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International Conference on Applied Nonlinear Dynamics, Vibration, and control, ICANDVC 2023

作者： Wu, Jie Chen, Jianen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9789819705535

In this paper, a nonlinear energy sink (NES) is designed to suppress the vibrations of a rectangular plate, where the vibrations within a non-resonant band of the plate are mainly investigated. The selected frequency range is 9–11 Hz with a loading frequency interval of 0.5 Hz. The harmonic excitation experiments with fixed frequency are conducted within the non-resonant band to obtain its amplitude-frequency curves. The results indicate that the NES always has effective vibration absorption with the variations in NES mass and spring stiffness under low excitation accelerations. However, the rectangular plate exhibits a higher branch of response within the low-frequency range under high excitation accelerations. Metrics such as the effective value of response acceleration and the vibration level are introduced to evaluate the experimental results to analyze the vibration absorption of the NES. The study reveals that optimal performance is achieved when a non-weighted NES with a spring having a wire diameter of 1.2 mm and an external diameter of 10 mm is attached to the rectangular plate. This device yields a reduction of vibration level by 7.29 dB. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Rectangular plate

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Parametric Study on Performance of Parallel Asymmetric Nonlinear Energy Sinks

Parametric Study on Performance of Parallel Asymmetric Nonli...

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International Conference on Applied Nonlinear Dynamics, Vibration, and control, ICANDVC 2023

作者： Li, Huiyang Chen, Jianen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9789819705535

The complexification-averaging method is utilized to study the amplitude-frequency response of a system connected to a parallel asymmetric nonlinear energy sink (NES) under harmonic excitation, and the Runge-Kutta method is used to analyze the change law of the frequency band of the higher branches of response and the strongly modulated responses with the assistance of the complexification-averaging method. Under shock loading, the effect of parallel asymmetric NES parameters on its vibration absorption efficiency is investigated. The results demonstrate that the frequency band of higher branches of response is widened by reducing the stiffness ratio, mass ratio, and damping ratio of the two NES, emphasizing the fact that the frequency band of the strongly modulated response can be widened or narrowed with the reduction of these parameters. Moreover, reducing the mass ratio and damping ratio of the two NESs decreases the vibration absorption efficiency when the system is subjected to a shock load. However, the vibration absorption efficiency increases by reducing the stiffness ratio. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Energy dissipation

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Dunhuang murals image inpainting method based on fusion classification pre-training model

Dunhuang murals image inpainting method based on fusion clas...

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2024 International Conference on Culture-Oriented Science and Technology, CoST 2024

作者： Ren, Hui Zhang, Chengya Sun, Ke Ye, Chenyu Communication University of China School of Information and Communication Engineering Beijing100024 China Ministry of Culture and Tourism Key Laboratory of Audiovisual Technology and Intelligent Control System Beijing100024 China Beijing Key Laboratory of Modern Performing Arts Technology Beijing100024 China University of Pennsylvania School of Engineering and Applied Science PA19104 United States

ISBN: (纸本)9798350380347

Murals are an important part of China's cultural heritage. Because of their age, Dunhuang murals have suffered from discoloration, fading and damage. With the development of computer image restoration technology, digital image processing provides strong support for mural restoration. Although there are many research results in the field of ancient mural images, there is no pre-trained model based on ancient mural images available for migration. There is a method for Dunhuang murals image restoration based on Generative Adversarial Network (GAN) with improved ResNet50 structure as an encoder in the generator. This research result proposes a generative adversarial network model with a parallel double convolutional extraction of deep features for the generator, combined with a ternary heterogeneous joint discriminator. On this basis, this paper proposes a binary classification task to distinguish ancient mural images from modern natural style images, so that the model pre-learns features such as color, texture, and structure of mural images, which are inputted into the restoration network as a priori information, in order to achieve the effect of reducing the probability of incomplete restoration of the model, and better generalization ability. The experimental results show that the method proposed in this paper has an overall improvement in the evaluation indexes such as Peak Signal to Noise Ratio(PSNR) and Structural Similarities(SSIM) when compared with other methods, and the restored images are more in line with human subjective vision, which proves the validity of the method. © 2024 IEEE.

关键词： Generative adversarial networks

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An autonomous path planning method considering terrain aided navigation constraints

An autonomous path planning method considering terrain aided...

