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7th IEEE information technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Ma, Yuqi Zhang, Yunxi Wang, Zihan Zhao, Ya Liu, Jia School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350370782

This paper presents a speech recognition method combining spectral subtraction with improved BP neural network algorithm. The speech samples containing unstable noise are collected in the real environment. Firstly, the noise from speech signals is removed using spectral subtraction method, and the speech feature parameters after noise removal are extracted. Then the speech is recognized effectively by the improved BP neural network algorithm. Finally, some comparative experiments are given to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Speech enhancement

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Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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Cancelable Speaker Identification System Based on Optical-Like Encryption Algorithms

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Computer Systems Science & engineering 2022年第10期43卷 87-102页

作者： Safaa El-Gazar Walid El-Shafai Ghada El-Banby Hesham F.A.Hamed Gerges M.Salama Mohammed Abd-Elnaby Fathi E.Abd El-Samie Department of Electrical Engineering Faculty of EngineeringEgyptian-Russian UniversityCairoEgypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last *** achieves safe access to systems using biometrics instead of the traditional *** utilization of a biometric in its original format makes it usable only ***,a cancelable biometric template should be used,so that it can be replaced when it is *** biometrics aims to enhance the security and privacy of biometric *** encryption is an efficient technique to be used in order to generate cancelable biometric *** this paper,a highly-secure encryption algorithm is proposed to ensure secure biometric data in verification *** considered biometric in this paper is the speech *** speech signal is transformed into its ***,the spectrogram is encrypted using two cascaded optical encryption *** first algorithm is the Optical Scanning Holography(OSH)for its efficiency as an encryption *** OSH encrypted spectrogram is encrypted using Double Random Phase Encoding(DRPE)by implementing two Random Phase Masks(RPMs).After the two cascaded optical encryption algorithms,the cancelable template is *** verification is implemented through correlation estimation between enrolled and test templates in their encrypted *** the correlation value is larger than a threshold value,the user is *** threshold value can be determined from the genuine and imposter correlation distribution curves as the midpoint between the two *** implementation of optical encryption is adopted using its software rather than the optical *** efficiency of the proposed cancelable biometric algorithm is illustrated by the simulation *** can improve the biometric data security without deteriorating the recognition *** results give close-to-zero This values for the Equal Error Rate(EER)and close-to-one values for the Area under Receiver Operator Charact

关键词： Cancelable biometrics spectrogram OSH DRPE EER AROC

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Fault prediction of electric vehicle charging stations based on cooperative game strategy and DBO-BiLSTM 6

Fault prediction of electric vehicle charging stations based...

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6th IEEE Advanced information Management, Communicates, Electronic and Automation control Conference, IMCEC 2024

作者： Tian, Liguo Shang, Chunhu Li, Meng Chen, Qingbin Tianjin University of Technology and Education College of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350316520

Aiming at the problem of high failure rate of electric vehicle charging pile, an electric vehicle charging pile failure prediction method based on cooperative game strategy and dung beetle optimisation algorithm-bidirectional long and short-term memory network (DBO-BiLSTM) is proposed. Firstly, the outliers are handled by parameter statistical distribution, the missing values are handled by mean padding, and the normalisation operation is performed on the processed data;secondly, multiple single-assignment methods are selected to calculate the feature weights, the combined weights are calculated by the cooperative game strategy, and the parameter feature matrix is enlarged;and then, the DBO-BiLSTM model is constructed, and under the simulation experiments, the accuracy rate of the training set and test set, the F1 coefficients are 0.89, 0.89, 0.90 and 0.89, ***, relevant comparison experiments are constructed, and the results show that the proposed model has better performance, which verifies the effectiveness and reasonableness of the proposed model. © 2024 IEEE.

关键词： Brain

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Substation Insulator Inspection Robot System Based on Deep Learning 7

Substation Insulator Inspection Robot System Based on Deep L...

