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Pixelated non-volatile programmable photonic integrated circuits with 20-level intermediate states

International Journal of Extreme Manufacturing 2024年第3期6卷 477-487页

作者： Wenyu Chen Shiyuan Liu Jinlong Zhu State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074People’s Republic of China Optics Valley Laboratory WuhanHubei 430074People’s Republic of China

Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum *** this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm *** flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing *** believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.

关键词： programmable photonic integrated circuits phase change materials multi-level intermediate states metasurfaces

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WeldNet:A voxel-based deep learning network for point cloud annular weld seam detection

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Science China(Technological Sciences) 2024年第4期67卷 1215-1225页

作者： WANG Hui RONG YouMin XU JiaJun XIANG SongMing PENG YiFan HUANG Yu State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China

Weld seam detection is an important part of automated *** present,few studies have been conducted on annular weld seams,and a lot of defects exist in the point cloud model of the tube sheet obtained by RGB-D cameras and photography *** at the above problems,this paper proposed an annular weld seam detection network named WeldNet where a voxel feature encoding layer was adaptively improved for annular weld seams,the sparse convolutional network and region proposal network(RPN)were used to detect annular weld seam position,and an annular weld seam detection loss function was ***,an annular weld seam dataset was established to train the *** with the random sampling consistency(RANSAC)method,WeldNet has a higher detection accuracy,as well as a higher detection success rate which has increased by 23%.Compared with U-Net,WeldNet has been proven to achieve a better detection result,and the intersection over the union of the weld seam detection is improved by 17.8%.

关键词： deep learning point cloud weld seam detection welding annular weld seam

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Sparse convolutional model with semantic expression for waste electrical appliances recognition

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Science China(Technological Sciences) 2024年第9期67卷 2881-2893页

作者： HAN HongGui LIU YiMing LI FangYu DU YongPing Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing 100124China Engineering Research Center of Digital Community Ministry of EducationBeijing 100124China Beijing Artificial Intelligence Institute and Beijing Laboratory for Intelligent Environmental Protection Beijing 100124China

Deep neural networks play an important role in the recognition of waste electrical appliances. However, deep neural network components still lack reliability in decision-making features. To address this problem, a sparse convolutional model with semantic expression(SCMSE) is proposed. First, a low-rank sparse semantic expression component, combining the benefits of residual networks and sparse representation, is adapted to enhance sparse feature extraction and semantic expression. Second, a reliable network architecture is obtained by iterating the optimal sparse solution, enhancing semantic expression. Finally, the results of visualization experiments on the waste electrical appliances dataset demonstrate that the proposed SCMSE can obtain excellent semantic performance.

关键词： sparse convolutional model deep neural network semantic expression visualization computer vision

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Transient Synchronous Stability Analysis and Assessment of PLL-Based VSC systems by Bifurcation Theory

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IEEE Transactions on Energy Conversion 2024年第2期40卷 1312-1324页

作者： Han, Miao Ma, Rui Zhan, Meng Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic Engineering Wuhan430074 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Jinan250061 China

For the transient synchronous stability of phase-locked loop based voltage source converter grid-tied systems, the generalized swing equation (GSE) is believed as very important. In this paper, the GSE is studied deeply by bifurcation theory. For instance, the co-dimension-2 Bogdanov-Takens (BT) bifurcation is rigorously analyzed, and the formulations for three co-dimension-1 bifurcations near the BT bifurcation point including the generalized saddle-node, Hopf, and homoclinic bifurcations are explicitly obtained. Moreover, all Hopf bifurcations in the GSE have been theoretically proven to be subcritical by the normal form method. Therefore, after the Hopf and homoclinic bifurcations, two different types of basin of attraction occur widely including a closed loop surrounded by an unstable limit cycle and a fish- like pattern surrounded by the stable manifold of unstable equilibrium point (UEP), respectively. In addition, for the transient synchronous stability assessment after the homoclinic bifurcation, based on the linear approximation of the stable manifold of the UEP, an index for the distance between the stable equilibrium point and the approximated stability boundary is formulated. All these theoretical results are well verified and supported by numerical calculations and real-time simulations, making all previous phenomenal observations of the GSE stand on the solid foundation of rigorous mathematics. © 1986-2012 IEEE.

