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3rd International Conference on Power Systems and Electrical Technology, PSET 2024

作者： Fang, Jingyang Jiang, Qin Yang, Hanqing Shandong University School of Control Science and Engineering Jinan China Sichuan University College of Electrical Engineering Chengdu China University of Electronic Science and Technology of China School of Automation Chengdu China

ISBN: (纸本)9798350353204

Extremely high current/voltage stresses challenge power electronics. This paper proposes a novel series of power converters, collectively referred to as Fractal (F) converters. F converters consist of several identical layers, which further comprise many identical cells or submodules. Salient benefits of F converters include but not limited to 1) modularity and scalability;2) boundless current and voltage ratings;3) high power quality;4) unified control applied to various layers;5) high reliability;6) control flexibility, e.g., for efficiency optimization. F converters will quickly find their applications in 1) high-voltage dc/ac transmissions;2) renewable energy generation;3) power quality enhancement equipment;4) electric vehicles;5) marine and aircraft propulsion;6) medical applications such as noninvasive magnetic stimulators;7) high-frequency high-power power supplies;8) plasma applications;9) future distributed power grids. For validations, simulation results are presented, demonstrating that F converters operate well as high-voltage and high-current inverters as well as arbitrary pulse generators. © 2024 IEEE.

关键词： Power converters

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Deep Learning Method for Leakage Location Detection of Pneumatic Systems Based on Infrared Thermal Image Evaluation 24

Deep Learning Method for Leakage Location Detection of Pneum...

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7th International Conference on Software engineering and Information Management, ICSIM 2024

作者： Chang, Jiaqi Shi, Yan Yang, Liman Niu, Yanxia Nie, Yulong Yang, Zhiguo Li, Lei Zhang, Wenchao School of Automation Science and Electrical Engineering Beihang University China Engineering Training Center Beihang University China Guangzhou Industrial Control Environmental Protection Technology Co. Ltd China

ISBN: (纸本)9798400709197

Pneumatic systems are an essential fluid transmission method in the industrial field, which can achieve the transmission and control of power or signals. Leakage in pneumatic systems is challenging to detect and is a highly harmful fault. Most existing leak detection methods use flow or pressure sensors to detect specific leakage amounts, while leak localization is still in the traditional manual detection, which significantly restricts localization efficiency. This article establishes a deep learning framework-based thermal image localization method for pneumatic system leak detection. Infrared images captured in the pneumatic system were collected, and then a deep-learning localization method based on the YOLO framework was established. Then, the recognition accuracy of this method was calculated. The results indicate that the accuracy has reached 99.5% of mAP_0.5 and 86.27% of mAP_0.5:0.95, indicating that this work is a meaningful study that can apply intelligent computing to engineering. © 2024 ACM.

关键词： Object detection

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An Improved YOLOv5 Model for Steel Surface Defect Detection by Integrating Multi-Dimensional Atrous Convolution

An Improved YOLOv5 Model for Steel Surface Defect Detection ...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Huang, Jianhang Jia, Lijie Zhou, Yitian Wang, Shuo Zhang, Xinliang Xu, Xiaozhuo School of Electrical Engineering and Automation Henan Polytechnic University Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment Jiaozuo China Zhoushan Yangwangnaxin Technology Co. Zhoushan China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo China

ISBN: (纸本)9798331504755

In deep network-based steel surface defect detection models, using only serial convolution operations can hinder the detection of small defects due to insufficient multi-scale detail information. To address this issue, a detection model based on joint multi-dimensional atrous convolution (JMDC) is proposed. By introducing atrous convolution with various kernel sizes into the feature extraction layer, a multi-channel parallel convolution chain is constructed to capture multi-scale defect features, enhancing the detail perception. Subsequently, a JMDC operator, generated from the residual network, fuses these features and establishes a channel constraint to improve the training stability and global feature extraction. Then by integrating the JMDC into the multi-level feature extraction layers, the improved YOLOv5 realizes the detection enhancement for the multi-scale defects. Correspondingly, the k-means algorithm is adopted to generate adaptive multi-scale anchor boxes with the reduction of the positional deviation. Experimental results show that the proposed approach has provided a detection accuracy of 81.7% on the NEU-DET dataset, yielding a significant improvement on the defect detection, especially for small targets. © 2024 IEEE.