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7th IEEE information technology, Networking, Electronic and Automation control Conference, ITNEC 2024

作者： Li, Meng Tian, Liguo Hou, Shidong College of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin China

ISBN: (纸本)9798350370782

Substation plays an important role in power system As the key electrical isolation component in substation, the state of insulator is directly related to the safe operation of power grid In order to improve the inspection efficiency and safety of substation insulators, this paper presents a substation insulator inspection robot system based on ResNet18 model in order to improve the inspection efficiency and safety of substation insulators The system consists of visual inspection module, navigation module and main control system The visual inspection module adopts Hi3516 visual identification terminal to accurately inspect insulators;The navigation module uses lidar and Rising Sun X3 to collect map data and SLAM algorithm to realize accurate positioning and path planning;The main control system takes STM32 core board as the center and is responsible for motor control network communication and other tasks In addition, a man-machine interface is designed to display the inspection status and inspection results of the robot in real time Experiments show that the system has high accuracy and robustness in practical application, which provides technical support for automatic inspection of insulators in substations. © 2024 IEEE.

关键词： Motion planning

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Plant Growth Status Analyser based on WOA-LSTM Prediction Model 6

Plant Growth Status Analyser based on WOA-LSTM Prediction Mo...

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6th IEEE Advanced information Management, Communicates, Electronic and Automation control Conference, IMCEC 2024

作者： Hu, Zhiming Tian, Liguo Li, Meng Tianjin University of Technology and Education College of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350316520

Plant electrical signal is a kind of non-smooth and non-linear weak signal, and it is a low-frequency random signal. The plant growth state analyzer of the plant electrical signal is to receive the data from the plant electrical signal acquisition board first, and then preprocess the electrical signal data collected from the acquisition board to finally obtain the plant electrical signal with high signal-to-noise ratio, extract the maximum value, minimum value, peak value, average value, area, rising speed, falling speed as the feature value, and then get the deep learning model through the training of WOA-LSTM neural network to obtain the collected plant electrical signal and a relationship with the influences on the plant growth state. model to get the collected plant electrical signals and a relationship with the influence of plant growth state. The experimentally trained WOA-LSTM neural network model has a mean square error MSE and correlation coefficient R of 0.0232 and 0.9408, respectively. which is a good judgment, proving that the model has a high judgment accuracy. Finally, the model was deployed to the development board and the plant growth status was displayed on the feedback interface using QT. The plant growth state analyzer speculates the current growth state of the plant through the change of the electrical signal of the plant in order to adjust the environment of the plant in time. Through the electrical signal to determine whether the plant grows in a good direction or a bad direction to control it, it helps to promote the development of agriculture in a more accurate, efficient and sustainable direction. © 2024 IEEE.

关键词： Neural network models

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An improved short-circuit current control method for self-synchronization controlled wind turbine 12

An improved short-circuit current control method for self-sy...

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12th International Conference on Renewable Power Generation, RPG 2023

作者： Deng, Zhenyan Wang, Han Qin, Yao Cai, Xu The key Laboratory of Control of Power Transmission and Conversion of Ministry of Education Department of Electrical Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China

The self-synchronization controlled wind turbine directly controls its output voltage amplitude and phase, which can actively support the grid frequency and voltage stability, provide inertia and damping support for the system, showing the characteristics of voltage a source. However, when the power grid fails, as this method has no current control loop, the short-circuit current of converter cannot be controlled, which may easily cause the damage of components due to the overcurrent. In view of the above problems, this paper conducts in-depth research on two short-circuit current control methods based on virtual impedance and voltage loop controller, analyzes their advantages and disadvantages, and proposes an integrated controller combine thesis two methods. The integrated current-limiting controller can realize the effective control of the steady-state and transient amplitude of the short-circuit current of the self-synchronization controlled wind turbine. The full electromagnetic transient simulation model of the permanent magnet direct-drive wind turbine is built, and the simulation verifies the effectiveness of the proposed control strategy. © The Institution of engineering & technology 2023.

关键词： Wind turbines

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Detection of inter row navigation lines in corn fields based on improved CenterNet

Detection of inter row navigation lines in corn fields based...

