Central catadioptric cameras are widely used in virtual reality and robot navigation,and the camera calibration is a prerequisite for these applications.In this paper,we propose an easy calibration method for central ...Central catadioptric cameras are widely used in virtual reality and robot navigation,and the camera calibration is a prerequisite for these applications.In this paper,we propose an easy calibration method for central catadioptric cameras with a 2D calibration pattern.Firstly,the bounding ellipse of the catadioptric image and field of view(FOV)are used to obtain the initial estimation of the intrinsic parameters.Then,the explicit relationship between the central catadioptric and the pinhole model is used to initialize the extrinsic parameters.Finally,the intrinsic and extrinsic parameters are refined by nonlinear optimization.The proposed method does not need any fitting of partial visible conic,and the projected images of 2D calibration pattern can easily cover the whole image,so our method is easy and robust.Experiments with simulated data as well as real images show the satisfactory performance of our proposed calibration method.展开更多
2D patterned hollow structures have emerged as advanced materials with exceptional mechanical properties and lightweight characteristics,making them ideal for high-performance applications in aerospace and automotive ...2D patterned hollow structures have emerged as advanced materials with exceptional mechanical properties and lightweight characteristics,making them ideal for high-performance applications in aerospace and automotive industries.However,optimizing their structural design to achieve uniform stress distribution and minimize stress concentration remains a significant challenge due to the complex interplay between geometric patterns and mechanical performance.In this study,we develop an integrated framework combining conditional generative adversarial networks(cGANs)and deep Q-networks(DQNs)to predict and optimize the stress fields of 2D-PHS.We generated a comprehensive dataet comprising 1000 samples across five distinct density classes using a custom grid pattern generation algorithm,ensuring a wide range of structural variations.The cGAN accurately predicts stress distributions,achieving a high correlation with finite element analysis(FEA)results while reducing computational time from approximately 40 s(FEA)to just 1-2 s per prediction.Concurrently,the DQN optimizes design parameters through scaling and rotation operations,enhancing structural performance based on predicted stress metrics.Our approach resulted in a 4.3%improvement in average stress uniformity and a 23.1%reduction in maximum stress concentration.These improvements were validated through FEA simulations and experimental tensile tests on 3D-printed thermoplastic polyurethane samples.The tensile strength of the optimized samples increased from an initial average of 5.9-6.6 MPa under 100%strain,demonstrating enhanced mechanical resilience.This study demonstrates the efficacy of combining advanced AI techniques for rapid and precise material design optimization,providing a scalable and cost-effective solution for developing superior lightweight materials with tailored mechanical properties for critical engineering applications.展开更多
Electronic speckle pattern interferometry（ESPI） and digital speckle pattern interferometry are wellestablished non-contact measurement methods. They have been widely used to carry out precise deformation mapping. Ho...Electronic speckle pattern interferometry（ESPI） and digital speckle pattern interferometry are wellestablished non-contact measurement methods. They have been widely used to carry out precise deformation mapping. However, the simultaneous two-dimensional（2D） or three-dimensional（3D） deformation measurements using ESPI with phase shifting usually involve complicated and slow equipment. In this Letter, we solve these issues by proposing a modified ESPI system based on double phase modulations with only one laser and one camera. In-plane normal and shear strains are obtained with good quality. This system can also be developed to measure 3D deformation, and it has the potential to carry out faster measurements with a highspeed camera.展开更多
Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential applicatio...Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential application of distributed fibre optical sensing(DFOS)based on optical frequency domain reflectometry(OFDR)technology in characterizing the twodimensional(2D)desiccation cracking processes of surface soils,a comprehensive test device is utilized to conduct soil evaporation tests,continuously record water content changes,desiccation cracking evolution,and FO sensing strain status.A deep learning-based quantitative analysis method is employed to meticulously examine the relationship between 2D cracking geometric parameters and strain status.The comprehensive analysis not only reveals the mutual feedback response mechanism between the strain status and the soil evaporation-shrinkage-cracking processes,but also clarifies the early detection distance of OFDR technology for 2D desiccation cracking.Specifically,OFDR technology can detect the propagation of horizontal desiccation cracks up to 23 mm in advance with a strain measurement accuracy of 1με.To address the spatial continuity issue in OFDR sensing strain data,an innovative high-resolution characterization framework is proposed by combining the finite element method(FEM)and OFDR technology,referred to as the FEM-OFDR framework.Comparative results indicate that the proposed FEM significantly surpasses both the kriging and radial basis function(RBF)methods in inferring missing OFDR sensing strain data.Notably,during the drying process,reaching a critical water content causes the local decoupling between the uncracked clods and the substrate,resulting in a decreasing trend in the sensing strain at the crack position.This study provides crucial technical means and theoretical support for a deeper understanding of the mechanisms driving 2D desiccation-induced shrinkage and cracking in surface soils.展开更多
基金Supported by National Natural Science Foundation of China(60575019)the National High Technology Research and Development Program of China(863 Program)(2006AA01Zl16)Institute of Automation Chinese Academy of Sciences Innovation Fund For Young Scientists
文摘Central catadioptric cameras are widely used in virtual reality and robot navigation,and the camera calibration is a prerequisite for these applications.In this paper,we propose an easy calibration method for central catadioptric cameras with a 2D calibration pattern.Firstly,the bounding ellipse of the catadioptric image and field of view(FOV)are used to obtain the initial estimation of the intrinsic parameters.Then,the explicit relationship between the central catadioptric and the pinhole model is used to initialize the extrinsic parameters.Finally,the intrinsic and extrinsic parameters are refined by nonlinear optimization.The proposed method does not need any fitting of partial visible conic,and the projected images of 2D calibration pattern can easily cover the whole image,so our method is easy and robust.Experiments with simulated data as well as real images show the satisfactory performance of our proposed calibration method.