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2022 Chinese Automation Congress, CAC 2022

作者： Jiang, Min Xu, Cheng Ji, Hua Wang, Yuqi Engineering Institute Beijing Electro-Mechanical Bejing China Beijing Electro-Mechanical Engineering Institute System Control and Intelligent Agent Cooperation Laboratory Science and Technology on Complex Bejing China

ISBN: (纸本)9781665465335

In order to solve the autonomous path planning problem with terrain aided navigation constraints, a navigation-first path planning method was adopted, that is, the distribution of terrain matching regions and the drift of navigation errors were given priority, and the path planning problem was transformed into the shortest path problem of single source directed graph to determine the nodes on the path. Secondly, the path planning between adjacent nodes is transformed into a path planning problem with initial direction constraint and terminal direction freedom/constraint, and the lateral path is smoothed. Finally, for the local path passing through the no-fly zone, the obstacle avoidance path planning with initial and terminal direction constraints is carried out based on convex optimization method. The simulation results show that the autonomous path planning method considering terrain aided navigation constraints can plan the shortest flight path under the constraints of navigation accuracy, maneuverability and no-fly zone. © 2022 IEEE.

关键词： Motion planning

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Simulation Testing of Large-Scale Grid-Connected Wind Power with Energy Storage system Based on Active Support Performance Evaluation Indices 10

Simulation Testing of Large-Scale Grid-Connected Wind Power ...

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10th International Forum on Electrical Engineering and Automation, IFEEA 2023

作者： Zhu, Yihua Hu, Yun Tu, Liang Su, Mingzhang Luo, Chao Csg State Key Laboratory of Hvdc Electric Power Research Institute Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China China Southern Power Grid Csg Key Laboratory for Power System Simulation Electric Power Research Institute Guangzhou China

ISBN: (纸本)9798350309379

This paper establishes simulation modeling for large-scale grid connected wind power with energy storage system (ESS). The conventional grid-following (GFL) based ESS is used as a reference object to test the active support performance of large-scale grid-connected wind power with grid-forming (GFM) based ESS with active support performance evaluation indices in different scenarios. (1) Small disturbance evaluation indices: The point of common coupling (PCC) frequency/voltage drop depth and recovery time. (2) Large disturbance evaluation indices: The PCC frequency/voltage drop depth and rise height after fault removal. The output active/reactive power drop depth and rise height/recovery time after fault removal. (3) Island capability evaluation indices: The PCC frequency/voltage fluctuation amplitude at the moment of switching and system stability after switching. © 2023 IEEE.

关键词： active support performance evaluation indices different scenarios grid-following (GFL) grid-forming (GFM)

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Weak-Model Based Reinforcement Learning control Strategy of Aircraft Attitude system

Weak-Model Based Reinforcement Learning Control Strategy of ...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Huang, Dingcui Hu, Jiangping Peng, Zhinan Hao, Mingrui School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811581540

intelligent aircraft control is an important strategic development trend. Traditional aircraft control algorithms have a strong dependence on the system models, and it is difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, an online intelligent controller design based on a weak-model reinforcement learning technology is proposed to solve stabilization problem of an aircraft. The control problem is firstly converted to an optimal control problem, then an adaptive dynamic programming (ADP) technology is applied for computing the corresponding nonlinear Hamilton-Jacobi-Bellman equation (HJB) equation. Then, actor-critic neural networks structures are established to learn the optimal controller online where only partial information of the aircraft dynamics is required. The proposed control strategy enables the aircraft to adjust and update its control strategy on-line according to the actual mission targets and environments, such that the requirements of autonomous learning and intelligent operation can be realized. Finally, simulation example is offered to validate the effectiveness of the proposed weak-model based controller design. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Research on intelligent Fault Diagnosis Method of Planetary Gearbox based on ITD and CNN 15

Research on Intelligent Fault Diagnosis Method of Planetary ...

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15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Zhu, Songsong Chen, Jiwei Xie, Ruitong Song, Yuhao Zhang, Mian Zhao, Mengxiong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350354010

Accurate fault diagnosis of planetary gearboxes (PGs) is crucial for preventing equipment failures and extending their lifespan. To enhance the efficiency and accuracy of PG fault diagnosis, this paper proposes a novel method integrating intrinsic time scale decomposition (ITD) with convolutional neural network (CNN). The proposed method leverages the demodulation capability of ITD to decompose and reconstruct the original signal, effectively removing irrelevant noise and isolating core fault features, and the learning ability of CNN to accurately identify the fault features. Compared to methods relying on CNN only, the proposed method not only improves the computational efficiency but also achieves higher fault diagnosis accuracy. © 2024 IEEE.

