Local feature description of point clouds is essential in 3D computer vision. However, many local feature descriptors for point clouds struggle with inadequate robustness, excessive dimensionality, and poor computational efficiency. To address these issues, we propose a novel descriptor based on Planar Projection Contours, characterized by convex packet contour information.
View Article and Find Full Text PDFComposite materials are frequently exposed to external factors during their operational service, resulting in internal structural damage which subsequently impacts their structural performance. This paper employs ferromagnetic materials for their sensitivity to magnetic field strength. By detecting variations in the magnetic field within the embedded ferromagnetic microwires of composite materials, the aim is to indirectly assess the health status of the composite materials.
View Article and Find Full Text PDFThin-walled structures (TWS) were widely used in engineering equipment, and may be subjected to impact loads to produce different degrees of structural damage during application. However, it is a difficult problem to determine the impact load conditions for these structural damages. In this study, we developed a novel method of identifying the impact load condition of the thin-walled structure damage, which is based on particle swarm optimization-backpropagation (PSO-BP) neural network.
View Article and Find Full Text PDFFixed beam structures are widely used in engineering, and a common problem is determining the load conditions of these structures resulting from impact loads. In this study, a method for accurately identifying the location and magnitude of the load causing plastic deformation of a fixed beam using a backpropagation artificial neural network (BP-ANN). First, a load of known location and magnitude is applied to the finite element model of a fixed beam to create plastic deformation, and a polynomial expression is used to fit the resulting deformed shape.
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