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IEEE International Conference on Industrial Technology (ICIT)

作者： Yiheng Chen Fan Yin Xiaochong Chen Yi Ren Jie Hu Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an efficient coke pushing plan. To address this issue, this paper proposes a scheduling method based on the particle swarm optimization algorithm. Firstly, the fuzzy c-means clustering is utilized to categorize actual operating conditions as either normal or abnormal, thereby facilitating the scheduling of pushing plan under disparate conditions. Subsequently, the scheduling problem for the pushing plan is transformed into a traveling salesman problem, and scheduling models under various conditions are established. Finally, to accelerate the convergence and enhance the algorithm's global search capability, an adaptive inertia adjustment strategy is employed to dynamically regulate the velocity and position of particles. The proposed method has been implemented in the coking process. Through the analysis of application results, the completion coefficient of pushing plan has been increased by 4.25%, demonstrating that the proposed has advantages in scheduling the pushing plan during the actual coking process.

关键词： Job shop scheduling Heuristic algorithms Clustering algorithms Production Traveling salesman problems Stability analysis Robustness complexity theory Particle swarm optimization Convergence

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network

Pipeline Anomaly Detection Based on KPCA and Cosine Distance...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Kang Yi Xin Liu Wenkai Hu Yupeng Li School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Accurately and promptly detecting the pipeline anomaly is crucial to the safe operation of pipeline systems, while a difficulty lies in that many existing methods require massive data for training models. However, pipelines are running under normal state for the most of the time, and labeled pipeline anomaly data is usually scarce. Among the commonly used sensors, vibration sensors are widely utilized in pipeline detection because of their advantages such as easy installation and high sensitivity. However, the vibration signal shows non-stationary characteristics when anomalies occur, and are contaminated by noises, making it difficult to represent the actual state with features extracted from either the time or frequency domain. Accordingly, this paper proposes a pipeline anomaly detection method based on the KPCA (kernel principal component analysis) and cosine distance prototypical network. First, features are extracted from original signals; then, the feature dimension is reduced by KPCA; last, the cosine distance is introduced to the prototypical network for anomaly detection. The effectiveness of the proposed method is demonstrated by case studies involving experimental data.

关键词： Vibrations Training Time-frequency analysis Sensitivity Pipelines Sensor phenomena and characterization Feature extraction Time-domain analysis Anomaly detection Principal component analysis

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Unit commitment with bidirectional ramping constraints of flexibility retrofit thermal power unit

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International Journal of Electrical Power and Energy systems 2025年 168卷

作者： Jiang, Jingxiao Zhu, Yanran Wang, Ying Guo, Xiaorui Lv, Jianhu Qin, Jianxiang Yan, Xingyun Zhang, Kaifeng Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China China Electric Power Research Institute Nanjing210003 China State Grid Ningxia Electric Power Co. Ltd. Yinchuan 750001 China

Flexibility retrofits of thermal power units have been widely implemented to improve power system balancing. These retrofits enable operation below the regular minimum output, known as deep peak regulation, to accommodate increasing renewable energy integration. Due to the inherent characteristics of thermal power units, ramp-up rates and ramp-down rates generally differ. Existing studies often overlook this difference by assuming equal ramping rates. To bridge this gap, this paper systematically models and analyses bidirectional ramping constraints in unit commitment (UC) models, providing a more accurate and realistic representation of the ramping process. Specifically, this paper proposes three innovative bidirectional ramping models. The first is the all-period fixed bidirectional ramping (AFBR) model, which assumes a constant ramp rate across all periods. The second model is the interperiod dynamic bidirectional ramping (InterDBR) model, which captures variations in ramping rates across different peak regulation states, including deep peak regulation with oil (DPRO), deep peak regulation (DPR), and regular peak regulation (RPR). These ramping rate adjustments are restricted to interperiod scheduling periods. The third is the intraperiod dynamic bidirectional ramping (IntraDBR) model, which considers transitions between DPRO, DPR, and RPR within an intraperiod scheduling period, thereby reflecting actual operational conditions of the unit. We validate the effectiveness of the proposed bidirectional ramping models on the IEEE 118-bus system and a real-world Ningxia Power Grid system. Results demonstrate that bidirectional ramping models more accurately and effectively support dispatch scheduling decisions, improving system security and economic efficiency. © 2025 The Authors

关键词： Retrofitting

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Multi-scale Dilated Attention-based Generative Adversarial Network for Infrared and Visible Image Fusion

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Current Optics and Photonics 2025年第2期9卷 120-129页

作者： Yang, Shunyuan Shi, Xiaoping Huo, Ju Sun, Kangjian Wang, Yu School of Astronautics Harbin Institute of Technology Harbin150001 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150001 China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China Shanghai Space Propulsion Technology Research Institute Shanghai201109 China

In the field of optics, infrared and visible images are often required for use in different situations. In particular, in the field of optical sensors, infrared and visible sensors are mainly used to obtain different band images, which are applied to improve the comprehensive information content of images and to improve the quality and availability of images. In existing infrared and visible image fusion methods, the focus is often placed on retaining the background information from visible images and the salient targets from infrared images. To address this issue, we introduce a multi-scale dilated attention module into the encoder-decoder structure of the generator. By applying dilated convolution and selfattention mechanisms, this module improves the perceptual capability of the model, thereby improving performance without increasing network complexity. This design emphasizes gradient information and detailed features in visible images. Experimental results on the public TNO dataset demonstrate that our method achieves superior visual quality and preserves the most abundant image information. Moreover, experiments on spacecraft images validate the robustness and applicability of our approach. Simultaneously, our method also provides significant technical support for the optical field. © 2025 Current Optics and Photonics.

