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Adaptive Space Expansion for Fast Motion Planning

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1499-1514页

作者： Shenglei Shi Jiankui Chen state key laboratory of digital manufacturing equipment and technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The sampling process is very inefficient for sam-pling-based motion planning algorithms that excess random sam-ples are generated in the planning *** this paper,we pro-pose an adaptive space expansion(ASE)approach which belongs to the informed sampling category to improve the sampling effi-ciency for quickly finding a feasible *** ASE method enlarges the search space gradually and restrains the sampling process in a sequence of small hyper-ellipsoid ring subsets to avoid exploring the unnecessary ***,for a con-structed small hyper-ellipsoid ring subset,if the algorithm cannot find a feasible path in it,then the subset is ***,the ASE method successively does space exploring and space expan-sion until the final path has been ***,we present a particular construction method of the hyper-ellipsoid ring that uniform random samples can be directly generated in *** last,we present a feasible motion planner BiASE and an asymptoti-cally optimal motion planner BiASE*using the bidirectional exploring method and the ASE *** demon-strate that the computation speed is much faster than that of the state-of-the-art *** source codes are available at https://***/shshlei/ompl.

关键词： Adaptive space expansion(ASE) hyper-ellipsoid ring informed sampling motion planning.

Full-Scale Isogeometric Topology Optimization of Cellular Structures Based on Kirchhoff-Love Shells

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2479-2505页

作者： Mingzhe Huang Mi Xiao Liang Gao Mian Zhou Wei Sha Jinhao Zhang state key lab of Intelligent manufacturing equipment and technology Huazhong University of Science and TechnologyWuhan430074China

Cellular thin-shell structures are widely applied in ultralightweight designs due to their high bearing capacity and strength-to-weight *** this paper,a full-scale isogeometric topology optimization(ITO)method based on Kirchhoff-Love shells for designing cellular tshin-shell structures with excellent damage tolerance ability is *** method utilizes high-order continuous nonuniform rational B-splines(NURBS)as basis functions for Kirchhoff-Love shell *** geometric and analysis models of thin shells are unified by isogeometric analysis(IGA)to avoid geometric approximation error and improve computational *** topological configurations of thin-shell structures are described by constructing the effective density field on the *** volume constraints are imposed in the proximity of each control point to obtain bone-like cellular *** facilitate numerical implementation,the p-norm function is used to aggregate local volume constraints into an equivalent global *** numerical examples are provided to demonstrate the effectiveness of the proposed *** simulation and comparative analysis,the results indicate that the cellular thin-shell structures optimized by the proposed method exhibit great load-carrying behavior and high damage robustness.

关键词： Cellular thin-shell structures isogeometric analysis full-scale topology optimization Kirchhoff–Love shells

A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

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Computers, Materials & Continua 2024年第4期79卷 1-18页

作者： Yan Dong Kang Zhao Liang Gao Hao Li The state key lab of digital manufacturing equipment and technology Huazhong University of Science and TechnologyWuhan430074China Institute of Systems Engineering China Academy of Engineering PhysicsMianyang621900China

With the continuous advancement in topology optimization and additive manufacturing(AM)technology,the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown ***,a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures,potentially resulting in diminished efficiency or macroscopic failure.A Hybrid Level Set Method(HLSM)is proposed,specifically designed to enhance connectivity among non-uniform microstructures,contributing to the design of functionally graded cellular *** HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure ***,an interpolation algorithm is presented to construct transition microstructures seamlessly connected on both ***,the algorithm enables the morphing of non-uniform unit cells to seamlessly adapt to interconnected adjacent *** method,seamlessly integrated into a multi-scale topology optimization framework using the level set method,exhibits its efficacy through numerical examples,showcasing its prowess in optimizing 2D and 3D functionally graded materials(FGM)and multi-scale topology *** essence,the pressing issue of interface connections in complex structure design is not only addressed but also a robust methodology is introduced,substantiated by numerical evidence,advancing optimization capabilities in the realm of functionally graded materials and cellular structures.