关键词： Phase locked loops

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Penalty Function-Based Distributed Primal-Dual Algorithm for Nonconvex Optimization Problem

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 394-402页

作者： Xiasheng Shi Changyin Sun IEEE the Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University the School of Artificial Intelligence Anhui University Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Anhui University the Anhui Key Laboratory Industrial Energy-Saving and Safety Anhui University

This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the p-power transformation and penalty function techniques are introduced to reframe the nonconvex optimization problem. This ensures that the Hessian matrix of the augmented Lagrangian function becomes local positive definite by choosing appropriate control parameters. A multi-timescale primal-dual method is then devised based on the Karush-Kuhn-Tucker(KKT) point of the reformulated nonconvex problem to attain convergence. The Lyapunov theory guarantees the model's stability in the presence of an undirected and connected communication network. Finally, two nonconvex optimization problems are presented to demonstrate the efficacy of the previously developed method.

关键词： Constrained optimization Karush-Kuhn-Tucker (KKT) point nonconvex p-power transformation

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Fine-Grained Emotion Prediction for Movie and Television scene images

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The Journal of China Universities of Posts and Telecommunications 2024年第3期31卷 43-55页

作者： Su Zhibin Zhou Xuanye Liu Bing Ren Hui State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing 100024China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

For the task of content retrieval,analysis and generation of film and television scene images in the field of intelligent editing,fine-grained emotion recognition and prediction of images is of great *** this paper,the fusion of traditional perceptual features,art features and multi-channel deep learning features are used to reflect the emotion expression of different levels of the *** addition,the integrated learning model with stacking architecture based on linear regression coefficient and sentiment correlations,which is called the LS-stacking model,is proposed according to the factor association between multi-dimensional *** experimental results prove that the mixed feature and LS-stacking model can predict well on the 16 emotion categories of the self-built image *** study improves the fine-grained recognition ability of image emotion by computers,which helps to increase the intelligence and automation degree of visual retrieval and post-production system.

关键词： fine-grained emotion prediction movie and television scene images stacking model linear regression

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A Climbing Robot for Tube-sheet Inspection Based on Planar Parallel Mechanisms

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IEEE Robotics and Automation Letters 2025年第7期10卷 6752-6759页

作者： Zhang, Kuan Fan, Jizhuang Xu, Tian Zhang, Xuehe Lin, Jinghan Yu, Xuan Zhao, Jie Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

This paper introduces a novel climbing robot for tube-sheet inspection (CRTI) that uses inner wall grippers (IWGs) to grasp tubes, enabling it to hang and crawl beneath the tube-sheet plane. The robot is designed primarily for inspecting steam generators in nuclear power plants. The CRTI based on a planar parallel mechanism is proposed, with its workspace optimized through the solution space method to address the limitations of existing systems in adaptability, load capacity, and efficiency. A modular IWG based on a wedge mechanism is introduced, featuring a load capacity exceeding 100 kg without damaging tubes, with its configuration optimized through a geometric method to enable insertion into smaller apertures. Furthermore, a forward kinematic solution method for parallel robots based on coordinate transformation is proposed, providing a unique analytical solution for the forward kinematics of all parallel configurations of this CRTI. The performance evaluation, which is grounded in singularity analysis and typical experiments, reveals that the proposed CRTI offers high efficiency, substantial load capacity, and exceptional adaptability, indicating its significant potential for future applications. © 2016 IEEE.

关键词： Grippers

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Gradient-based attitude planning for rigid spacecraft on SO(3)

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Science China Technological Sciences 2025年第5期68卷 167-178页

作者： Tao HUO Jin YANG Chengfei YUE Xueqin CHEN Xibin CAO School of Astronautics Harbin Institute of Technology School of Management Harbin Institute of Technology State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster Harbin Institute of Technology School of Aerospace Science Harbin Institute of Technology Shenzhen

Attitude planning of rigid bodies has many applications in robotics and aerospace. However, because the attitude configuration space is non-Euclidean and the constraints are complex and non-linear, the design of the attitude curve has always been a tricky problem. In this paper, a gradient-based attitude planning method is proposed to simultaneously handle attitude pointing, angular velocity, torque, and time constraints on Lie group SO(3). Firstly, the attitude interpolation algorithm on SO(3) gives an attitude curve connecting the initial and target attitudes. The shape of the curve is determined by the fitting coefficients and maneuvering time. Secondly, to match the curve with suitable angular velocity and control torque, a nonlinear planning model with fitting coefficients and maneuver time as decision variables is proposed. Solving the problem gives a smooth attitude curve that satisfies both kinematic and dynamic constraints and also avoids complicated time allocation. Then, to apply the gradientbased solver, analytical formulas for the derivatives of each order of the attitude curve with respect to the decision variables are given in this paper. Finally, the effectiveness of the proposed algorithm is verified by a series of numerical simulations.