关键词： Convolutional neural networks

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Application and Performance Evaluation of Object Detection Technology Based on Computer Vision

Application and Performance Evaluation of Object Detection T...

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Asian control Conference

作者： WeiXue Li Hang Zhang Cong Wan JiaWen Shi TingRu Li National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Talent Exchange Center Ministry of Industry and Information Technology P.R.C. Beijing China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In light of the challenges posed by the variability of industrial part shapes, weak texture information, and surface reflections in current industrial vision inspection, traditional methods such as feature descriptors and template matching are inadequate. This paper innovatively proposes a machine learning object detection method, establishes robust stable features for weakly textured industrial parts, and evaluates the performance of the model and feature selection in combination with actual fuel tank cap detection tasks. Firstly, we construct a dataset of fuel tank cap targets and establish a comprehensive and relatively stable feature dataset, including geometric features, texture features, and color features. Secondly, through ablation experiments and comparative experiments, we conduct intelligent per-formance testing on model detection accuracy, parameter selection, and feature contribution. Finally, the evaluation results demon-strate that the support vector machine (SVM) model exhibits the best detection performance after feature selection, with a detection accuracy of 99.0% under the optimal parameter settings validated through experiments.

关键词： Support vector machines Adaptation models Image color analysis Computational modeling Fuel storage Object detection Inspection

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Single Domain Generalization in Vibration Damper Detection Using Frequency Domain Attention and Scale-Invariant Learning

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IEEE Transactions on Power Delivery 2025年

作者： Yang, Ke Zhao, Xiaoyu Ge, Xinyu Hu, Zhedong Wang, Qianming Zhai, Yongjie North China Electric Power University School of Control and Computer Engineering Baoding071003 China Baoding Key Laboratory of Intelligent Robot Perception and Control in Electric Power System Baoding China

Improving the generalization capability of vibration damper detection model for transmission lines is essential for its application in complex power scenarios. Variations in vibration damper types, and unmanned aerial vehicle(UAV) shooting distances lead to domain shift, which impacts detection performance. This paper proposes a single domain generalization (SDG) detection method for vibration dampers that integrates structural knowledge to guide the model in extracting domaininvariant features (DIF), combining frequency domain attention (FDA) and scale-invariant learning (SIL). Different types of vibration dampers exhibit combinatory structural invariance, while dampers of varying scales demonstrate aspect ratio invariance. First, a learnable weight matrix is applied to the amplitude spectrum after Fourier transformation, preserving low-frequency information while attenuating high-frequency components. This approach retains structural features and reduces morphological differences. Next, SIL is introduced to emphasize aspect ratios during bounding box regression, improving the model's capacity to handle scale variations and enhancing feature generalization. Experimental results demonstrate that without significantly increasing the number of parameters and model size, the proposed method achieves AP50 of 60.8% and 77.1% in the two target domains, respectively, representing increases of 3.3% and 4.0% over the original model, thus offering strong support for the practical application of intelligent detection models. © 1986-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Small-Target Infrastructure Detection with Spatial Tracking and Multi-Level Feature Extraction of Railway Track Scenes

Small-Target Infrastructure Detection with Spatial Tracking ...

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2024 International Conference on intelligent Communication, Sensing and Electromagnetics, ICSE 2024

作者： Du, Heng Cang, Huaiming Bai, Yiwen Wang, Xinyi Beijing Elephant Technology Co. Ltd Beijing China School of Transportation Science and Engineering Beihang University Beijing102206 China State Key Lab of Intelligent Transportation System Beijing100191 China School of Mechanical Engineering Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechanical System Design and Intelligent Control Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9798350354935

In the field of railway transportation, with the continuous improvement of train running speed and the continuous increase of operating mileage, it becomes particularly important to ensure the safety and integrity of small-Target infrastructure along the railway train. Although many small-Target detection methods have been proposed, the research on small-Target infrastructure detection along rail trains is very rare. To solve this problem, this paper proposes a small-Target infrastructure detection network with spatial tracking and multi-level feature extraction based on Yolov8n. The experimental results show that ST-YOLO has a 3.6% mAP improvement on the OSDaR23 dataset compared to the baseline Yolov8n, and shows significant advantages over other state-of-The-Art methods. © 2024 IEEE.

关键词： Railroads

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