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6th International Conference on Intelligent Robotics and control engineering, IRCE 2023

作者： Zhang, Mingyi Huang, Peng Wang, Yawu School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

ISBN: (纸本)9798350326338

Dielectric elastomer sensor (DES) is a flexible sensor that can perform free bending deformation, thus it has broad application prospects in the fields of medical electronics, wearable devices, soft robots, etc. Previous studies have mostly focused on exploring the static sensing characteristics of the DES. Considering that the DES may be used in dynamic conditions, it is very meaningful to study its dynamic sensing characteristics to broaden its application ranges. In this paper, a dynamic sensing model of the DES is established based on the gate recurrent unit (GRU) neural network. Firstly, the structure of the DES and the construction of the experimental system are introduced. In addition, the dynamic sensing characteristics of the DES are analyzed by conducting several sets of experiments, which shows that the DES has significant rate-dependent hysteresis nonlinearities, multivalued mapping and memory characteristics. After that, the dynamic sensing model of the DES is built based on the GRU neural network to describe the above dynamic sensing characteristics. Next, the dynamic displacement and force sensing models of the DES are trained according to the dynamic displacement-capacitance and dynamic force-capacitance experimental data, respectively. Finally, several experiments are performed to verify the effectiveness and generalization ability of the established dynamic sensing model. © 2023 IEEE.

关键词： Capacitance

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Phenomenological Modeling and End-Point Trajectory Tracking control of a Flexible Beam with Pneumatic Soft Actuators 6

Phenomenological Modeling and End-Point Trajectory Tracking ...

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6th International Conference on Intelligent Robotics and control engineering, IRCE 2023

作者： Sun, Xuefeng Meng, Qingxin Wu, Jundong Zhu, Mingliang School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China

ISBN: (纸本)9798350326338

As the basic construction of flexible mechanical systems, the flexible beam and its control problem have attracted widespread attention in recent years. This paper takes a flexible beam with pneumatic soft actuators (FBPSA) as the research object and studies its phenomenological modeling and end-point trajectory tracking control strategy. Firstly, we develop an experimental platform for the FBPSA and perform tests on it, gathering its input and output data. Using these collected data, we analyzed the motion characteristics of the FBPSA. Subsequently, a phenomenological model is established to describe the motion characteristics of the system, and the parameters of this model are identified through a large amount of the collected experimental data. Then, a combined feedforward-feedback control strategy is proposed to achieve the end-point trajectory tracking control of the system. Finally, three sets of experiments are carried out to verify the accuracy of the established model and the effectiveness and superiority of the control strategy. © 2023 IEEE.

关键词： Trajectories

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Bearing Fault Diagnosis Under Variable Working Conditions Based on Domain Adaptation and Improved Depthwise Separable Convolution Network 26

Bearing Fault Diagnosis Under Variable Working Conditions Ba...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Kuang, Zehui Mao, Fan Zhao, Xingyu Wan, Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Domain adaptation methods and appropriate feature extractors are usually applied to solve the problem that the variable working conditions of bearings affect the effectiveness of the fault diagnostic framework. However, the existing feature extractors are too complex to be deployed in real industries. In this paper, we propose a lightweight framework called improved depthwise separable convolution network (IDSCN) for the diagnosis of bearing faults in variable operating conditions. IDSCN is built on wavelet convolution and depthwise separable residual convolution (DSRC), where the wavelet convolution is used to extract frequency features from the source and target domains, and DSRC guarantees the performance of feature extraction with reduced parameters and computation. To minimise the distribution difference between the source and target domains, the local maximum mean difference is incorporated into the proposed framework. The performance of the proposed framework is validated on the Paderborn University dataset, involving a total of 6 transfer tasks. The experiment shows that the proposed framework achieves satisfactory results and outperforms other frameworks in bearing fault diagnosis. © 2025 IEEE.