关键词： K-means clustering

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Feedback Generative Adversarial Network With Channel-Space Attention for Image-Based Optimal Path Search Planning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4293-4307页

作者： Sun, Tao Li, Jian-Sheng Zhang, Yi-Fan Ru, Xin-Feng Wang, Ke Tsinghua University Department of Automation Beijing100084 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tongji University School of Economics and Management Shanghai200092 China

Path planning and seeking is one of the most challenging and interesting problems in the field of artificial intelligence. In this article, we propose a new image-based path planning algorithm to overcome traditional design concepts based on complex topological networks. Specifically, a novel feedback generative adversarial network learning model with channel-space attention (CSA-FGAN) is developed to search and plan an optimal path. It is worth noting that the input and output of the proposed feedback learning model are RGB images with complex spatial obstacle environment maps and RGB images with feasible paths, respectively. In particular, in order to further enhance the feature extraction ability and path prediction accuracy of image data, the feedback attention mechanism controls and improves the depth of the network by forming a closed loop of the proposed learning model. Final, three application scenario image examples are conducted to verify the superiority of the proposed path planning policy. © 2020 IEEE.

关键词： Motion planning

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An Early Multi-Fault Diagnosis Method of Lithium-ion Battery Based on Data-Driven 41

An Early Multi-Fault Diagnosis Method of Lithium-ion Battery...

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第41届中国控制会议

作者： Xin Gu Yunlong Shang Chijun Li Yuhao Zhu Bin Duan Jinglun Li Wenyuan Zhao School of Control Science and Engineering Shandong University School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Lithium-ion power battery is the "heart" of electric *** is significant to diagnose the battery fault quickly and accurately.A real-time data driven diagnosis approach for early battery faults based on improved principal component analysis is proposed in this *** technique rotates the battery pack voltage sequence into a new coordinate space through linear combination,while the detection metrics of square prediction errors and modified contribution plots are employed to achieve minor fault *** addition,the training sample of this method relies on the voltage sequence of the battery health state instead of the battery fault data which is difficult to *** experimental results demonstrate that this approach can not only locate the battery cell where the fault occurs,but also diagnose the open-circuit and short-circuit faults of the battery as well as the occurrence and duration of the fault in ***,the feasibility and robustness of the proposed method are verified by applying different experimental *** summary,the presented approach provides an easy-to-implement option that does not require accurate mathematical modeling,expert understanding,and complex computational processes.

关键词： Early fault diagnosis Lithium-ion battery pack Principal component analysis Data driven

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Mechanical behavior of entangled metallic wire materials-polyurethane interpenetrating composites

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Defence Technology（防务技术） 2023年第2期20卷 120-136页

作者： Xiao-yuan Zheng Zhi-ying Ren Hong-bai Bai Zhang-bin Wu You-song Guo College of Mechanical Engineering and Automation Fuzhou UniversityFuzhou350116China Institute of Metal Rubber&Vibration Noise Fuzhou UniversityFuzhou350116China Gongbang Vibration Control Technology Co. LtdJiangsuJiangyin214431China

Composite materials exhibit the impressive mechanical properties of high damping and stiffness,which cannot be attained by employing conventional single *** these lines,a novel material architecture is presented in this work in order to fabricate composites with enhanced mechanical *** specifically,entangled metallic wire materials were used as the active matrix,whereas polyurethane was employed as the reinforcement *** a result,an entangled metallic wire material-polyurethane composite with high damping and stiffness was prepared by enforcing the vacuum infiltration *** top of that,the mechanical properties(loss factor,energy consumption,and average stiffness)of the proposed composite materials were characterized by performing dynamic tests,and its fatigue characteristics were verified by the micro-interface bonding,as well as the macro-damage *** impact of the density,preloading spacing,loading amplitude,and exciting frequency on the mechanical properties of the composites were also thoroughly *** extracted results indicate that the mechanical properties of the composites were significantly enhanced than those of the pure materials due to the introduction of interface ***,the average stiffness of the composites was about 10 times the respective value of the entangled metallic wire ***,a rise in the loading period leads to some failure between the composite interfaces,which reduces the stiffness property but enhances the damping dissipation ***,a comprehensive dynamic mechanical model of the composites was established,while it was experimentally *** proposed composites possess higher damping features,i.e.,stiffness characteristics,and maintain better fatigue characteristics,which can broaden the application range of the *** addition,we provide a theoretical and experimental framework for the research and applications in the field of metal ma

关键词： Entangled metallic wire material Composites materials Damping property Stiffness Fatigue characteristics

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An analysis towards integrated control of wastewater collecting and treatment systems 27

An analysis towards integrated control of wastewater collect...

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Vasiliev, Iulian Luca, Laurentiu Barbu, Marian Vilanova, Ramon Caraman, Sergiu Department of Automation and Electrical Engineering Dunărea de Jos University of Galati Galati Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain

ISBN: (纸本)9798350337983

This paper deals with an analysis regarding the effect of Sewer Network operation on the performances of the integrated wastewater collecting and treatment system. The analysis is done by considering various control actions for the output storage tank of the sewer network, comparing a series of performance indicators defined for both subsystems with their "no control" value. Two cases have been considered regarding the control actions for the output storage tank of the sewer network: 1. keeping the output valve at a constant opening and 2. keeping the output valve at the maximum opening possible such as the outflow is limited to a constant value. While the second case did not prove advantageous, the first one showed that lowering the sewer network output valve opening would improve the integrated system performances. © 2023 IEEE.

