore, taking the core component of many industrial equipment, the winding, as the research object, and aiming to improve the safety and reliability of the equipment, this study focuses on the state prediction method of winding with the help of sensitive feature information. With the rapid development of industrial big data technology, data-driven technology, especially time series prediction technology, has developed rapidly. Considering the characteristics of winding degradation data, a winding state prediction method based on the Long Short-Term Memory (LSTM) approach is proposed. By using experimental data of winding, a health index reflecting their health status is constructed, and the LSTM is utilized for training the health index, thereby achieving time series-based state prediction of winding. This provides reliable support for the health status assessment of industrial mechanical and electrical equipment and enhances the reliability of the equipment. © Published under licence by IOP Publishing Ltd.

关键词： Machine windings

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：