关键词： Bearing fault diagnosis Depthwise separable residual convolution Domain adaptation Wavelet convolution

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Remote Sensing Image Classification Based on Lightweight Network and Pruning

Remote Sensing Image Classification Based on Lightweight Net...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Zexi Xue, Wei Chen, Kehui Ma, Shaopeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

In recent years, deep neural network has continuously improved the performance of remote sensing image classification. Though The deep neural network model is powerful, it is difficult to deploy on resource-constrained hardware platforms such as mobile terminal devices and embedded devices due to the large number of network parameters. In this paper, a novel lightweight network (LW-Net) model and a network pruning method are used for remote sensing image classification. This LW-Net model adopts a net block unit to obtain more characteristic graphs with less computational complexity. The proposed network pruning method uses the sparsity regularization on the influence factor in BN layer to automatically identified and pruned unimportant channels to make the model structure simpler. Experimental results demonstrate compared with traditional deep neural networks, the proposed model with the network pruning method can greatly reduce the computational complexity and model parameters with a little accuracy loss. © 2022 IEEE.

关键词： Deep neural networks

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Optimal Scheduling Strategy of Limited Electricity Based on Energy Sharing of Multi-microgrid

Optimal Scheduling Strategy of Limited Electricity Based on ...

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2022 Chinese Automation Congress, CAC 2022

作者： Zeng, Zihan Li, Danyun Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (纸本)9781665465335

In the environment of limited electricity supply in distribution network, due to the limitation of its own power capacity and the uncertainty of new energy output, there will be insufficient electricity supply in microgrid, which will affect the economy and comfort of users in microgrid system. Therefore, aiming at the situation of limited electricity supply in distribution network, multi-microgrid system is taken as the research object, and the cooperative game method is adopted to realize the energy sharing of multi-microgrid system, and then the limited electricity optimal dispatching model of multi-microgrid system is constructed to realize the reasonable power distribution for different types of loads. Finally, the simulation results show that this strategy can effectively realize power sharing, reduce outage loss and improve user satisfaction. © 2022 IEEE.

关键词： Electric power distribution

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Aerodynamic and aeroacoustic impact of the axial distance upon contra-rotating rotors during hovering condition

Aerodynamic and aeroacoustic impact of the axial distance up...

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AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023

作者： Li, Pengyu Yang, Yannian Zhang, Haoyu Liu, Yu Li, Qingxi Noack, Prof. Bernd Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South Guangdong510640 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong Shenzhen518055 China AVIC General Aircraft Research Institute Zhuhai Shenzhen Key Laboratory of Complex Aerospace Flows Guangdong519040 China School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Shenzhen518055 China

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

Contra-rotating rotors have the advantage of compactness and redundancy, which can be observed in many unmanned aerial vehicles. One significant installation parameter for the contra-rotating rotors is the axial distance between the upper and lower rotors, which influences both the time-averaged and unsteady loading of the rotors, as well as the aeroacoustic noise emission. Through experimental methods, each rotor is mounted to a six-component balance to study the impact of the axial distance on the two rotors, and an microphone arc-array is used to study the noise emission and directivity in an anechoic chamber. Two rotors are set at the same rotational speed for all axial distance settings. The results indicate that the increase of axial distance is advantageous for the aerodynamic performance increase and noise reduction, especially in the axial range of 0.1 diameter. The recovery of aerodynamic performance is due to the fully developed slipstream which reduces the mutual influence between the two rotors. The noise reduction is mainly due to the reduced velocity fluctuation alleviates the inter actiontonal noise, although the broadband noise becomes larger as the axial distance increases. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Noise abatement

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Pinr: A Physics-Integrated Neural Representation for Dynamic Fluid Scenes

SSRN

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SSRN 2024年

作者： Zhao, Ziyu Zhou, Sifan Lu, Xiaobo Zeng, Weili Qian, Jian School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of ASIC and System Fudan University Shanghai China

