文献类型：期刊文献

中文题名：基于雷达检测的木材内部孔洞面积测算与修正

英文题名：Calculation and correction of wood internal cavity area based on radar detection

作者：陈勇平[1] 郭文静[1] 唐启恒[1]

第一作者：陈勇平

机构：[1]中国林业科学研究院木材工业研究所,北京100091

年份：2020

卷号：37

期号：6

起止页码：1193-1199

中文期刊名：浙江农林大学学报

外文期刊名：Journal of Zhejiang A & F University

收录：CSTPCD;;北大核心:【北大核心2017】；CSCD:【CSCD2019_2020】；

基金：中央级公益性科研院所基本科研业务费专项资金(CAFYBB2019ZB008)。

语种：中文

中文关键词：木材学;古建筑木结构;孔洞;雷达;定量评估;介电常数

外文关键词：wood science;ancient building timber structure;cavity;radar;quantitative evaluation;dielectric constant

分类号：S781.1

摘要：【目的】开展木材内部孔洞的雷达检测研究,探讨该检测手段下孔洞成像的准度和精度,实现木材内部孔洞的雷达快速识别和定量表征。【方法】以古建筑木结构常用的马尾松Pinus massoniana木材和杉木Cunninghamia lanceolata木材为研究对象,采取人工模拟的方法在木段端部制作异型孔洞,并利用雷达扫描仪对带孔木段进行检测,比较分析直观成像技术与希尔伯特积算法、单路径数据提取合成以及成像轮廓多参数校正等处理方法之间的差异,提出基于雷达检测的木材内部孔洞面积测算与可行的修正方法。【结果】利用雷达无损检测技术可以对马尾松和杉木木材内部孔洞的存在进行快速识别,但其直观成像技术在定量评估方面误差较大,需进行相关的数据处理和修正;未经修正的雷达图像其预估孔洞面积小于实际孔洞面积,通过希尔伯特积算法演算或介电常数修正的雷达图像其预估孔洞面积与实际孔洞面积仍存在一定的误差;木材边缘与孔洞边缘的距离应按s3c=(sr-a)k1k2进行修正,即实际应用中根据树种和含水率所得到的介电常数仅为多参数校正中的一个因素;无论是否进行数据处理和修正,雷达检测难以准确识别孔洞的具体形状,应开展进一步研究。【结论】该雷达检测及修正方法应用于木材内部孔洞探测,综合树种和含水率数值,可确保孔洞面积识别误差小于30%。
[Objective] The objective of this study is to realize the rapid recognition and quantitative characterization of the internal cavities in wood by evaluating the accuracy and precision of the cavity imaging under radar detection method. [Method] Pinus massoniana and Cunninghamia lanceolata, commonly used in ancient building timber structure, were taken as the research object. Artificial simulation was used to make special-shaped cavities at the end of the logs to simulate the internal damages, and then the radar scanner was used to detect the cavities. The differences between the visual imaging technology and the processing methods such as the Hilbert integral method, single path data extraction and synthesis, and the multi-parameter correction of the image contour were compared and analyzed. The calculation and feasible correction method of wood internal cavity area based on radar detection was proposed. [Result] The internal cavity of P. massoniana and C. lanceolata wood could be recognized rapidly by the radar nondestructive testing technology, but the visual imaging technology had a large error in quantitative evaluation, which required further relevant data processing and correction. The estimated cavity area of the unmodified radar image was smaller than that of the actual one.There was still a certain error between the actual cavity area and the estimated cavity area of the radar image calculated by Hilbert integral method or modified by dielectric constant. The distance between the wood edge and the cavity edge should be corrected according to the formula s3 c=(sr-a)k1 k2, that was to say, the dielectric constant obtained by tree species and moisture content in practical application was only one factor in the multiparameter correction. Therefore, it was difficult for radar scanner to accurately recognize the specific shape of the cavity, regardless of data processing and correction, and further research should be carried out.[Conclusion] The radar detection and correction technology can be applied to the detection of cavities in wood and the error of cavity area identification can be less than 30% by integrating tree species and moisture content values.