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IEEE Transactions on Sustainable Computing 2024年第3期10卷 475-490页

作者： Song, Changqing Zhao, Hongzhi Yu, Yong Li, Zhuo Shao, Shihai University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China Yangzhou Marine Electronic Instrument Institute Yangzhou225101 China

The artificial noise shielded frequency-hopping (ANFH) architecture can secure wireless communications against interference and eavesdropping. However, the AN suppression performance is highly sensitive to the radio frequency (RF) impairments, and the transceiver in-phase and quadrature (IQ) imbalances and phase noise in FH systems are more severe for the wide FH bandwidth. In this study, the AN-FH transceivers under RF impairments are mathematically modeled. Subsequently, distortions for transceiver phase noise are represented by the common phase error, distortions for transceiver IQ imbalances are represented by the mirror image component, and closed-form expressions for their respective power are derived and compared with the thermal noise power. Finally, the AN suppression capability is evaluated via the AN suppression ratio (ANSR), defined as the ratio of the AN-plus-noise power before and after suppression. It is found that when only phase noise exists, shortening the channel compensation cycle can enhance ANSR and reduce ANSR degradation;when the distortions' power is smaller than the thermal noise power, it is also recommended to enhance the transmitting power and the power ratio of AN to information signals. When only IQ imbalances exist, increasing the power ratio of AN to information signals is suggested;when the distortions' power is smaller than the thermal noise power, enhancing the transmitting power is also suggested © 2016 IEEE.

关键词： Phase noise

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A Novel Grades Prediction Method for Undergraduate Students by Learning Explicit Conditional Distribution

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4837-4848页

作者： Zhang, Na Liu, Ming Wang, Lin Liu, Shuangrong Sun, Runyuan Yang, Bo Zhu, Shenghui Li, Chengdong Yang, Cheng Cheng, Yuhu China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Quan Cheng Laboratory Jinan250100 China Shandong Jianzhu University Shandong Key Laboratory of Intelligent Buildings Technology Jinan250101 China Shandong Jianzhu University School of Information and Electrical Engineering Jinan250101 China Ministry of Education Engineering Research Center of Intelligent Control for Underground Space Xuzhou221116 China

Educational data mining (EDM) offers an effective solution to predict students' course grades in the next term. Conventional grade prediction methods can be viewed as regressing an expectation of the probability distribution of the student's grade, typically called single-value grade prediction. The reliable prediction outcomes of these methods depend on the complete input information related to students. However, next-term grade prediction often encounters the challenge of incomplete input information due to the inaccessibility of future data and the privacy of data. In this scenario, single-value grade prediction struggles to assess students' academic status, as it may not be represented and assessed by relying on a singular expectation value. This limitation increases the risk of misjudgment, and may lead to errors in educational decision-making. Considering the challenge of collecting complete input information, we shift from traditional single-value predictions to forecasting the explicit probability distribution of the course grade. The probability distribution of the grade can assess the students' academic status by providing probabilities corresponding to all possible grade values rather than relying solely on an expectation value, which offers the foundation to support the educators' decision-making. In this article, the course grade distribution prediction (CGDP) model is proposed, aiming to estimate an explicit conditional probability distribution of course grades in the next term. This model can identify at-risk students, offering comprehensive decision-making information for educators and students. To ensure precise distribution predictions, a calibration method is also employed to improve the alignment between predicted and actual probabilities. Experimental results verify the effectiveness of the proposed model in early grade warning for undergraduates, based on real university data. © 2020 IEEE.

关键词： Probability distributions

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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Reinforcement Learning-based Frequency control for Renewable Energy Microgrids 7

Reinforcement Learning-based Frequency Control for Renewable...

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7th International Conference on intelligent Robotics and control Engineering, IRCE 2024

作者： He, Jing Zhang, Junpeng Jiang, Haiping Ma, Zongfang College of Information and Control Engineering Xi'an University of Architecture and Technology The Moe Key Laboratory of Intelligent Network and Network Security Xi'an Jiaotong University China Xi'an University of Architecture and Technology College of Information and Control Engineering Xi'an China

ISBN: (纸本)9798350352399

With extensive access to renewables, the inertia of microgrid is significantly reduced, which in turn puts forward higher requirements for the frequency stability of the system. In this paper, a frequency control method based on reinforcement learning is proposed for the intermittent and unstable characteristics of renewables. First, the microgrid frequency control principle and reinforcement learning theory are introduced. On this basis, a microgrid frequency control strategy based on Q-learning algorithm is proposed, and the design process is described in detail, including the design of the action set, state set, and reward function. Finally, the Q-learning algorithm is pretrained offline through simulation experiments, and tested in several scenarios for online operation. The effectiveness and adaptability of the proposed algorithm are verified through comparative analysis with other strategies. © 2024 IEEE.