基金supported by the National Natural Science Foundation of China(Grant Nos.52322305 and 52473098)the starting Grant of ShanghaiTech University,the Double First-Class Initiative Fund of ShanghaiTech University and the Shanghai Clinical Research and Trial Center.Materials were tested at the Analytical Instrumentation Center(Grant No.SPST-AIC10112914)the Center for High-resolution Electron Microscopy(C-hEM),SPST,ShanghaiTech University.
文摘2D patterned hollow structures have emerged as advanced materials with exceptional mechanical properties and lightweight characteristics,making them ideal for high-performance applications in aerospace and automotive industries.However,optimizing their structural design to achieve uniform stress distribution and minimize stress concentration remains a significant challenge due to the complex interplay between geometric patterns and mechanical performance.In this study,we develop an integrated framework combining conditional generative adversarial networks(cGANs)and deep Q-networks(DQNs)to predict and optimize the stress fields of 2D-PHS.We generated a comprehensive dataet comprising 1000 samples across five distinct density classes using a custom grid pattern generation algorithm,ensuring a wide range of structural variations.The cGAN accurately predicts stress distributions,achieving a high correlation with finite element analysis(FEA)results while reducing computational time from approximately 40 s(FEA)to just 1-2 s per prediction.Concurrently,the DQN optimizes design parameters through scaling and rotation operations,enhancing structural performance based on predicted stress metrics.Our approach resulted in a 4.3%improvement in average stress uniformity and a 23.1%reduction in maximum stress concentration.These improvements were validated through FEA simulations and experimental tensile tests on 3D-printed thermoplastic polyurethane samples.The tensile strength of the optimized samples increased from an initial average of 5.9-6.6 MPa under 100%strain,demonstrating enhanced mechanical resilience.This study demonstrates the efficacy of combining advanced AI techniques for rapid and precise material design optimization,providing a scalable and cost-effective solution for developing superior lightweight materials with tailored mechanical properties for critical engineering applications.
基金financially supported by the ANR Micromorfing Program(ANR-14-CE07-0035)China Scholarship Council(CSC)the Labex Action
文摘Electronic speckle pattern interferometry（ESPI） and digital speckle pattern interferometry are wellestablished non-contact measurement methods. They have been widely used to carry out precise deformation mapping. However, the simultaneous two-dimensional（2D） or three-dimensional（3D） deformation measurements using ESPI with phase shifting usually involve complicated and slow equipment. In this Letter, we solve these issues by proposing a modified ESPI system based on double phase modulations with only one laser and one camera. In-plane normal and shear strains are obtained with good quality. This system can also be developed to measure 3D deformation, and it has the potential to carry out faster measurements with a highspeed camera.
基金supported by the National Natural Science Foundation of China(Grant Nos.41925012,42230710,42172290)the Natural Science Foundation of Jiangsu Province(Grant No.BK20211087)+2 种基金the Key Laboratory Cooperation Special Project of Western Cross Team of Western Light,CAS(Grant No.xbzg-zdsys-202107)the China Scholarship Council(Grant No.202206190069)the Fundamental Research Funds for the Central Universities。
文摘Drought-induced desiccation cracking can trigger several weakening mechanisms in surface soils,potentially precipitating instability and failure of slopes and earthen structures.To investigate the potential application of distributed fibre optical sensing(DFOS)based on optical frequency domain reflectometry(OFDR)technology in characterizing the twodimensional(2D)desiccation cracking processes of surface soils,a comprehensive test device is utilized to conduct soil evaporation tests,continuously record water content changes,desiccation cracking evolution,and FO sensing strain status.A deep learning-based quantitative analysis method is employed to meticulously examine the relationship between 2D cracking geometric parameters and strain status.The comprehensive analysis not only reveals the mutual feedback response mechanism between the strain status and the soil evaporation-shrinkage-cracking processes,but also clarifies the early detection distance of OFDR technology for 2D desiccation cracking.Specifically,OFDR technology can detect the propagation of horizontal desiccation cracks up to 23 mm in advance with a strain measurement accuracy of 1με.To address the spatial continuity issue in OFDR sensing strain data,an innovative high-resolution characterization framework is proposed by combining the finite element method(FEM)and OFDR technology,referred to as the FEM-OFDR framework.Comparative results indicate that the proposed FEM significantly surpasses both the kriging and radial basis function(RBF)methods in inferring missing OFDR sensing strain data.Notably,during the drying process,reaching a critical water content causes the local decoupling between the uncracked clods and the substrate,resulting in a decreasing trend in the sensing strain at the crack position.This study provides crucial technical means and theoretical support for a deeper understanding of the mechanisms driving 2D desiccation-induced shrinkage and cracking in surface soils.
