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Influence of different anodised nanoporous structures on the anti-icing and electrical properties of transmission Al lines

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High Voltage 2025年第1期10卷 167-177页

作者： Xu Dai Yuan Yuan Jie Xiao Chenghao Jiang Xujiang Hua Huiying Xiang Tao Zhu Guoyong Liu Jiang Zhou Ruijin Liao State Key Laboratory of Power Transmission Equipment&System Security and New Technology Chongqing UniversityChongqingChina College of Materials Science and Engineering Chongqing UniversityChongqingChina Dongfang Electric Machinery Co. LtdDeyangChina

Ice accumulation of overhead transmission lines can lead to serious damage to power *** nanostructured Al conductors are proposed to replace the de-icing or ice-melting equipment for economic advantages,good anti-icing properties and robust electrical *** under different direct current densities is adopted to fabricate two nanostructures on Al conductors,including the reticular and honeycomb-like nanoporous *** to pure Al conductors,the anodised surface of honeycomb-like nanoporous structures exhibits lower ice adhesion(3.82 kPa)and ice *** conductor steel reinforced treated in the proposed method has also been validated to exhibit a significant anti-glaze icing ***-tionally,corona performance and line loss are experimentally measured and calculated to prove good electrical *** 0.27 A Al strand shows the highest corona inception voltage(27.86 kV)and the lowest AC resistance(4.65Ω/km),which is attributed to the good dielectric property and heat ***,the proposed anti-icing transmission conductors show profound application potential for power systems.

关键词： electrical structures properties

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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths

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Energy Informatics 2025年第1期8卷 1-12页

作者： Guo, Qi Lu, Yuanhong Zhang, Jie Zhang, Jingyue Huang, Libin Guo, Haiping Guo, Tianyu Tu, Liang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R & D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

The task scheduling problem based on directed acyclic graphs (DAGs) has been proven to be NP-complete in general cases or under certain restrictions. In this paper, building upon existing scheduling algorithms, we introduce a static task scheduling algorithm based on directed acyclic graphs. By incorporating the proportion of task transmission delay as a guiding metric in the optimization process, processors can be prioritized for tasks with high latency, thereby improving computational efficiency. We first validate the theoretical feasibility of the algorithm using a theoretical case study and illustrate the algorithmic effectiveness using two real case studies, direct current (DC) model and alternating current (AC) model respectively. The research indicates that the scheduling algorithm proposed in this paper achieves an average scheduling length improvement of over 1.2% compared to the Heterogeneous Earliest-Finish-Time algorithm (HEFT) in topologies with high latency tasks. Additionally, the experiments show that the HEFT algorithm consumes 39.85us and the EMT-DM algorithm consumes 38.29us during simulation using DC, and the HEFT algorithm consumes 31.23us and the EMT-DM algorithm consumes 26.51us during simulation using AC, both of which are improved compared to the HEFT algorithm. © The Author(s) 2025.

关键词： Flow graphs

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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

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Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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Diagnosis of unbalanced bearing fault samples based on cycle generative adversarial networks

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Neural Computing and Applications 2025年 1-21页

作者： Huang, Rihao Ma, Liangyu Hu, Jingchen Duan, Xiaochong Gao, Haitian Ma, Jin School of Control and Computering Engineering North China Electric Power University Baoding071003 China Baoding Key Laboratory of State Detection and Optimization for Integrated Energy System Baoding071003 China

The robust feature extraction capability of deep learning (DL) has rendered it a popular choice for fault diagnosis in various industries. However, the accuracy of fault diagnosis models is often compromised due to an imbalance between normal and faulty data during the production process. To address this issue, this study proposes an unbalanced bearing fault sample diagnostic method based on a cycle generative adversarial network, using vibration fault diagnosis of rotating machinery rolling bearings as an illustrative example for validation purposes. The method utilizes continuous wavelet transform (CWT) to convert the original vibration signal into time–frequency maps, which are then utilized as input for the cycle generative adversarial network. To address issues related to unstable training and timely convergence of the model, spectral normalization and weight decay techniques are introduced, thereby enhancing the performance of the improved cycle generative adversarial network in generating additional fault samples. Finally, the Swin Transformer model is employed for fault diagnosis and compared with other methods such as Random Forest (RF), Sparse Autoencoder (SAE), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The diagnostic experiment encompasses sample expansion, imbalanced proportion between normal and faulty samples, as well as scenarios involving limited sample sizes. Experimental results demonstrate that the proposed method can generate higher quality synthetic samples when training data is scarce;moreover, utilizing the Swin Transformer for diagnosis yields superior accuracy compared to alternative approaches such as RF, SAE, SVM, or CNN models—thus showcasing significant potential in addressing imbalanced data within fault diagnosis. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Convolutional neural networks

