基于雷达波的树木躯干内部缺陷探测识别
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摘要
【目的】采用探地雷达对木质体内部缺陷进行断层扫描探测,研究基于雷达波的树木内部层面反射特征识别算法,为雷达波无损测试技术在树木内部结构和缺陷的解析、定位及分布表征提供理论依据。【方法】采用900 MHz介质耦合树木雷达对柳木试件进行断层扫描,研究实现阈值法、匹配滤波器法和希尔伯特积算法获取缺陷层面的反射位置,基于层剥反演法对树木内部不同介质进行介电常数反演,求得层位的相对深度,结合三维激光扫描仪获取的树木外形轮廓点云数据,根据轮廓追踪法将雷达波B扫描图像与断层轮廓绝对位置进行映射,实现对树木内部缺陷的准确定位和表征。对3种算法分别使用FDTD正演方法进行对比验证,并应用于颐和园古柳木试件试验测试中。【结果】正演对比测试结果表明,希尔伯特积算法相较于阈值法和匹配滤波器法,对木质体内部缺陷识别效果更好。柳木试验测试结果显示,树木内部缺陷深度误差为10%,结合三维激光和外轮廓扫描技术求得的缺陷部分面积误差在5%左右。【结论】本研究提出的算法可以实现雷达波扫描图像对树木内部缺陷的准确定位和分布成像。
【Objective 】 In order to provide a theoretical basis for the analysis,localization and distribution characterization of internal structure and defects of the radar waves by non-destructive testing technique,tree radar tomography were applied to detect internal defects of wood body,and the recognition algorithm of internal reflection features of radar trees was studied and analyzed. 【Method】 Tomography of Willow wood was carried out with a 900 MHz medium-coupled tree radar. The threshold value,matched filter and Hilbert's algorithm were used to obtain the reflection position of the defect layer. Based on the layer stripping inversion method, the inversion of the dielectric constant were applied for the different media in the tree,and the relative depth of the horizon were calculated,then the point cloud data of the contour of the tree obtained by the 3 D laser scanner were mapped,and the absolute position of the B-scan radar image and the contour of the fault were mapped according to the contour tracing method. Therefore, the accurate positioning and characterization of the internal defects of trees were achieved. The three algorithms were respectively verified by finite difference-time-domain( FDTD) forward method,and the method is applied to the test of the ancient willow wood specimen in the Summer Palace. 【Result 】 The results of forward comparison test show that Hilbert plot method is better than threshold method and matched filter method in identifying defects in wood body. The actual willow test results show that the depth error of defects in trees is 10 %. The area error of defects calculated by 3 D laser and contour scanning technology is about 5 %.【Conclusion】 The method proposed in this paper can realize the accurate localization and imaging distribution of the internal defects of the trees by the radar wave scanning images.
【Objective 】 In order to provide a theoretical basis for the analysis,localization and distribution characterization of internal structure and defects of the radar waves by non-destructive testing technique,tree radar tomography were applied to detect internal defects of wood body,and the recognition algorithm of internal reflection features of radar trees was studied and analyzed. 【Method】 Tomography of Willow wood was carried out with a 900 MHz medium-coupled tree radar. The threshold value,matched filter and Hilbert's algorithm were used to obtain the reflection position of the defect layer. Based on the layer stripping inversion method, the inversion of the dielectric constant were applied for the different media in the tree,and the relative depth of the horizon were calculated,then the point cloud data of the contour of the tree obtained by the 3 D laser scanner were mapped,and the absolute position of the B-scan radar image and the contour of the fault were mapped according to the contour tracing method. Therefore, the accurate positioning and characterization of the internal defects of trees were achieved. The three algorithms were respectively verified by finite difference-time-domain( FDTD) forward method,and the method is applied to the test of the ancient willow wood specimen in the Summer Palace. 【Result 】 The results of forward comparison test show that Hilbert plot method is better than threshold method and matched filter method in identifying defects in wood body. The actual willow test results show that the depth error of defects in trees is 10 %. The area error of defects calculated by 3 D laser and contour scanning technology is about 5 %.【Conclusion】 The method proposed in this paper can realize the accurate localization and imaging distribution of the internal defects of the trees by the radar wave scanning images.
