基于计算机断层扫描技术的木材节子检测算法研究

编号 lyqk004806

中文标题 基于计算机断层扫描技术的木材节子检测算法研究

作者 赵德达  杨淑敏  刘杏娥  于伸  田根林  马建锋  王卿平 

作者单位 国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102;东北林业大学材料科学与工程学院,哈尔滨 150040;国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102;国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102;东北林业大学材料科学与工程学院,哈尔滨 150040;国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102;国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102;国际竹藤中心生物质材料研究中心,竹藤科学与技术重点实验室,北京 100102

期刊名称 世界林业研究 

年份 2015 

卷号 28

期号 5

栏目编号 1

栏目名称 专题论述 

中文摘要 介绍了目前国内外通过计算机断层扫描技术(CT)结合各种算法对木材中节子部分进行无损检测所取得的研究进展,概述了以灰度阈值法、滤波算法、最大似然法和神经网络法为主的算法识别特点,并对其中应用广泛的神经网络算法进行了对比分析。现有研究表明,运用该技术结合多种算法可实现对原木中节子参数特征的提取与分析,通过算法的不断改进能够提高节子检测的准确率。文中还总结了CT技术在处理节子检测方面存在的主要问题,并对未来趋势进行了展望。

关键词 木材节子  计算机断层扫描技术  无损检测  算法研究 

基金项目 国际竹藤中心基本科研业务费专项(1632010002);国家林业公益性行业科研专项(201304513)

英文标题 Computed Tomography(CT) Technology Application in Knot Algorithm Study

作者英文名 Zhao Deda,Yang Shumin,Liu Xing'e,Yu Shen,Tian Genlin,Ma Jianfeng and Wang Qingping

单位英文名 International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China;Materials Science and Engineering College,Northeast Forestry University,Harbin 150040,China;International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China;International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China;Materials Science and Engineering College,Northeast Forestry University,Harbin 150040,China;International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China;International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China;International Center for Bamboo and Rattan,Key Laboralory of Bamboo and Rattan Science and Technology,Beijing 100102,China

英文摘要 The paper introduced the domestic and international research progress on non-destructive testing of wood knot by computed tomography technology combined with various algorithms, described algorithm's identifying characteristics in gray threshold method, filtering algorithm, maximum likelihood method and neural network algorithm, and comparatively analyzed the wide application of neural network algorithm. Existing research shows that the use of CT technique combined with a variety of algorithm can achieve extraction and analysis of knot parameters features, and the accuracy in knot test could be improved through the continuous improvement of the algorithm. Finally, the main problems existing in knot testing with CT technology were summarized and the future tendency was also discussed.

英文关键词 knot;computed tomography technology;non-destructive testing;algorithm research

起始页码 50

截止页码 55

投稿时间 2015/1/12

分类号 S781.51

DOI 10.13348/j.cnki.sjlyyj.2015.05.005

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