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Bioinspired Sensing of Undulatory Flow Fields Generated by Leg Kicks in Swimming

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 13895-13906页

作者： Wang, Jun Shen, Tongsheng Zhao, Dexin Zhang, Feitian Peking University State Key Laboratory of Turbulence and Complex Systems College of Engineering Department of Advanced Manufacturing and Robotics Beijing100871 China National Innovation Institute of Defense Technology Beijing100071 China

The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming have not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer’s leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results. © 2004-2012 IEEE.

关键词： Long short-term memory

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Experiment of 2×40Gbd PAM8 MISO-FSO system reinforced by high-speed optical signal coupling and precoder-shaped multi-level polar codes

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Optical and Quantum Electronics 2025年第1期57卷 1-18页

作者： Yang, Weiying Liu, Xiaoyu Xiao, Shilin Liu, Zhiyang The State Key Laboratory of Advanced Optical Communication System and Networks Shanghai Jiao Tong University Dongchuan Road Shanghai200240 China

This paper proposes and successfully demonstrates a high-speed optical signal coupling (HS-OSC) of 2x40Gbaud PAM8 with precoder-shaped multi-level polar codes (PS-MLPC) in a gain-oriented multiple-input single-output free space optical (MISO-FSO) system. With the pilot-based correction (PBC), the system gets a multi-path error (MPE) detecting and correcting module, which can minimize the MPE and achieve the gain-oriented HS-OSC. On the other hand, PS-MLPC is deployed in the MISO-FSO system to provide the non-uniform PAM-8 symbols and save the power budget. In the experiment, the PBC module is proven to ensure the HS-OSC process by comparing the captured waveforms. Results in the static FSO channel validate that the bit error rate (BER) of the MISO-FSO system is improved from 4.76×10-3 to below 10-5 and the PS-MLPC PAM-8 saves most 0.85 dB effective signal-to-noise ratio (ESNR). Under turbulent conditions, the gain-oriented MISO-FSO system not only enhances the mean ESNR of about 4.3–5.4 dB but also mitigates the standard deviation of ESNR by 40.6–61.4 %, on which the PS-MLPC provides a Q-factor gain of 1.17–1.64 dB. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Budget control

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Optimal Linear Codes With Few Weights From Simplicial Complexes

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IEEE Transactions on Information Theory 2025年第5期71卷 3531-3543页

作者： Chen, Bing Xu, Yunge Hu, Zhao Li, Nian Zeng, Xiangyong Hubei University Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Wuhan430062 China Hubei University Key Laboratory of Intelligent Sensing System and Security Ministry of Education Hubei Provincial Engineering Research Center of Intelligent Connected Vehicle Network Security School of Cyber Science and Technology Wuhan430062 China State Key Laboratory of Integrated Service Networks Xi’an710071 China Hubei University Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Key Laboratory of Intelligent Sensing System and Security Ministry of Education Wuhan430062 China

Recently, constructions of optimal linear codes from simplicial complexes have attracted much attention and some related nice works were presented. Let q be a prime power. In this paper, by using the simplicial complexes of Fmq with one single maximal element, we construct four families of linear codes over the ring Fq+uFq}( u2=0 ), which generalizes the results of Wu et al. (2020). The parameters and Lee weight distributions of these four families of codes are completely determined. Most notably, via the Gray map, we obtain several classes of optimal linear codes over Fq, including (near) Griesmer codes and distance-optimal codes. Moreover, it is shown that most of the Gray images are minimal or self-orthogonal codes which are useful in applications. © 1963-2012 IEEE.