关键词： Image coding

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Dynamic gesture tracking using wearable data gloves with flexible FBGs

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Sensors and Actuators A: Physical 2025年 390卷

作者： Qian, Muyun Yan, Haitang Wang, Wanying Sun, Zelin Dong, Yaohui Wei, Xinyuan Wang, Hanbin School of Electrical and Information Engineering Anhui University of Technology Anhui Ma'anshan243002 China Anhui Province Engineering Laboratory of Intelligent Demolition Equipment Anhui Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Anhui Ma'anshan243002 China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Anhui Hefei230009 China School of Intelligent Electromechanical Engineering Zhongyuan University of Technology Henan Zhengzhou450007 China

Existing wearable data gloves for gesture recognition often face challenges in achieving both high precision and real-time performance. To address these limitations, we propose a data glove design incorporating fiber Bragg gratings (FBGs) encapsulated in flexible materials and positioned near the interphalangeal joints. This setup enables effective gesture recognition. First, the principle of fiber grating curvature sensing is derived, followed by curvature calibration of the FBG data glove through flexible encapsulation. An experimental platform was constructed to assess the glove's performance in static and dynamic digital gesture recognition. Calibration results demonstrate a linear correlation between wavelength drift and curvature changes, with a comprehensive sensitivity of 0.0126 nm/°. Static and dynamic experimental findings confirm that the FBG sensors effectively monitor wavelength shifts induced by finger curvature variations. Analysis of different digital gestures at various time intervals revealed the wavelength offsets corresponding to the straightening and bending states of each finger. The five FBG sensors, encapsulated in flexible materials and positioned at the proximal interphalangeal joints, capture curvature changes across the five fingers, enabling accurate, real-time recognition of both static and dynamic gestures. This study highlights the potential of the developed wearable data glove for tracking and recognizing fine movements of the human hand. © 2025 Elsevier B.V.

关键词： Gesture recognition

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Numerical investigation of pitching airfoil subjected to incoming gust

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Physics of Fluids 2025年第5期37卷

作者： Shao, Mingyu He, Lihao McFarland, D. Michael Jiang, Hanbo Chen, Shiyi State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China Eastern Institute for Advanced Study Eastern Institute of Technology Zhejiang Ningbo315200 China Ningbo Institute of Digital Twin Eastern Institute of Technology Zhejiang Ningbo315200 China

This work investigates the aerodynamic and acoustic response of a pitching airfoil subjected to time-harmonic gust flows. A low-dissipation and dispersion numerical solver of compressible Navier-Stokes equations was developed with the kinetic energy preserving flux scheme. The incoming gust perturbations were introduced via the momentum source method. Then, the interaction between a gust and a pitching airfoil is subsequently analyzed. In the absence of incoming gusts, the wake of the airfoil is composed of a series of vortex pairs convected downstream, while the lift and drag curves exhibit stable periodic variations. The presence of the gust has significant impact on the wake structure and aerodynamics of the pitching airfoil. Specifically, when the gust has a small wavenumber, the phase of the gust significantly influences the far-field sound. Interestingly, the symmetry of the lift and drag curves, as well as the wake structure, varies with the wavenumber of the incoming flow. The phase angle of the inflow gust also impacts the wake pattern and the aeroacoustics of the pitching airfoil evidently. A gust with a smaller amplitude has minor effects on the aerodynamics and aeroacoustics of the pitching airfoil. © 2025 Author(s).

关键词： Kinetic energy

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A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning

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IEEE Transactions on Transportation Electrification 2025年

作者： Wu, Tao Dai, Peipei Xue, Gang Guo, Youguang Lei, Gang Zhu, Jianguo Wang, Yifei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Technology Sydney School of Electrical and Data Engineering NSW2007 Australia University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

Thermal modeling and analysis are critical for permanent magnet linear synchronous motors (PMLSMs), particularly in multi-physical analysis and motor design optimization. This paper proposes a new method for thermal steady state modeling and analysis based on transfer learning, which combines the thermal mechanism model with the data-driven model to achieve high-precision temperature analysis with small number of finite element analysis (FEA) samples. First, an equivalent thermal circuit (ETC) model is established for PMLSMs based on the structural parameters and heat transfer principles. Second, a hybrid model based on transfer learning is developed: the model is pre-trained by a large sample set generated from the ETC in the source field (mechanism analytical model), and then the trained model is transferred to the target field (FEA data-driven model). The parameters of the neural network in the target field are optimized by a few FEA sample sets with higher precision to improve the prediction accuracy of the target model. Experimental results demonstrate that the proposed method significantly boosts the performance of the deep neural network (DNN) model, particularly when training sets are small. The root mean square error (RMSE) of the DNN model decreases by 0.901 in the 5:5 (training/testing) dataset and 1.726 in the 2:8 dataset;and the corresponding R2 and maximal absolute error of motor performances are significantly decreased. The smaller the proportion of the training set, the better performance of the hybrid modeling will achieve. Furthermore, a temperature rise experiment conducted on a prototype motor validates the efficacy and precision of the proposed hybrid modeling methodology. © 2015 IEEE.

