To simulate the bending behavior of wheat straw,a flexible straw model was developed based on the Hertz-Mindlin with bonding model using discrete element method.The proposed model was constructed by bonding straw unit...To simulate the bending behavior of wheat straw,a flexible straw model was developed based on the Hertz-Mindlin with bonding model using discrete element method.The proposed model was constructed by bonding straw units(filled by multi-spherical method)through parallel bonding keys.By means of a three-point bending test,single-factor sensitivity analysis and calibration of bonding parameters were performed.Results showed that elastic modulus of the flexible straw enhanced with the increase of bonded disk radius,normal stiffness per unit area and shear stiffness per unit area.The three bonding parameters were respectively calibrated to be 2.11 mm,9.48×10^(9)N/m^(3)and 4.67×10^(9)N/m^(3) by solving the regression equation developed from Box-Behnken design.The simulated elastic modulus(in terms of those three calibrated parameters)exhibited 4.20%difference with the measured one.It proved that the flexible straw could accurately demonstrate bending property of the wheat straw.This would not only help to improve accuracy in simulating wheat straw,but also provide references for flexible straw modeling and parameters calibration of other crops.展开更多
For the process of point cloud registration,and the problem of inaccurate registration due to errors in correspondence between keypoints.In this paper,a registration method based on calibration balls was proposed,the ...For the process of point cloud registration,and the problem of inaccurate registration due to errors in correspondence between keypoints.In this paper,a registration method based on calibration balls was proposed,the trunk,branch,and crown were selected as experimental objects,and three calibration balls were randomly placed around the experimental objects to ensure different distances between two ball centers.Using the Kinect V2 depth camera to collect the point cloud of the experimental scene from four different viewpoints,the PassThrough filter algorithm was used for point cloud filtering in each view of the experimental scenes.The Euclidean cluster extraction algorithm was employed for point cloud clustering and segmentation to extract the experimental object and the calibration ball.The random sample consensus(RANSAC)algorithm was applied to fit the point cloud of a ball and calculate the coordinates of the ball center so that the distance between two ball centers under different viewpoints can be obtained by using the coordinates of the ball center.Comparing the distance between the ball centers from different viewpoints to determine the corresponding relationship between the ball centers from different viewpoints,and then using the singular value decomposition(SVD)method,the initial registration matrix was obtained.Finally,Iterative Closest Point(ICP)and its improved algorithm were used for accurate registration.The experimental results showed that the method of point cloud registration based on calibration balls can solve the problem of corresponding error of keypoints,and can register point clouds from different viewpoints of the same object.The registration method was evaluated by using the registration running time and the fitness score.The final registration running time of different experimental objects was not more than 6.5 s.The minimum fitness score of the trunk was approximately 0.0001,the minimum fitness score of the branch was approximately 0.0001,and the minimum fitness score of the crown was 展开更多
基金This research was financially supported by Research Fund for the Doctoral Program of Higher Education of China(Grant No.20130204110020).
文摘To simulate the bending behavior of wheat straw,a flexible straw model was developed based on the Hertz-Mindlin with bonding model using discrete element method.The proposed model was constructed by bonding straw units(filled by multi-spherical method)through parallel bonding keys.By means of a three-point bending test,single-factor sensitivity analysis and calibration of bonding parameters were performed.Results showed that elastic modulus of the flexible straw enhanced with the increase of bonded disk radius,normal stiffness per unit area and shear stiffness per unit area.The three bonding parameters were respectively calibrated to be 2.11 mm,9.48×10^(9)N/m^(3)and 4.67×10^(9)N/m^(3) by solving the regression equation developed from Box-Behnken design.The simulated elastic modulus(in terms of those three calibrated parameters)exhibited 4.20%difference with the measured one.It proved that the flexible straw could accurately demonstrate bending property of the wheat straw.This would not only help to improve accuracy in simulating wheat straw,but also provide references for flexible straw modeling and parameters calibration of other crops.
基金This research was funded by the National Key R&D Program of China(Grant No.2018YFD0700601)and the National Natural Science Foundation of China(Grant No.31600588).
文摘For the process of point cloud registration,and the problem of inaccurate registration due to errors in correspondence between keypoints.In this paper,a registration method based on calibration balls was proposed,the trunk,branch,and crown were selected as experimental objects,and three calibration balls were randomly placed around the experimental objects to ensure different distances between two ball centers.Using the Kinect V2 depth camera to collect the point cloud of the experimental scene from four different viewpoints,the PassThrough filter algorithm was used for point cloud filtering in each view of the experimental scenes.The Euclidean cluster extraction algorithm was employed for point cloud clustering and segmentation to extract the experimental object and the calibration ball.The random sample consensus(RANSAC)algorithm was applied to fit the point cloud of a ball and calculate the coordinates of the ball center so that the distance between two ball centers under different viewpoints can be obtained by using the coordinates of the ball center.Comparing the distance between the ball centers from different viewpoints to determine the corresponding relationship between the ball centers from different viewpoints,and then using the singular value decomposition(SVD)method,the initial registration matrix was obtained.Finally,Iterative Closest Point(ICP)and its improved algorithm were used for accurate registration.The experimental results showed that the method of point cloud registration based on calibration balls can solve the problem of corresponding error of keypoints,and can register point clouds from different viewpoints of the same object.The registration method was evaluated by using the registration running time and the fitness score.The final registration running time of different experimental objects was not more than 6.5 s.The minimum fitness score of the trunk was approximately 0.0001,the minimum fitness score of the branch was approximately 0.0001,and the minimum fitness score of the crown was
