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Simultaneous Strain and Temperature measurement Based on Chaotic Brillouin Optical Correlation-Domain Analysis in Large-Effective-Area Fibers

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Photonic Sensors 2021年第4期11卷 377-386页

作者： Xiaocheng ZHANG Shuangshuang LIU Jianzhong ZHANG Lijun QIAO Tao WANG Shaohua GAO Mingjiang ZHANG Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China College of Physics and Optoelectronics Institute of Optoelectronic EngineeringTaiyuan University of TechnologyTaiyuan 030024China

Chaotic Brillouin optical correlation domain analysis(BOCDA)has been proposed and experimentally demonstrated with the advantage of high spatial ***,it faces the same issue of the temperature and strain *** this paper,the simultaneous measurement of temperature and strain can be preliminarily achieved by analyzing the two Brillouin frequencies of the chaotic laser in a large-effective-area fiber(LEAF).A temperature resolution of 1℃ and a strain resolution of 20μξ can be obtained with a spatial resolution of *** actual temperature and strain measurement errors are 0.37℃ and 10μξ,respectively,which are within the maximum measurement errors.

关键词： Brillouin scattering simultaneous strain and temperature measurement chaotic laser BOCDA LEAF

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The relationship between orthopedic clinical imaging and bone strength prediction

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Medicine in Novel Technology and Devices 2021年第1期9卷 9-17页

作者： He Gong Meng Zhang Shaowei Jia Linwei Lv Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education Beijing Advanced Innovation Center for Biomedical EngineeringSchool of Biological Science and Medical EngineeringBeihang UniversityBeijingChina Department of Engineering Mechanics Nanling CampusJilin UniversityChangchun130025China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin300384China

Pathologic fracture is caused by bone diseases,which is common in middle-aged and elderly *** bone strength is the leading contributor to this type of ***,accurately quantifying bone strength could help clinicians assess individualized fracture risk and develop therapeutic *** clinical imaging including dual X-ray absorptiometry(DXA),computed tomography(CT),and magnetic resonance imaging(MRI)has been an important tool to obtain radiology images of bone,which could be further used for noninvasive assessment of bone strength and related fracture *** the development of biomechanics and computer technology,the combination of finite element analysis with orthopedic imaging is the most advanced method for noninvasive prediction of bone strength in *** this review,an overview is provided for the commonly noninvasive methods based on the radiology images(i.e.,DXA,CT,and MRI)to predict bone strength,which may improve the understanding of the relationship between orthopedic clinical imaging and biomechanics.

关键词： Orthopedic clinical imaging Biomechanics Bone strength Finite element analysis

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Real-time Semantic Segmentation of Solar Photovoltaic Arrays for Autonomous UAV Flights 43

Real-time Semantic Segmentation of Solar Photovoltaic Arrays...

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43rd Chinese control Conference, CCC 2024

作者： Li, Nanyan Chen, Hao Sun, Zhigang Gao, Jing Yi, Dewei Liu, Cunjia Su, Jinya Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Cse Ministry of Education Nanjing210096 China State Grid Jiangsu Integrated Energy Service CO. Ltd Nanjing210096 China Jiangsu Sudian Industry Management CO. Ltd Nanjing210096 China University of Aberdeen Department of Computing Science AberdeenAB24 3UE United Kingdom Loughborough University Department of Aeronautical and Automotive Engineering LoughboroughLE11 3TU United Kingdom