关键词： Turbo codes

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Distributed Bundle Adjustment Based on Penalty Function Method

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IEEE robotics and Automation Letters 2025年第6期10卷 5449-5456页

作者： Sun, Qixuan Zhang, Guanghui Zhu, Dongchen Wang, Lei Zhang, Xiaolin Li, Jiamao Chinese Academy of Sciences Bionic Vision System Laboratory State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Shanghai200050 China University of Chinese Academy of Sciences Beijing100049 China

Bundle Adjustment (BA) aims to estimate the camera poses and build maps utilizing the nonlinear optimization algorithm. The update step of the optimization is obtained by solving a linear system, which is the bottleneck of the BA efficiency. Many works perform bundle adjustment in a distributed manner to reduce the computational cost of solving the linear system and achieve outstanding performance. However, the distributed methods implement the constrained optimization method that involves the computation of the Lagrange multiplier, causing extra overhead. To improve the efficiency of BA, we propose a novel distributed algorithm based on the penalty method, dubbed PenBA, that formulates an unconstrained problem and hence saves the computation of extra variables. To solve the unconstrained linear system with low cost, we design a novel distributed Preconditioned Conjugate Gradient (PCG) which has complexity bounded by hyper-parameters. It can be proved that, given the parameter update strategy of the optimization method, the penalty linear system can be solved with fast convergence. Experimental results in the BAL dataset illustrate that our penalty method outperforms the Lagrange multiplier method and conventional BA. Compared with the most accurate conventional PCG-based BA solver, PenBA decreases the objective values by 3.8%, the time per iteration by 17% and the maximum memory consumption by 24%. Experimental results in the SfM and SLAM datasets prove that PenBA applies to both computer vision and robotics contexts. © 2016 IEEE.

关键词： Constrained optimization

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Improved calibration and 3D reconstruction for micro fringe projection profilometry

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Optics Express 2025年第6期33卷 13455-13471页

作者： Zhang, Chenfan Zhu, Dongchen Shi, Wenjun Wang, Lei Li, Jiamao Bionic Vision System Laboratory State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China University of Chinese Academy of Sciences Beijing100049 China

Micro fringe projection profilometry (MFPP) is a crucial three-dimensional measurement technology widely used in industrial inspection. As the system measurement accuracy is limited by calibration and reconstruction errors, this paper proposes a joint calibration of telecentric camera and projector, and develops noise-robust 3D reconstruction, ultimately forming a high-precision MFPP for microscopic object measurement. Specifically, the optimal parameters for the telecentric camera model are determined by constructing a virtual 3D calibration target, which circumvents the limitations that plane-based calibration methods often produce local optimal solutions. In response to the presence of phase errors, a method employing global homography is proposed to refine the projector pixel coordinates of feature points, thus enhancing the calibration accuracy of the projector. Furthermore, we integrate epipolar constraints into the reconstruction process, which helps eliminate noise points and optimizes the reconstruction results by constructing epipolar deviation. Extensive experiments demonstrate that our MFPP system can achieve micron-level measurement accuracy. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Profilometry

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Partial Solution Operator Discretization-Based Methods for Efficiently Computing Least-Damped Eigenvalues of Large Time Delayed Power systems

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CSEE Journal of Power and Energy systems 2025年第2期11卷 671-682页

作者： Hua Ye Xiaofan Jia Muyang Liu Yutian Liu Sicong Zhang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of EducationShandong UniversityJinan 250061China School of Electrical Engineering Xinjiang UniversityUrumqi 830046China State Grid Jiangsu Electric Power Research Institute Nanjing 211103China

To investigate impact of time delays on the small signal stability of power systems, the least-damped eigenvalues with the smallest damping ratios have been calculated by eigen-analysis methods based on Solution Operator Discretization (SOD) with Pseudo-Spectral collocation (PS) and Implicit Runge-Kutta (IRK) methods. This paper evolves SOD-PSIIRK into their partial counterparts, i.e., PSOD-PSIIRK, with greatly enhanced efficiency and reliability in analyzing large-scale time delayed power systems. Compared with SOD-PSIIRK, PSOD-PSIIRK are characterized in constructing low order discretization matrices of solution operator as well as efficiently and directly solving the embedded Matrix-Inverse-Vector Products (MIVPs). The dimensions of the discretization matrices of solution operator are largely reduced as only the retarded state variables are discretized, rather than all state variables as in SOD-PSIIRK. Meanwhile, the proposed PSOD-PSIIRK optimize the most computationally expensive operations in SOD-PSIIRK by avoiding the iterative solutions to the two embedded MIVPs. PSOD-PS/IRK directly and efficiently compute the MIVPs via factorizing the Kronecker product-like discretization matrices of the solution operator into Schur complements. The Central china-North china ultra-high-voltage power grid with 80577 state variables serves to validate the proposed PSOD-PSIIRK and shows that compared with SOD-PSIIRK, the computational time consumed by PSOD-PSIIRK is cut down by 49.96 times without loss of any accuracy.

关键词： Eigenvalue analysis low frequency oscillation Schur complement decomposition small signal stability solution operator discretization spectral discretization time delay wide-area measurement system

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