关键词： Adversarial machine learning

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Terahertz Spectroscopic Characterization and Thickness Evaluation of Internal Delamination Defects in GFRP Composites

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Chinese Journal of Mechanical Engineering 2023年第1期36卷 190-210页

作者： Walter Nsengiyumva Shuncong Zhong Manting Luo Bing Wang Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhou350108China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhou350108P.R.China School of Mechanical and Electrical Engineering Putian UniversityPutian351100China

The use of terahertz time-domain spectroscopy(THz-TDS)for the nondestructive testing and evaluation(NDT&E)of materials and structural systems has attracted significant attention over the past two decades due to its superior spatial resolution and capabilities of detecting and characterizing defects and structural damage in non-conducting *** this study,the THz-TDS system is used to detect,localize and evaluate hidden multi-delamination defects(i.e.,a three-level multi-delamination system)in multilayered GFRP composite *** obtain accurate results,a wavelet shrinkage de-noising algorithm is used to remove the noise from the measured time-of-flight(TOF)*** thickness and location of each delamination defect in the z-direction(i.e.,through-the-thickness direction)are calculated from the de-noised TOF signals considering the interaction between the pulsed THz waves and the different interfaces in the GFRP composite laminates.A comparison between the actual and the measured thickness values of the delamination defects before and after the wavelet shrinkage denoising process indicates that the latter provides better results with less than 3.712%relative error,while the relative error of the non-de-noised signals reaches 16.388%.Also,the power and absorbance levels of the THz waves at every interface with different refractive indices in the GFRP composite laminates are evaluated based on analytical and experimental *** present study provides an adequate theoretical analysis that could help NDT&E specialists to estimate the maximum thickness of GFRP composite materials and/or structures with different interfaces that can be evaluated by the ***,the accuracy of the obtained results highlights the capabilities of the THz-TDS for the NDT&E of multilayered GFRP composite laminates.

关键词： Glass-fiber-reinforced polymer-matrix(GFRP)composites Terahertz time-domain spectroscopy(THz-TDS) Nondestructive testing and evaluation(NDT&E) Stationary wavelet transform(SWT) Thickness evaluation Delamination defects

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Simulation analysis and optimization of triple quadrupole mass spectrometer based on CFD 6

Simulation analysis and optimization of triple quadrupole ma...

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2023 6th World Conference on Mechanical Engineering and intelligent Manufacturing, WCMEIM 2023

作者： Huang, Dong Yin, Shugui Mao, Luyao Chen, Qiyu Mo, Ting Institute of Intelligent Manufacturing Guangdong Academy of Science Guangdong Key Laboratory of Modern Control Technology Guangzhou China Guangzhou Hexin Instrument Co. Ltd. Guangzhou China

CFD software conducted a hydrothermal simulation study of a triple quadrupole mass spectrometer. The results show that the auxiliary intake fan has a poor effect on cooling the PCB circuit board inside the mass spectrometer, but instead generates a vortex here, affecting the stability of the instrument. Besides, the reinforcing ribs on the bottom plate of the mass spectrometer and the orifice plate in the PCB slot prevent the flow of cooling air, resulting in high flow resistance and low cooling air volume. Therefore, structural optimization was carried out on the bottom plate and orifice plate of the mass spectrometer. The results show that after optimization, the air volume of the main intake fan increased by 6.2%, the air volume entering the PCB slot increased by 29.9%, and its proportion to the air volume of the main intake fan increased by 22.2%. The average temperature of the RF amplification board decreased by 17.3%, resulting in a better cooling effect. Meanwhile, simulation and comparison of the two installation positions of the dustproof cotton showed that installing the dustproof cotton around the bottom plate had a better effect. © Published under licence by IOP Publishing Ltd.

关键词： Orifices

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Towards a Unified Theory on the Superposition Principles 4th

Towards a Unified Theory on the Superposition Principles

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4th International Symposium on Automation, Mechanical and Design Engineering, SAMDE 2023

作者： Chen, Xiayu Wang, Bing Zhao, Chenmin Du, Dongmei Guan, Chenglong Zhong, Shuncong Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and Automation Fuzhou University Fuzhou350108 China Institute of Precision Instrument and Intelligent Measurement and Control Fuzhou University Fuzhou350108 China