ISBN: (纸本)9789887581581

This paper considers the real-time semantic segmentation of solar PhotoVoltaic (PV) arrays using down-facing cameras onboard Unmanned Aerial Vehicles (UAVs) to support autonomous navigation for ultra-low altitude industrial inspection. Various semantic segmentation algorithms, including SegNet, UNet, Deeplabv3+, and their respective variants, are compared to identify the most suitable one that strikes a balance between segmentation and real-time performance. Subsequently, each video frame is processed by the selected segmentation network to create a solar array mask. This mask is then optimally fitted to diverse solar array shapes to determine angular and horizontal deviations between the image center and the solar array center-line. The algorithms are validated on a self-constructed dataset of 594 solar PV array UAV images, encompassing varied environmental conditions and solar farm layouts. The top-performing network, lightweight vgg 16bn-Unet, achieves 99.4% overall accuracy and 98.2% Intersection over Union (IoU), while the most balanced network, mobilev3-Deeplabv3+, attains 98.9% accuracy and 96.5% IoU, with a 27.59 fps (using an NVIDIA GeForce MX150 GPU) suitable for real-time UAV flights. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Semantic Segmentation

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Interdependence between individual and social learning shapes cooperation with asymmetric exploration

arXiv

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arXiv 2025年

作者： Hou, Zhihao She, Zhikun Liang, Quanyi Su, Qi Li, Daqing School of Mathematical Sciences Beihang University Beijing100191 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Reliability and Systems Engineering Beihang University Beijing100083 China

Cooperation on social networks is crucial for understanding human survival and development. Although network structure has been found to significantly influence cooperation, some human experiments indicate that it cannot fully explain the evolutionary patterns of cooperation. While evidence suggests that this gap arises from human exploration, our understanding of its impact mechanisms and characteristics, such as asymmetry, remains limited. Here, we seek to formalize human exploration as an individual learning process involving trial and reflection, and integrate social learning to examine how their interdependence shapes cooperation. We find that individual learning can alter the imitative tendency of social learning, while its cooperative tendency in turn relies on social learning and players' decision preferences. By analyzing a series of key experiments, we show that the above coupled dynamics can explain human behavior in game interactions. Furthermore, we find that individual learning can promote cooperation when its probability is negatively correlated with payoffs, a mechanism rooted in the psychological tendency to avoid trial-and-error when individuals are satisfied with their current payoffs. These results link long-unexplained asymmetric exploration with the cooperation-promoting ability of social networks, helping to bridge the gap between theoretical research and reality. © 2025, CC BY.

关键词： Human engineering

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Speech Emotion Recognition Based on Syllable-Level Feature Extraction

SSRN

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SSRN 2023年

作者： Rehman, Abdul Liu, Zhen-Tao Wu, Min Cao, Wei-Hua Jiang, Cheng-Shan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

Speech emotion recognition systems have high computational requirements for deep learning models and low generalizability mainly because of the poor reliability of emotional measurements across multiple corpora. To solve these problems, we present a speech emotion recognition system based on a reductionist approach of decomposing and analyzing syllable-level ***-spectrogram of an audio stream is decomposed into syllable-level components, which are then analyzed to extract statistical features. The proposed method uses formant attention, noise-gate filtering, and rolling normalization contexts to decrease contextual differences and increase focus the attention on the structure of a formant. A set of syllable-level formant features is extracted and fed into a single hidden layer neural network that makes predictions for each syllable as opposed to the conventional approach of using a sophisticated deep learner to make sentence-wide *** syllable level predictions help to lower the aggregated error in utterance level cross-corpus predictions. The experiments on IEMOCAP (IE), MSP-Improv (MI), and RAVDESS (RA) databases show that the method archives better than the state-of-the-art cross-corpus unweighted accuracy of 47.6% for IE to MI and 56.2% for MI to IE. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Perceptual Quality Evaluation of Corrupted Industrial Images 18th

Perceptual Quality Evaluation of Corrupted Industrial Images

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18th International Forum of Digital Multimedia Communication, IFTC 2021

作者： Gong, Yafei Peng, Chenchen Liu, Jing Zhou, Chengxu Liu, Hongyan Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China Faculty of Science Beijing University of Technology Beijing China