关键词： Hybrid level set method functionally graded cellular structure connectivity interpolated transition optimization design

Surface roughness classification using light scattering matrix and deep learning

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Science China(Technological Sciences) 2024年第2期67卷 520-535页

作者： SUN Hao TAN Wei RUAN YiXiao BAI Long XU JianFeng state key laboratory of Intelligent manufacturing equipment and technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China Wuhan digital Design and manufacturing Innovation Center Co. LtdWuhan 430074China

High-quality optical components have been widely used in various applications;thus,extremely high beam quality is ***,surface roughness is a key indicator of the surface *** this study,the angular distribution of light scattering field intensity was obtained for surfaces having different roughness profiles based on the finite difference time domain(FDTD)method,and the results were compared with those obtained using the generalized Harvey-Shack(GHS)*** was shown that the FDTD approach can be used for an accurate simulation of the scattered field of a rough surface,and the superposition of results obtained from many surfaces that have the same roughness level was in good agreement with the result given by the analytic GHS model.A light scattering matrix(LSM)method was proposed based on the FDTD simulation results that could obtain rich surface roughness *** classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning *** classification accuracy of the model trained with the LSM dataset was obtained as 95.74%,which was 23.40%higher than that trained using the SISD ***,the effects of different noise types and filtering methods on the classification performance were analyzed,and the LSM was also shown to improve the robustness and generalizability of the trained surface roughness ***,the proposed LSM method has important implications for improving the data acquisition scheme of current light scattering measurement systems,and it also has the potential to be used for detection and characterization of surface defects of optical components.

关键词： surface roughness FDTD simulation GHS theory deep learning light scattering matrix

VMMAO-YOLO:an ultra-lightweight and scale-aware detector for real-time defect detection of avionics thermistor wire solder joints

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Frontiers of Mechanical Engineering 2024年第3期19卷 77-92页

作者： Xiaoqi YANG Xingyue LIU Qian WU Guojun WEN Shuang MEI Guanglan LIAO Tielin SHI School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China state key laboratory of digital manufacturing equipment and technology Huazhong University of Science and TechnologyWuhan 430074China

The quality of the exposed avionics solder joints has a significant impact on the stable operation of the inorbit ***,the previously reported inspection methods for multi-scale solder joint defects generally suffer low accuracy and slow detection ***,a novel real-time detector VMMAO-YOLO is demonstrated based on variable multi-scale concurrency and multi-depth aggregation network(VMMANet)backbone and“one-stop”global information gather-distribute(OS-GD)*** with infrared thermography technology,it can achieve fast and high-precision detection of both internal and external solder joint ***,VMMANet is designed for efficient multi-scale feature extraction,which mainly comprises variable multi-scale feature concurrency(VMC)and multi-depth feature aggregation-alignment(MAA)*** can extract multi-scale features via multiple fix-sized and deformable convolutions,while MAA can aggregate and align multi-depth features on the same order for feature *** allows the low-level features with more spatial details to be transmitted in depth-wise,enabling the deeper network to selectively utilize the preceding inference *** VMMANet replaces inefficient highdensity deep convolution by increasing the width of intermediate feature levels,leading to a salient decline in *** OS-GD is developed for efficacious feature extraction,aggregation and distribution,further enhancing the global information gather and deployment capability of the *** a self-made solder joint image data set,the VMMAOYOLO achieves a mean average precision mAP@0.5 of 91.6%,surpassing all the mainstream YOLO-series ***,the VMMAO-YOLO has a body size of merely 19.3 MB and a detection speed up to 119 frame per second,far superior to the prevalent YOLO-series detectors.

关键词： defect detection of solder joints VMMAO-YOLO ultra-lightweight and high-performance multiscale feature extraction VMC and MAA modules OS-GD

The joint knowledge reasoning model based on knowledge representation learning for aviation assembly domain

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Science China(Technological Sciences) 2024年第1期67卷 143-156页

作者： LIU PeiFeng QIAN Lu LU Hu XUE Lei ZHAO XingWei TAO Bo state key laboratory of digital manufacturing equipment and technology Department of MechanicalHuazhong University of Science and TechnologyWuhan 430074China School of Transportation and Logistics Engineering Wuhan University of Technology(WHUT)Wuhan 430063China Shanghai Aircraft manufacturing Co. Ltd.Shanghai 201324China

Knowledge graph technology is widely applied in the domain of general knowledge reasoning with an excellent *** fine-grained professional fields,professional knowledge graphs can provide more accurate information in practical industrial *** on an aviation assembly domain-specific knowledge graph,the article constructs a joint knowledge reasoning model,which combines a named entity recognition model and a subgraph embedding learning *** performing knowledge reasoning tasks,the two models vectorize entities,relationships and entity attributes in the same space,so as to share parameters and optimize learning *** knowledge reasoning model,which provides intelligent question answering services,is able to reduce the assembly error rate and improve the assembly *** system can accurately solve general knowledge reasoning problems in the assembly process in actual industrial scenarios of general assembly and component assembly under interference-free ***,this paper compares the proposed knowledge reasoning model based on knowledge representation learning and the question-answering system based on large-scale pre-trained *** the application scenario of system functional testing in general assembly,the joint model attains an accuracy rate of 95%,outperforming GPT with 78%accuracy and enhanced representation through knowledge integration with 71%accuracy.

