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The Impact of Grid Harmonics on Commutation Failure 7

The Impact of Grid Harmonics on Commutation Failure

引用

7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Li, Ming Shen, Xiaolin Wu, Yucheng Liu, Yiqi State Grid Economic and Technology Research Institute Co. Ltd. Beijing China College of Mechanical and Electrical Engineering Northeast Forestry University Harbin China College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

Commutation failure is a common fault in Line Commutated Converter High Voltage Direct Current (LCC-HVDC) systems. LCC-HVDC relies on the AC power grid to provide reverse voltage to naturally turn off thyristors. Faults in the AC system on the inverter side can lead to commutation failures. In practical engineering applications, AC network harmonics also affect the commutation of thyristors. This paper further elucidates the impact of AC network harmonics on commutation failure and validates the effect of non-characteristic harmonics of different orders on LCC-HVDC commutation failure using the PSCAD/EMTDC simulation platform. © 2024 IEEE.

关键词： Thyristors

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Speech Recognition of Vedic Sanskrit using Deep Learning Algorithm 6

Speech Recognition of Vedic Sanskrit using Deep Learning Alg...

引用

6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Pandey, Mrinal Pandey, Rashmikiran Nazarov, Alexey Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798350346961

In this study, we examined the use of computational techniques for accurately processing acoustic signals of human speech using digital media. Specifically, we focused on the Sanskrit language and applied a language modeling approach to improve recognition by machines. Our implementation of this approach for Sanskrit speech represents a novel approach in the field and has the potential to extract valuable information through automated processing. The ability to accurately process speech is crucial for effective human communication, and our research contributes to the development of more efficient and effective methods for achieving this goal... © 2023 IEEE.

关键词： Speech recognition

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Design of an Intelligent Monitoring System for Operating States in a Coal Mine Drilling Process 41

Design of an Intelligent Monitoring System for Operating Sta...

引用

第41届中国控制会议

作者： Xiao Yang Luefeng Chen Sheng Du Chengda Lu Wangnian Li Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Xi'an Research Institute Co.Ltd. China Coal Technology and Engineering Group

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development trend of intelligent drilling in coal mines,an intelligent monitoring system for operating states in a drilling process is developed to solve the problems of incomplete display of drilling parameters and ineffective *** system realizes the remote monitoring of drilling *** mainly adopts the Fuzzy C-Means clustering algorithm to cluster the drilling *** it combines expert empirical knowledge to classify coal seams into soft,hard and alternating soft and hard coal *** boundary values are calculated according to the boundary ***,three drilling operating states,rated,conservative and over-excited,are judged to provide guidance for the drilling process control.

关键词： Drilling process Intelligent monitoring Fuzzy C-Means clustering Operating states

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Design of An Intelligent control System for Underground Directional Drilling Trajectory in Coal Mines 41

Design of An Intelligent Control System for Underground Dire...

引用

第41届中国控制会议

作者： Wangnian Li Min Wu Ke Yao Quanxin Li Chengda Lu Sheng Du School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Xi'an Research Institute Co.Ltd. China Coal Technology and Engineering Group

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Directional drilling trajectory control technology is one of the key technologies to realize automation and intelligence of underground tunnel drilling in coal *** construction of directional drilling in underground coal mines mainly relies on manual observation of measurement-while-drilling parameters to control the drilling trajectory,which is highly dependent on manual *** paper designs an intelligent control system of underground directional drilling trajectory for coal *** the idea of hierarchical design and modular design,this system collects and displays geometric parameters,geological parameters,and engineering parameters of the directional drilling ***,an intelligent decision-making platform for directional drilling trajectory prediction and control is developed,laying a foundation for the research of directional drilling trajectory prediction and intelligent control for coal mines.

关键词： Trajectory prediction trajectory control geometric parameters geological parameters engineering parameters

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Enhanced DDoS Detection using Machine Learning 6

Enhanced DDoS Detection using Machine Learning

引用

6th International Conference on Information Systems and computer Networks, ISCON 2023

作者： Pandey, Rashmikiran Pandey, Mrinal Nazarov, Alexey Moscow Institute of Physics and Technology Department of Radio Engineering and Cybernetics Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798350346961

The rapid growth of internet population poses a serious challenge to the security of internet resources. The security is directly affected by the hits of Denial of Services (DoS) attack which is rampant nowadays. With this evolving threat, designing a cutting-edge method is difficult from a cyber-security perspective. In this study, we propose a deep learning-based system for detecting Distributed Denial of Service (DDoS) attacks, which utilizes Logistic Regression, K- Nearest Neighbor, and Random Forest algorithms. We assess proposed models using a recently updated NSL KDD dataset. Our research's findings also demonstrate that proposed model is highly accurate in detecting Distributed Denial of Service (DDoS) attacks. Our results show that our proposed model significantly improves upon current state-of-the-art attack detection methods. © 2023 IEEE.