ISBN: (纸本)9789811922657

In recent years, computer vision applied in industrial application scenarios has been attracting attention. A lot of work has been made to present approaches based on visual perception, ensuring the safety during the processes of industrial production. However, much less effort has been done to assess the perceptual quality of corrupted industrial images. In this paper, we construct an Industrial Scene Image Database (ISID), which contains 3000 distorted images generated through applying different levels of distortion types to each of the 50 source images. Then, the subjective experiment is carried out to gather the subjective scores in a well-controlled laboratory environment. Finally, we perform comparison experiments on ISID database to investigate the performance of some objective image quality assessment algorithms. The experimental results show that the state-of-the-art image quality assessment methods have difficulty in predicting the quality of images that contain multiple distortion types. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Database systems

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

Phenomenological Modeling and End-Point Trajectory Tracking ...

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IEEE International Conference of Intelligent Robotic and control engineering (IRCE)

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

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.

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Precise LiDAR SLAM in Structured Scene Using Finite Plane and Prior Constraint

Precise LiDAR SLAM in Structured Scene Using Finite Plane an...

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IEEE International Conference on Robotics and Biomimetics

作者： Yuhui Xie Wentao Zhao Jiahao Wang Jingchuan Wang Weidong Chen Key Laboratory of System Control and Information Processing Ministry of Education Institute of Medical Robotics and Department of Automation Shanghai Jiao Tong University Shanghai China Ministry of Education School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665481106

In this paper, we propose a precise LiDAR SLAM in optimization framework using plane-like object as landmark. Compared to general methods, finite plane feature is used to represent landmark and a new residual model is designed, making constraint from edge of landmark can be used to limit the parallel position between LiDAR and landmark, leading to a more accurate result. Moreover, floor plan is used to provide global pose for reduction of drift, and additionally feature orientation prior is used to prevent map distortion when updating the inaccurate part of floor plan. Experiments are conducted using data collected in real environment. The result qualitatively shows that proposed method can build a corrected map from floor plan without distortion, and quantitatively verifies that proposed method can outperform other baseline methods in accuracy.

关键词： Laser radar Simultaneous localization and mapping Image analysis Biomimetics Distortion Floors Robots

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OLMNE+FT: Multiplex network embedding based on overlapping links

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Physica A: Statistical Mechanics and its Applications 2022年 596卷 127116-127116页

作者： Liang, Bo Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronic Engineering and Automation Shanghai University Shanghai China

Network embedding or graph representation learning has recently attracted more researchers’ attention and achieved state-of-the-art performance in many areas and tasks. Nevertheless, most of these methods are targeted for monolayer networks and ignore the multiplexity property of nodes which refers to the multifaceted relationships between two elements. Multiplexity provides multiple types of auxiliary information to refine the characteristics of nodes and can be modeled as a multiplex network. In this study, we propose a multiplex network embedding algorithm to learn a unique embedding for each node in each layer or each relation type. A biased path-dependency random walk strategy is adopted to generate node sequences for integrating different types of relations between nodes, which pays more attention to overlapping links and makes neighbor nodes in the sampling sequence more similar to each other. Then the skip-gram model is used to learn an overall embedding over node sequences. To strengthen the expressive power of the embedding in a specific layer, a fine tuning strategy with low time cost is employed to make the embedding comprise information of nodes at this particular layer and preserve their distinctive properties, and the unique embedding is achieved ultimately. To verify the effectiveness of our algorithms, we validate the performance of our algorithm and other baseline methods in the link prediction task. The results demonstrate that the learned embedding can capture the interlayer relationships and preserve the specific characteristics of nodes, and our algorithms can stably obtain better or comparable performance compared with other methods. © 2022 Elsevier B.V.

关键词： Network embeddings

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Dynamic Sensing Modeling of Dielectric Elastomer Sensors Based on GRU Neural Network

Dynamic Sensing Modeling of Dielectric Elastomer Sensors Bas...

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IEEE International Conference of Intelligent Robotic and control engineering (IRCE)

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

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.

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