Recent research based on neural representation has achieved impressive results in dynamic reconstruction. However, reconstructing high-fidelity dynamic fluid scenes from multi-view videos remains challenging due to the complex fluid phenomena such as translucency, scattering, occlusion, and visual ambiguity. In this paper, we present a novel neural representation that simultaneously exploits physics knowledge and differentiable volume rendering techniques to construct a physically plausible neural field. We first propose a simple yet effective state field to separate fluid and non-fluid contents apart, which essentially reduces the amount of computation and appearance ambiguity. To achieve robust optimization and fast convergence, we introduce intermediate velocity in neural representation based on Helmholtz Decomposition to decouple physical quantities (velocity, pressure and density) that are tightly coupled in physical equations. In contrast to previous physics-informed reconstruction methods, we explore a novel solution by introducing a fast and stable fluid solver to update the intermediate velocity to a physically conserved incompressible velocity. This solver is based on a parallelizable multi-scale architecture, which can effectively avoid degenerate solutions. By adopting the proposed physics-aware loss, we achieved better convergence and superior performance in dynamic fluid scenes. Extensive experiments show that the proposed method can achieve state-of-the-art results for reconstructing dynamic fluid scenes, and the performance and efficiency have been significantly improved in different scenarios. © 2024, The Authors. All rights reserved.

关键词： Computer vision

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Optimizing Bounding Box Regression in complex Backgrounds

Optimizing Bounding Box Regression in Complex Backgrounds

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2024 China Automation Congress, CAC 2024

作者： Chen, Jun Zhang, Haiyan Yu, Anjun Wang, Yiwei School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Jiangxi Ganyue Expressway Co.Ltd. Nanchang China School of Automation China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798350368604

In the context of electrical power operation sites, the automated and accurate detection of whether workers are properly equipped with safety gear, such as safety clothing, helmets, and safety ropes for high-altitude operations, is crucial for ensuring the safety of personnel. Traditional object detection models often struggle to accurately identify these critical pieces of safety equipment in complex environments, due to variable object sizes, overlapping objects, and substantial background noise. To specifically address these challenges, we propose a novel loss function-Enhanced Alignment Intersection over Union (EAIoU) loss. This loss function is designed to enhance the model’s ability to discriminate between closely spaced and overlapping safety gear in real-time, significantly improving robustness against scale variations and complex backgrounds. In experiments based on the YOLOv8s architecture, our model achieved a mean Average Precision (mAP) of 92.1% on a dataset specific to electrical power operations, markedly outperforming traditional IoU loss functions. Additionally, EAIoU demonstrated improved performance on the COCO dataset, indicating its generalization capability across various complex scenarios. This research not only enhances the accuracy and real-time performance of safety equipment detection at electric power operation sites but also opens new avenues for advanced object detection technology in complex, multi-object environments. © 2024 IEEE.

关键词： Safety devices

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Design of a High Speed 360-degree Panoramic Video Acquisition System Based on FPGA and USB 3.0

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IEEE Sensors Journal 2023年 1-1页

作者： Lyu, Congyi Peng, Jianqing Zhou, Weiguo Yang, Shanshan Liu, Yunhui Intelligent Robotics Institute Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Mechatronical Engineering Beijing Institute of Technology Beijing China

This paper presents a FPGA-based hardware architecture for capturing real-time panoramic images and the parallel implementation of an image stitching algorithm based on the scale-invariant feature transform (SIFT) features. First, the system transfers the images captured by five CMOS sensors to the designed FPGA board through the FMC adapter plate. Then, the system employs the FPGA-based parallel computing to extract the SIFT features and detect the best matching region and points for image registration. Finally, in order to obtain the panoramic image with smooth changes at the junctions, images of the adjacent images are fused. Using the designed FPGA platform makes it possible to extract the SIFT and stitch the images in real-time, which is not realized in most panoramic imaging systems. The panoramic system, developed using the Xilinx Zynq®-7000 all programmable SOC, can capture video of 5*640*480 images at the speed of 60 fps. To enable high-speed image transfer from the imaging system to the host computer, the USB3.0 interface with the transmission speed of 359MB/s has been developed. The real-time efficiency of the parallel system will be demonstrated by the simulations and experiments. IEEE

关键词： Real time systems

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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