关键词： Wastewater treatment

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Coupled Urban Risks:A Complex Systems Perspective with a People-Centric Focus

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工程（英文） 2025年第1期44卷 44-50页

作者： Min Ouyang Zekai Cheng Jiaxin Ma Hongwei Wang Stergios Aristoteles Mitoulis School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control Ministry of EducationHuazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Management Huazhong University of Science and TechnologyWuhan 430074China School of Engineering University of BirminghamBirmingham B15 2TTUK

The complexity of coupled risks,which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives,is inherent to cities functioning as dynamic,interdependent systems.A disruption in one domain ripples across various urban systems,often with unforeseen *** to this complexity are people,whose behaviors,needs,and vulnerabilities shape risk evolution and response *** cities as complex systems centered on human needs and behaviors is essential to understanding the complexities of coupled urban *** paper adopts a complex systems perspective to examine the intricacies of coupled urban risks,emphasizing the critical role of human decisions and behavior in shaping these *** focus on two key dimensions:cascading hazards in urban environments and cascading failures across interdependent exposed systems in *** risk assessment models often fail to capture the complexity of these processes,particularly when factoring in human *** tackle these challenges,we advocate for a standardized taxonomy of cascading hazards,urban components,and their *** its core is a people-centric perspective,emphasizing the bidirectional interactions between people and the systems that serve *** on this foundation,we argue the need for an integrated,people-centric risk assessment framework that evaluates event impacts in relation to the hierarchical needs of people and incorporates their preparedness and response *** leveraging real-time data,advanced simula-tions,and innovative validation methods,this framework aims to enhance the accuracy of coupled urban risk *** effectively manage coupled urban risks,cities can draw from proven strategies in real complex ***,given the escalating uncertainties and complexities associated with climate change,prioritizing people-centric strategies is *** approach will empower cities to bui

关键词： Coupled urban risks People-centric Risk management

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Harnessing Neural Unit Dynamics for Effective and Scalable Class-Incremental Learning 41

Harnessing Neural Unit Dynamics for Effective and Scalable C...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Depeng Wang, Tianqi Chen, Junwei Dai, Wei Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

Class-incremental learning (CIL) aims to train a model to learn new classes from non-stationary data streams without forgetting old ones. In this paper, we propose a new kind of connectionist model by tailoring neural unit dynamics that adapt the behavior of neural networks for CIL. In each training session, it introduces a supervisory mechanism to guide network expansion whose growth size is compactly commensurate with the intrinsic complexity of a newly arriving task. This constructs a near-minimal network while allowing the model to expand its capacity when cannot sufficiently hold new classes. At inference time, it automatically reactivates the required neural units to retrieve knowledge and leaves the remaining inactivated to prevent interference. We name our model AutoActivator, which is effective and scalable. To gain insights into the neural unit dynamics, we theoretically analyze the model's convergence property via a universal approximation theorem on learning sequential mappings, which is under-explored in the CIL community. Experiments show that our method achieves strong CIL performance in rehearsal-free and minimal-expansion settings with different backbones. Copyright 2024 by the author(s)

关键词： Adversarial machine learning

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DUAL-COMPONENT INTER-DEPENDENT FAILURE MECHANISM ANALYSIS OF DIESEL ENGINE BASED ON COUNTERFACTUAL INFERENCE

DUAL-COMPONENT INTER-DEPENDENT FAILURE MECHANISM ANALYSIS OF...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Li, Heng Huang, Shoujin Ding, Yong Lu, Ningyun CRllege of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing211106 China

ISBN: (纸本)9781837242689

For diesel engines, the coupling between the high-pressure oil pump and injector complicates fault diagnosis, and relationships between faults and symptoms are complex. Without analyzing inter-dependent failure mechanisms, it is straightforward to fall into the trap of pseudo-relevance with big data and there is also no guarantee of the accuracy and robustness of the predictive model. Multi-facto accidents are characterized by strong concealment, complex factor association, irreversible state, etc. Analyzing inter-dependent failure mechanisms remains a challenging problem in the reliability and safety of diesel engines. To address these challenges, this paper constructs a dual-component inter-dependent failure mechanism analysis method. First, a fault causal network is constructed using domain knowledge. Next, the Leaky Noisy-Or assumption and hidden variable nodes are incorporated to establish a Structural Causal Model (SCM). In addition, counterfactual inference based on do operator intervention in twin networks is employed to calculate two metrics: expected sufficiency and expected disablement, measuring the strength of the causal explanation of faults on the symptom. Finally, the case study demonstrates that this method effectively provides a clear causal chain of failure and intuitively reveals the causal relationship between fault causes and fault symptoms. © The Institution of engineering & Technology 2024.

关键词： Inference engines

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