Novel boundary element method for resolving plate bending problems

This paper discusses the application of the boundary contour method fo r resolving plate bending problems. The exploitation of the integrand divergence free property of the plate bending boundary integral equation based on the Kirc hhoff hypothesis and a very useful application of Stokes' Theorem are presented to convert surface integrals on boundary elements to the computation of bending potential functions on the discretized boundary points,even for curved surface elements of arbitrary shape. Singularity and treatment of the discontinued corne r point are not needed at all. The evaluation of the physics variant at internal points is also shown in this article. Numerical results are presented for some plate bending problems and compared against analytical and previous solutions.

Research on Containment Relationships between Rapid Prototyping Part and CAD Model

Aiming at the geometrical features of different containment relationships in Rapid Prototyping （RP）, a general method of achieving the RP layer＇s cusp distribution of the positive, negative and mixed tolerance is proposed to meet the part＇s different applications. The procedure is executed by projecting the current and the next section of the CAD model onto a horizontal plane, computing the union and the intersection of the sections to get the outer and the inner boundary, and then blending the boundaries using a rotary vector through a proper inner point in the intersection to achieve the current layer＇s scanning contour. The method can realize the layer＇s cusp distribution of the mixed tolerance with unequal cusp height, expanding the connotation of the mixed tolerance.

Detection of the farmland plow areas using RGB-D images with an improved YOLOv5 model

Recognition of the boundaries of farmland plow areas has an important guiding role in the operation of intelligent agricultural equipment.To precisely recognize these boundaries,a detection method for unmanned tractor plow areas based on RGB-Depth(RGB-D)cameras was proposed,and the feasibility of the detection method was analyzed.This method applied advanced computer vision technology to the field of agricultural automation.Adopting and improving the YOLOv5-seg object segmentation algorithm,first,the Convolutional Block Attention Module(CBAM)was integrated into Concentrated-Comprehensive Convolution Block(C3)to form C3CBAM,thereby enhancing the ability of the network to extract features from plow areas.The GhostConv module was also utilized to reduce parameter and computational complexity.Second,using the depth image information provided by the RGB-D camera combined with the results recognized by the YOLOv5-seg model,the mask image was processed to extract contour boundaries,align the contours with the depth map,and obtain the boundary distance information of the plowed area.Last,based on farmland information,the calculated average boundary distance was corrected,further improving the accuracy of the distance measurements.The experiment results showed that the YOLOv5-seg object segmentation algorithm achieved a recognition accuracy of 99%for plowed areas and that the ranging accuracy improved with decreasing detection distance.The ranging error at 5.5 m was approximately 0.056 m,and the average detection time per frame is 29 ms,which can meet the real-time operational requirements.The results of this study can provide precise guarantees for the autonomous operation of unmanned plowing units.

Optimization of Triangulations Based on Serial Fault Data

Three-dimensional reconstructions based on serial fault data can be divided into boundary contour splicing and end contour closure. In boundary contour splicing, the Delaunay triangulation algorithm can generate long, narrow triangles or radial shapes and with end contour closure, the Delaunay triangulation based on the determination of the convex-concave vertices tends to generate long, narrow triangles and triangles whose sizes differ greatly, and in some cases failure. This paper presents a Delaunay triangulation algorithm based on the shortest distance first principle for boundary contour splicing and an improved algorithm which combines Delaunay triangulation based on the determination of convex-concave vertices with interpolation for end contour closure. The results show that the algorithms retain the original advantages of the algorithms while increasing the triangulation effectiveness and enhancing the universality of the algorithms.