关键词： attitude planning attitude constraints gradient optimization three-dimensional special orthogonal group (SO(3))

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Rethinking Mutual Information for Language Conditioned Skill Discovery on Imitation Learning 34

Rethinking Mutual Information for Language Conditioned Skill...

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34th International Conference on Automated Planning and Scheduling, ICAPS 2024

作者： Ju, Zhaoxun Yang, Chao Sun, Fuchun Wang, Hongbo Qiao, Yu Academy for Engineering and Technology Fudan University China Shanghai Artificial Intelligence Laboratory China State Key Laboratory of Intelligent Technology and System Tsinghua University China

ISBN: (纸本)9781577358893

Language-conditioned robot behavior plays a vital role in executing complex tasks by associating human commands or instructions with perception and actions. The ability to compose long-horizon tasks based on unconstrained language instructions necessitates the acquisition of a diverse set of general-purpose skills. However, acquiring inherent primitive skills in a coupled and long-horizon environment without external rewards or human supervision presents significant challenges. In this paper, we evaluate the relationship between skills and language instructions from a mathematical perspective, employing two forms of mutual information within the framework of language-conditioned policy learning. To maximize the mutual information between language and skills in an unsupervised manner, we propose an end-to-end imitation learning approach known as Language Conditioned Skill Discovery (LCSD). Specifically, we utilize vector quantization to learn discrete latent skills and leverage skill sequences of trajectories to reconstruct high-level semantic instructions. Through extensive experiments on language-conditioned robotic navigation and manipulation tasks, encompassing BabyAI, LORel, and CALVIN, we demonstrate the superiority of our method over prior works. Our approach exhibits enhanced generalization capabilities towards unseen tasks, improved skill interpretability, and notably higher rates of task completion success. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Semantics

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Knowledge and data jointly driven aeroengine gas path performance assessment method

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Chinese Journal of Aeronautics 2024年第5期37卷 533-557页

作者： Zhe WANG Xuyun FU Rui ZHANG Zhengfeng BAI Xiangzhao XIA Wei JIANG Department of Mechanical Engineering Harbin Institute of TechnologyWeihai 264209China Weihai Key Laboratory of Intelligent Operation and Maintenance Harbin Institute of TechnologyWeihai 264209China Control System Design Laboratory AECC ShenYang Engine Research InstituteShenyang 110015China

Aeroengines,as the sole power source for aircraft,play a vital role in ensuring flight *** gas path,which represents the fundamental pathway for airflow within an aeroengine,directly impacts the aeroengine's performance,fuel efficiency,and ***,timely and accurate evaluation of gas path performance is of paramount *** paper proposes a knowledge and data jointly driven aeroengine gas path performance assessment method,combining Fingerprint and gas path parameter deviation ***,Fingerprint is used to correct gas path parameter deviation values,eliminating parameter shifts caused by non-component performance ***,coarse errors are removed using the Romanovsky criterion for short-term data divided by an equal-length overlapping sliding ***,an Ensemble Empirical Mode Decomposition and Non-Local Means(EEMD-NLM)filtering method is designed to“clean”data noise,completing the preprocessing for gas path parameter deviation ***,based on the characteristics of gas path parameter deviation values,a Dynamic Temporary Blended Network(DTBN)model is built to extract its temporal features,cascaded with Multi-Layer Perceptron(MLP),and combined with Fingerprint to construct a Dynamic Temporary Blended AutoEncoder(DTB-AutoEncoder).Eventually,by training this improved autoencoder,the aeroengine gas path multi-component performance assessment model is formed,which can sufficiently decouple the nonlinear mapping relationship between aeroengine gas path multi-component performance degradation and gas path parameter deviation values,thereby achieving the performance assessment of engine gas path *** practical application cases,the effectiveness of this model in assessing the aeroengine gas path multi-component performance is verified.

关键词： Performance assessment Aeroengine Fingerprint Gas path parameter deviation values Jointly drive

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