Abstract

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.

摘要

活木生长特性的三维建模是一个难题。在树木生长特性无损检测数据中，如何处理树木生长缺陷图像以及如何重建树木生长三维模型是关键技术，因此利用雷达信号检测反馈树干内部生长，采用3D光栅扫描逆向图像处理技术对立材3D形状数据进行逆向重构，实现木材的雷达波无损检测，3D扫描光栅面多拼接方式为补充是有效的解决方案。本研究对树木内部缺陷雷达波检测反馈数据和树木根系生长状况反馈数据进行了分析，从而完成树木无形内部生长状况的数字化数据采集。本研究采用3D光栅方法扫描木材标本进行逆曲面拟合建模，然后在扫描的点云数据上拼接多点标记重建树木标本的曲面模型，多曲面分组拟合方法被用来成功地减少拼接错误。实验结果是通过放养躯干内部缺陷检测信息得到，统计数据后分析检测信息为图表，3D扫描逆向重建实验结果是得到放养复杂3D数据的外部形式信息，通过该技术的应用，雷达波无损检测技术的有效性是通过3D扫描光栅逆向重建技术在树木生长数据采样方法中的应用获得的，该方法可以对木材腐烂的空洞病理监测，树木外表面可以三维特征进行表面重建。这个结论是射线检测技术和模式识别技术在木材生长监测领域的应用。