Experimental study on the complementary inverse reconstruction of tree growth state data by radar detection and 3D raster scan

Le résumé fourni par la source

Three-dimensional modeling of the growth characteristics of living wood is a difficult problem. In tree growth characteristics of nondestructive testing of data, how to process the image of tree growth defect and how to reconstruct the three-dimensional model of tree growth is the key technology, so the use of radar signal detection feedback internal growth of the trunk, using 3D raster scan reverse image processing techniques reverse reconstruct the 3D shape data of standing timber, realize the radar wave nondestructive test of lumber and 3D scanning and grating surface more stitching way as complementary is the effective solution. In this study, the feedback data of radar wave detection of internal defects of trees and the feedback data of root growth condition of trees were analyzed, so as to complete the digital data collection of invisible internal growth condition of trees. In this study, 3D grating method was used to scan wood specimens for inverse surface fitting modeling, and then the surface model of tree specimens was reconstructed by splicing multi-point markers on the scanned point cloud data, and the multi-surface grouping fitting method was used to successfully reduce the splicing error. Experimental results are obtained by stocking the trunk of the growth of internal defects inspection information, analyzes the testing information after statistical data for the chart, the experimental results of 3D scanning the reverse reconstruction is to obtain the stocking complex 3D data in the form of external information, through the application of this technology, the effective of the radar wave nondestructive testing technology is obtained with 3D scanning grating reverse reconstruction technology application in tree growth data sampling method, this method can empty of wood rotting pathological monitoring, trees outside surface can be three-dimensional characteristics of surface reconstruction. This conclusion is the application of ray detection technology and pattern recognition technology in the field of wood growth monitoring.

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