ISBN: (纸本)9783031626630

Polymers and composites have been widely applied in many industries, especially in aerospace. There are growing demands for understanding their natural viscoelastic performance, especially in aerospace applications, where precise dimensional control and prediction of the residual strength and modulus are vital for the success of an aerospace vehicle. The existing superposition principles mainly focus on the well-known WLF-based horizontal shift to predict the long-term behaviour through short-term experimental tests in terms of creep or stress relaxation. Whilst the intrinsic microstructural changes or damages within a polymeric material due to viscoelastic deformation are not considered, which may lead to large differences for long-term predictions. Here, we look into the very fundamentals of the existing superposition principles, aiming to develop towards a unified theory to better predict the long-term relaxation modulus or creep of a polymeric solid. This is achieved by considering both the free volume theory-based horizontal shift factors and activation energy-based shift factors;microstructural changes or damages induced vertical shift factors are then coupled to improve the prediction accuracy of the superposition methods. These will facilitate long-term predictions and accelerated aging tests for viscoelastic solids. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Forecasting

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MMLN: Multi-directional and Multi-constraint Learning network for Remote Sensing Imagery Semantic Segmentation

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2024年 1-16页

作者： Sun, Hang Xie, Yongchang Ren, Dong Wen, Fangqing Tong, Lyuyang Chang, Laibin Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China Institute of Vehicle Information Control and Network Technology Hubei University of Automotive Technology Shiyan China School of Computer Science Wuhan University Wuhan China

Recent advances in satellite remote sensing technology and computer technology have significantly impacted practical applications in remote sensing image segmentation. However, the prevalent hybrid segmentation models that combine Convolutional Neural networks (CNNs) and Transformers, often overlook the critical exploration of local and global feature correlations across various scales. This exploration is essential for learning more representative features and strengthening context modeling capabilities. Additionally, the decoding layers of these models do not effectively exploit the pixel-level semantic relationships within cross-layer feature maps, thereby limiting the models' ability to discern small object features. To address these challenges, this paper introduces a Multi-directional and Multi-constraint Learning network (MMLN) designed for semantic segmentation of remote sensing imagery. This network features a Multi-directional Dynamic Complement Decoder (MDCD), which enhances the interaction between local and global features in the feature space, and subsequently improves the feature discrimination within the segmentation network. Moreover, a Multi-constraint Saliency Boundary-adaptive Module (MSBM) is implemented to reinforce the spatial constraints on saliency at the edge regions and ensure semantic consistency along the mask boundaries. This, in turn, augments the segmentation model's capability to detect small objects. The evaluation on four datasets reveals that the MMLN outperforms the existing state-of-the-art methods in remote sensing imagery segmentation. The code is available at https://***/zhongyas/MMLN. Authors

关键词： Semantics

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Steady-state Voltage Security-constrained Optimal Frequency control for Weak HVDC Sending-end AC Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 658-669页

作者： Qiangqiang Wang Liangzhong Yao Jian Xu Yuping Zheng Wei Li Wei Wang School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network(Wuhan University) Wuhan 430072China State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation(State Grid Electric Power Research Institute)Nanjing 211106China

Due to the fact that a high share of renewable energy sources(RESs)are connected to high-voltage direct current(HVDC)sending-end AC power systems,the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have *** has resulted in potential system operating problems such as overvoltage and overfrequency,which occur simultaneously when block faults exist in the HVDC *** this study,a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is *** integrated virtual inertia control of RESs is employed for system frequency *** dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security ***,an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is *** optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization *** are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC(LCC-HVDC)sending-end AC power system to verify the effectiveness of the proposed method.

关键词： Renewable energy source(RES) high-voltage direct current(HVDC) AC power system optimal frequency control steady-state voltage security dynamic reactive power compensation

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An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest

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材料科学技术（英文版） 2025年第6期209卷 300-310页

作者： Wenbo Chen Bingjun Yan Aidong Xu Xin Mu Xiufang Zhou Maowei Jiang Changgang Wang Rui Li Jie Huang Junhua Dong Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China General Research Institute China Oil & Gas Pipeline Network CorporationLangfang 065000China

One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction ***,this process often relies on human experience and judgment,which will introduce subjectivity and *** this paper,an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest *** can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS *** the typical scenario of metal corrosion,an atmospheric corrosion EIS dataset of low-carbon steel is constructed in this paper,which includes five different corrosion *** dataset was used to validate and evaluate the pro-posed method in this *** contributions of this paper can be summarized in three aspects:(1)This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm.(2)Using authentic EIS data collected from metal atmospheric corrosion,the paper es-tablishes a dataset encompassing five categories of metal corrosion scenarios.(3)The superiority of the proposed method is validated through the utilization of the established authentic EIS *** ex-periment results demonstrate that,in terms of equivalent circuit matching,this method surpasses other machine learning algorithms in both precision and ***,it shows strong applicability in the analysis of EIS data.

关键词： Electrochemical impedance spectroscopy Random forest Corrosion Equivalent circuit model

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