引文
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薛金林,张顺顺.2014.基于激光雷达的农业机器人导航控制研究.农业机械学报,45(9):55-60.(Xue J L,Zhang S S.2014.Navigation of an agricultural robot based on laser radar.Transactions of the Chinese Society for Agricultural Machiney,45(9):55-60.[in Chinese])
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Devaru D,Halabe U B,Gopalakrishnan B.2005.Algorithm for detecting defects in wooden logs using ground penetrating radar.Proc SPIE5999,Intelligent Systems in Design and Manufacturing VI,59990B,doi:10.1117/12.630835.
Halabe U B,Agrawal S,Gopalakrishnan B.2009.Nondestructive evaluation of wooden logs using ground penetrating radar.Nondestructive Testing&Evaluation,24(4):329-346.
Huang N E,Wu Z.2008.Review on Hilbert-Huang transform:method and its applications to geophysical studies.Reviews of Geophysics,46(2):RG2006.
Je6ováJ,Mertens L,Lambot S.2016.Ground-penetrating radar for observing tree trunks and other cylindrical objects.Construction&Building Materials,123:214-225.
Kim K H,Kim S J.2003.A wavelet-based method for action potential detection from extracellular neural signal recording with low signalto-noise ratio.IEEE Transactions on Biomedical Engineering,50(8):999-1011.
Lahouar S.2003.Development of data analysis algorithms for interpretation of ground penetrating radar data.Doctoral Dissertations,Virginia Polytechnic Institute and State University.
Lambot S,Slob E C,van den Bosch I,et al.2004.Modeling of groundpenetrating radar for accurate characterization of subsurface electric properties.IEEE Transactions on Geoscience and Remote Sensing,42(11):2555-2567.
Loizos A,Plati C.2007.Accuracy of pavement thicknesses estimation using different ground penetrating radar analysis approaches.Ndt&E International,40(2):147-157.
Lorenzo H,Pérez-Gracia V,Novo A,et al.2010.Forestry applications of ground-penetrating radar.Forest Systems,19(1):5-17.
Mucciardi A N.2002.Ground penetrating radar system for non-invasive inspection of trees for internal decay.US Patent,6.496.136.2002-12-17.
Perez-Gracia V,Santos-Assuncao S.2014.Study of wood beams in buildings with ground penetrating radar.Proceedings of the 15th International Conference on Ground Penetrating Radar,31-35.
Riggio M,Sandak J,Franke S.2015.Application of imaging techniques for detection of defects,damage and decay in timber structures onsite.Construction and Building Materials,101(part 2):1241-1252.
Solla M,González-Jorge H,Lorenzo H,et al.2013.Uncertainty evaluation of the 1 GHz GPR antenna for the estimation of concrete asphalt thickness.Measurement,46(9):3032-3040.