关键词： intelligent manufacturing knowledge graph aviation assembly knowledge representation knowledge-based question an-swering

Data-driven discovery of linear dynamical systems from noisy data

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Science China(Technological Sciences) 2024年第1期67卷 121-129页

作者： WANG YaSen YUAN Ye FANG HuaZhen DING Han School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China state key lab of digital manufacturing equipment and technology Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Department of Mechanical Engineering University of KansasLawrence 66045USA

In modern science and engineering disciplines,data-driven discovery methods play a fundamental role in system modeling,as data serve as the external representations of the intrinsic mechanisms within ***,empirical data contaminated by process and measurement noise remain a significant obstacle for this type of *** this study,we have developed a data-driven method capable of directly uncovering linear dynamical systems from noisy *** method combines the Kalman smoothing and sparse Bayesian learning to decouple process and measurement noise under the expectation-maximization framework,presenting an analytical method for alternate state estimation and system ***,the discovered model explicitly characterizes the probability distribution of process and measurement noise,as they are essential for filtering,smoothing,and stochastic *** have successfully applied the proposed algorithm to several simulation *** results demonstrate its potential to enable linear dynamical system discovery in practical applications where noise-free data are intractable to capture.

关键词： system identification sparse Bayesian learning Kalman smoothing process and measurement noise

Analysis of the Flow Field and Impact Force in High-Pressure Water Descaling

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Fluid Dynamics & Materials Processing 2024年第1期20卷 165-177页

作者： Yue Cui Liyuan Wang Jian Wu Haisheng Liu Di Wu key lab of Intelligent equipment digital Design and Process Simulation Hebei ProvinceTangshan UniversityTangshan063000China Department of Intelligent manufacturing Tangshan Vocational College of Science and TechnologyTangshan063001China

This study aims to improve the performances of the high-pressure water descaling technology used in steel hot rolling *** particular,a 2050 mm hot rolling line is considered,and the problem is investigated by means of a fluid–structure interaction(FSI)method by which the descaling effect produced by rolling coils with different section sizes is *** a flat fan-shaped nozzle at the entrance of the R1R2 roughing mill,the outflow field characteristics and the velocity distribution curve on the strike line(at a target distance of 30–120 mm)are *** is found that the velocity in the center region of the water jet with different target distances is higher than that in the boundary *** the target distance increases,the velocity of the water jet in the central region *** comparison with experimental results,it is shown that the simulation model can accurately predict the impact position of the high-pressure water on the impact plate,thereby providing a computational scheme that can be used to optimize the nozzle space layout and improve the slabs’descent effect for different rolling specifications.

关键词： High pressure water descaling flow field analysis FSI target distance strike range

基于改进离散-连续参数化的结构和连续材料方向协同拓扑优化方法

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Acta Mechanica Sinica 2024年第1期40卷 197-209页

作者：罗云锋刘书田仇政麻耀辉黄永安 state key laboratory of digital manufacturing equipment and technology Huazhong University of Science and technology Wuhan 430074 China state key laboratory of Structural Analysis for Industrial equipment Dalian University of TechnologyDalian 116024China

结构和材料方向的并行拓扑优化是过去几十年来的一个热门话题.然而,如何避免此类问题掉入局部最优相当具有挑战性。为了解决这个问题,我们在以前的工作中提出了一种将离散材料优化方法和连续纤维取向优化方法相结合的方法,称之为离散-... 详细信息

结构和材料方向的并行拓扑优化是过去几十年来的一个热门话题.然而,如何避免此类问题掉入局部最优相当具有挑战性。为了解决这个问题,我们在以前的工作中提出了一种将离散材料优化方法和连续纤维取向优化方法相结合的方法,称之为离散-连续参数化(DCP),该方法同时继承了离散方法的全局搜索能力和连续方法的全设计空间然而,DCP方法需要太多设计变量,导致了巨大的计算负担.因此,我们在本工作中提出了一种改进的DCP方法,以减少设计变量的数量,同时又不牺牲优化问题的凸性。在该方法中,我们提出了一种扩展的多材料插值方法,该方法能够大大减少设计变量的数量。然后,我们将所提出的插值方法集成到DCP方法中,最终建立了结构拓扑和纤维取向协同优化的改进DCP方法.几个基准优化实例表明,该方法可以在能大大降低陷入局部最优的风险的同时,使用更少的设计变量.

关键词：纤维取向设计变量协同优化插值方法 DCP 材料优化拓扑优化结构拓扑