关键词： Denial-of-service attack

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Partially Occluded Face Expression Recognition with CBAM-Based Residual Network for Teaching Scene

Partially Occluded Face Expression Recognition with CBAM-Bas...

引用

2023 China automation Congress, CAC 2023

作者： Bai, Yanxing Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcomes the problem of localized occlusion face feature extraction by focusing on the regions and channels containing important information in the occluded face data through CBAM. Multi-task cascaded convolutional networks (MTCNN) are firstly utilized to localize the key regions of face emotion, and then deep emotion features are extracted by CBAM-ResNet network. The final emotion labels are generated. The effectiveness of this paper's method is verified on the RAF-DB dataset and the occluded CK+ dataset. The experimental accuracy in the RAF-DB dataset is 76.3%, which is 3.74% and 1.64% higher than the accuracy produced by the method of RGBT, and the WLS-RF, respectively. Application experiments are carried out in the real teaching scenario, which verifies the applicability of the algorithm in the real teaching scene. © 2023 IEEE.

关键词： Emotion Recognition

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

引用

2023 China automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

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An Adaptive Scheduling Method for Infrastructure Construction Progress Based on Digital Twin 22

An Adaptive Scheduling Method for Infrastructure Constructio...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Liang, HaiSheng Wang, Yini Wei, Chuxi Yu, Songyuan Fang, Fang State Grid Shanghai Economic Research Institute State Grid Shanghai Municipal Electric Power Company Shanghai China School of Control And Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798331527471

The uncertainty of risk factors in infrastructure construction presents significant challenges to the management of construction progress. To effectively control construction progress while ensuring quality and reducing costs, we propose an adaptive scheduling method for infrastructure construction progress based on digital twin. First, we establish a digital twin model that reflects the construction progress by considering relevant progress information. Subsequently, taking into account the uncertainties associated with human factors, construction processes, and environmental factors, we develop a safety assessment method for power infrastructure and formulate a construction stoppage model. Then, we design an adaptive scheduling method that considers the uncertainties related to construction stoppage risks. Finally, the effectiveness and practicality of the proposed methods are validated through a comparative analysis of different cases. © 2024 IEEE.

关键词： adaptive scheduling digital twin infrastructure construction

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Design and Implement for Infrared Imaging Strapdown Seeker Simulation and Test System 42

Design and Implement for Infrared Imaging Strapdown Seeker S...

引用

42nd Chinese control Conference, CCC 2023

作者： Tao, Li Yi, Zhang Dan, Yang Shu-Jie, Liu Peng-Fei, Zhang Bo-Yi, Kang Pei, Pei Xi'an Modern Control Technology Research Institute Xi'an710065 China School of Automation Northwestern Polytechnical University Xi'an710072 China Technology Center Southwest Computer Co. Ltd Chongqing400060 China

ISBN: (纸本)9789887581543

In order to satisfy the stabilization requirements of the infrared imaging seeker, this paper derives the strapdown decoupling algorithm and obtains the line of sight (LOS) angular velocity required by proportional navigation law based on α-β filter. An infrared imaging strapdown seeker (IISS) simulation and test system is established based on Real-time extension (RTX) under the Windows operating system. Based on the system, simulation and test of the target tracking performance and disturbance rejection rate (DRR) of the seeker are executed. Simulation results show that the system can be suitable for verifying the performance of infrared imaging seeker and the validity of strapdown decoupling algorithm and practicability of the simulation system framework. The simulation system can provide a useful reference for other similar strapdown seeker simulation systems. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Disturbance rejection

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Acoustic feature extraction of wind turbine blades based on improved MFCC-GFCC 22

Acoustic feature extraction of wind turbine blades based on ...

引用

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Wang, Ziyi Chen, Yuanye Wang, Hua Wang, Haichao Fang, Fang School of Control and Computer Engineering North China Electric Power University Beijing China Huaneng Clean Energy Research Institute Beijing China Shaanxi Oceanx Technology Co. Ltd Xianyang China

ISBN: (纸本)9798331527471

As a critical component of wind turbines, the structural integrity of the blades is crucial for safe operation. To enhance the performance of health monitoring and fault detection systems, an acoustic feature extraction method is proposed to designed to aid in the development of a digital twin model for wind turbine blades (WTB). Our approach begins with a time index algorithm based on local maxima, which isolates single-blade data from audio recordings of the wind turbine. Then a blade acoustic signal feature extraction technique is developed by combining improved Mel Frequency Cepstral Coefficients (MFCC) and Gammatone Frequency Cepstral Coefficients (GFCC). This technique leverages anomaly contribution and the maximal information coefficient (MIC) as comprehensive indicators to filter out irrelevant and negative features. By multiplying and fusing the features, our method achieves feature complementarity and reduces computational complexity. The proposed method can be seamlessly integrated into digital twins for wind turbines. © 2024 IEEE.

关键词： Wind turbine blades

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