陈勇平,高甜,李德山,等.2017b.马尾松木材空洞开裂残损的雷达检测成像初探.北京林业大学学报,39(3):112-118.(Chen Y P,Gao T,Li D S,et al.2017b.Preliminary study on radar detection and imaging of cavities and cracks of Pinus massoniana.Journal of Beijing Forestry University,39(3):112-118.[in Chinese])
邸向辉,王立海.2013.探地雷达(GPR)在木材无损检测应用中的可行性探讨.无损检测,35(11):51-54.(Di X H,Wang L H.2013.Study on the feasibility about GPR applied on wood nondestructive testing.Nondestructive Testing,35(11):51-54.[in Chinese])
甘明旭,孙涛,康永祥,等.2016.应用探地雷达对黄帝陵古柏树干和粗根的研究.西北林学院学报,31(4):182-187.(Gan M X,Sun T,Kang Y X,et al.2016.Examination of the trunk cvity and thick root distribution of acient Platycladus orientalis in the tomb of yellow emperor by gound penetrating radar technology.Journal of Northwest Forestry University,31(4):182-187.[in Chinese])
岳小泉,王立海,刘泽旭,等.2016.不同含水率下利用电阻与应力波断层成像定量检测木材腐朽.福建农林大学学报:自然科学版,45(5):593-598.(Yue X Q,Wang L H,Liu Z X,et al.2016.Electrical resistance tomography and stress wave tomography to quantitatively detect wood decay under different moisture contents.Journal of Fujian Agriculture and Forestry University:Natural Science Edition,45(5):593-598.[in Chinese])
薛金林,张顺顺.2014.基于激光雷达的农业机器人导航控制研究.农业机械学报,45(9):55-60.(Xue J L,Zhang S S.2014.Navigation of an agricultural robot based on laser radar.Transactions of the Chinese Society for Agricultural Machiney,45(9):55-60.[in Chinese])
Baili J,Lahouar S,Hergli M,et al.2009.GPR signal de-noising by discrete wavelet transform.Ndt&E International,42(8):696-703.
Butnor J R,Pruyn M L,Shaw D C,et al.2009.Detecting defects in conifers with ground penetrating radar:applications and challenges.Forest Pathology,39(5):309-322.
Devaru D,Halabe U B,Gopalakrishnan B.2005.Algorithm for detecting defects in wooden logs using ground penetrating radar.Proc SPIE5999,Intelligent Systems in Design and Manufacturing VI,59990B,doi:10.1117/12.630835.
Halabe U B,Agrawal S,Gopalakrishnan B.2009.Nondestructive evaluation of wooden logs using ground penetrating radar.Nondestructive Testing&Evaluation,24(4):329-346.
Huang N E,Wu Z.2008.Review on Hilbert-Huang transform:method and its applications to geophysical studies.Reviews of Geophysics,46(2):RG2006.
Je6ováJ,Mertens L,Lambot S.2016.Ground-penetrating radar for observing tree trunks and other cylindrical objects.Construction&Building Materials,123:214-225.
Kim K H,Kim S J.2003.A wavelet-based method for action potential detection from extracellular neural signal recording with low signalto-noise ratio.IEEE Transactions on Biomedical Engineering,50(8):999-1011.
Lahouar S.2003.Development of data analysis algorithms for interpretation of ground penetrating radar data.Doctoral Dissertations,Virginia Polytechnic Institute and State University.
Lambot S,Slob E C,van den Bosch I,et al.2004.Modeling of groundpenetrating radar for accurate characterization of subsurface electric properties.IEEE Transactions on Geoscience and Remote Sensing,42(11):2555-2567.
Loizos A,Plati C.2007.Accuracy of pavement thicknesses estimation using different ground penetrating radar analysis approaches.Ndt&E International,40(2):147-157.
Lorenzo H,Pérez-Gracia V,Novo A,et al.2010.Forestry applications of ground-penetrating radar.Forest Systems,19(1):5-17.
Mucciardi A N.2002.Ground penetrating radar system for non-invasive inspection of trees for internal decay.US Patent,6.496.136.2002-12-17.
Perez-Gracia V,Santos-Assuncao S.2014.Study of wood beams in buildings with ground penetrating radar.Proceedings of the 15th International Conference on Ground Penetrating Radar,31-35.
Riggio M,Sandak J,Franke S.2015.Application of imaging techniques for detection of defects,damage and decay in timber structures onsite.Construction and Building Materials,101(part 2):1241-1252.
Solla M,González-Jorge H,Lorenzo H,et al.2013.Uncertainty evaluation of the 1 GHz GPR antenna for the estimation of concrete asphalt thickness.Measurement,46(9):3032-3040.