关键词： Permanent magnets

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ForkXplorer:an approach of fork summary generation

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Frontiers of Computer Science 2022年第2期16卷 1-15页

作者： Zhang ZHANG Xinjun MAO Chao ZHANG Yao LU Key Laboratory of Software Engineering for Complex Systems College of ComputerNational University of Defense TechnologyChangsha 410073China

Pull-based development has become an important paradigm for distributed software *** this model,each developer independently works on a copied repository(i.e.,a fork)from the central *** is essential for developers to maintain awareness of the state of other forks to improve collaboration *** this paper,we propose a method to automatically generate a summary of a *** first use the random forest method to generate the label of a fork,i.e.,feature implementation or a bug *** on the information of the fork-related commits,we then use the TextRank algorithm to generate detailed activity information of the ***,we apply a set of rules to integrate all related information to construct a complete fork *** validate the effectiveness of our method,we conduct 30 groups of manual experiment and 77 groups of case studies on *** propose Fea_(avg)to evaluate the performance of Fea_(avg)the generated fork summary,considering the content accuracy,content integrity,sentence fluency,and label extraction *** results show that the average of of the fork summary generated by this method is *** than 63%of project maintainers and the contributors believe that the fork summary can improve development efficiency.

关键词： open source software pull-based development fork summary distributed cooperative development

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Distributed Framework Construction for Affine Formation Control

arXiv

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arXiv 2025年

作者： Li, Huiming Chen, Hao Wang, Xiangke Li, Zhongkui Shen, Lincheng College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China Laboratory of Science and Technology on Integrated Logistics Support National University of Defense Technology Changsha410073 China The State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

In affine formation control problems, the construction of the framework with universal rigidity and affine localizability is a critical prerequisite, but it has not yet been well addressed, especially when additional agents join the formation or link/agent failures emerge. Motivated by this observation, we investigate the problem of constructing affine formation frameworks in three scenarios, including vertex addition, edge deletion and vertex deletion. Our approach starts from the original affine formation and uses geometric methods to locally adjust the structure of the weighted graph to describe the topology, so that the modified framework maintains the universal rigidity and affine localizability. Notably, the developed strategies only utilize local measurements and exhibit distributed characteristics, laying the foundation for applications in multi-agent systems. To demonstrate the compatibility with affine formation control proposals, we present a case study on affine formation tracking in a multi-UAV formation, demonstrating the effectiveness of our algorithms in constructing eligible frameworks in aforementioned scenarios. Moreover, a comparative simulations is also conducted to highlight the low time complexity of our distributed algorithm relative to the centralized optimization-based method. Copyright © 2025, The Authors. All rights reserved.

关键词： Rigidity

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Network structure governs Drosophila brain functionality

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Fundamental Research 2025年

作者： Zhang, Xiaoyu Yang, Pengcheng Feng, Jiawei Wen, Kang Yan, Gang Luo, Qiang Lin, Wei Lu, Xin College of Systems Engineering National University of Defense Technology Changsha 410073 China Xiangjiang Laboratory Changsha 410205 China Research Institute of Intelligent Complex Systems Fudan University Shanghai 200433 China MOE Key Laboratory of Advanced Micro-Structured Materials School of Physical Science and Engineering Tongji University Shanghai 200092 China

How intelligence emerges in living beings is a fundamental but largely unanswered question in neuroscience. To address this challenge, we leveraged the largest available data set of adult Drosophila connectome, and constructed a comprehensive computational framework using simplified neuronal activation mechanisms to mimic the observed activation behavior within the connectome. The results revealed that even with rudimentary neuronal activation mechanisms, models grounded in real neuronal network structures can generate activation patterns strikingly analogous to those observed in the actual brain. A significant discovery was the consistency of activation patterns across various neuronal dynamic models with the same network structure. This consistency results therefore underscore the pivotal role of network topology in neural information processing, but challenge the prevailing view that solely relies on neuron count or complex individual neuron dynamics. Further analysis demonstrated a near-complete separation of the visual and the olfactory systems at the network level. Moreover, we found that the network distance, rather than spatial distance, is the primary determinant of activation patterns, and also that a reconnect rate of at least 1^o/_oo was sufficient to disrupt the previously observed activation patterns. We also observed synergistic effects between the brain hemispheres: Even with unilateral input stimuli, visual-related neurons in both hemispheres were activated, highlighting the importance of interhemispheric communication. All these findings suggest the crucial role of network structure in neural activation and offer novel insights into the fundamental principles governing brain functionality. © 2025 The Authors

关键词： Activation pattern Brain network Drosophila connectome Network communication model

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