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International Conference on Computer Vision, Robotics, and Automation engineering, CRAE 2024

作者： Zhang, Zhipeng Li, Huiyan Meng, Qingkuan Zhang, Ruitong Zhang, Wenkang School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781510682283

In complex corn orchard environments, traditional machine vision algorithms often struggle to handle changes in light, occlusion between crops, and interference from weeds, which leads to inaccurate navigation line extraction. This article proposes a corn field navigation route detection method based on improved CenterNet to address this issue. Firstly, we replaced the CenterNet backbone network with ResNeSt, which can effectively improve detection performance when facing small targets and complex hierarchical image content. At the same time, we added CBMA attention mechanism in CenterNet to enhance the recognition of target features of corn seedlings and weaken background interference. We use the midpoint of corn seedlings as the navigation positioning base point, use an improved CenterNet model to detect corn seedlings on both sides, use the center point of corn seedlings as the positioning reference point, and then use the least squares method to fit the center points of corn seedlings on both sides. The experimental results show that the improved CenterNet model has a detection accuracy of 76.44% and a detection speed of 42.09 frames per second. Compared with the original CenterNet model, it has improved by 4.28 percentage points and 1.51 frames per second, respectively. From this, it can be seen that the model can accurately identify corn seedlings, and the average processing time for one frame of image is 0.082 seconds, which fully meets the needs of navigation in corn fields. © 2024 SPIE.

关键词： Seed

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Development of Wind Wake-effect Minimizing Model Based on Combination of Dung Beetle Optimization, Extreme Learning Machine, and Genetic Algorithms

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Sensors and Materials 2024年第3期36卷 1047-1064页

作者： Qu, Li-Nan Li, Hao-Peng Lin, Hsiung-Cheng Li, Ling-Ling State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300401 China China Electrical Equipment Research Institute of Science and Technology Co. Ltd. Shanghai200436 China School of Electronic and Information Engineering Hebei University of Technology Tianjin300401 China Department of Electronic Engineering National Chin-Yi University of Technology Taichung41170 Taiwan

The wake effect caused by a wind turbine can reduce the wind speed and add turbulence to the wind, thus impacting the power generation efficiency. To effectively enhance the generated power in wind farms, we propose an optimal layout model that is combined with artificial intelligence optimizing algorithms. First, the adaptive genetic algorithm (AGA) is used to optimize the collected wind speed and direction distribution data as the optimization basis. Second, the extreme learning machine (ELM) based on Monte Carlo simulation is used to establish a guidance for determining the turbine relocation from the optimization basis. Simultaneously, the dung beetle optimization (DBO) algorithm is developed to improve the performance of ELM for achieving the optimal solution. The proposed model was tested at six different wind farms and under three different wind condition distribution settings. The simulation results verify that the model is superior to existing algorithms in reducing the wakeeffect impact as well as optimizing the wind farm layout. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Genetic algorithms

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Weakly Secure Summation with Colluding Users

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IEEE Transactions on information Theory 2025年第7期71卷 5672-5683页

作者： Li, Zhou Zhao, Yizhou Sun, Hua Electronics and Information at Guangxi University Guangxi Key Laboratory of Multimedia Communications and Network Technology School of Computer Nanning530004 China Southwest University College of Electronic and Information Engineering Chongqing400715 China University of North Texas Department of Electrical Engineering DentonTX76203 United States

In secure summation, K users, each holds an input, wish to compute the sum of the inputs at a server without revealing any information about all the inputs even if the server may collude with an arbitrary subset of users. In this work, we relax the security and colluding constraints, where the set of inputs whose information is prohibited from leakage is from a predetermined collection of sets (e.g., any set of up to S inputs) and the set of colluding users is from another predetermined collection of sets (e.g., any set of up to T users). For arbitrary collection of security input sets and colluding user sets, we characterize the optimal randomness assumption, i.e., the minimum number of key bits that need to be held by the users, per input bit, for weakly secure summation to be feasible, which generally involves solving a linear program. © 1963-2012 IEEE.

关键词： Security Servers Costs Symbols Protocols Sun Entropy Electronic mail Vectors Training

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