南京林业大学学报（自然科学版）Issue(3)：130-136,7.DOI:10.3969/j.issn.1000-2006.2015.03.024
基于应力波和支持向量机的木材缺陷识别分类方法
A method of wood defect identification and classification based on stress wave and SVM
摘要
Abstract
The existing stress wave testing can only determine the existence of defects in the wood, but can not classify the type of wood defect. This paper presents a method which combines stress wave nondestructive testing technology and support vector machine ( SVM) to identify and classify wood defects. This method measures stress wave velocity in the wood firstly, and then classifies the internal conditions of wood using SVM with the stress wave velocity as the classifica⁃tion feature. In order to demonstrate the effectiveness of the proposed method, 31 pecan wood samples and 28 pine wood samples with different conditions were selected as experimental samples. The Arbotom detector from Rinntech Company in German was used to collect 117 groups of data of stress wave velocity from pecan wood and 80 groups of data of stress wave velocity from pine wood. The classification accuracy of pecan wood and pine wood are 93.75% and 95% respective⁃ly. This detection method can not only recognize wood defect but also can accurately distinguish the defect type including voids, cracks, and decay.关键词
应力波传播速度/木材缺陷识别/支持向量机/无损检测Key words
stress wave propagation velocity/wood defect identification/support vector machine/nondestructive testing分类
农业科技引用本文复制引用
王再超,李光辉,冯海林,方益明,费欢..基于应力波和支持向量机的木材缺陷识别分类方法[J].南京林业大学学报（自然科学版）,2015,(3):130-136,7.基金项目
国家自然科学基金项目（61272313，61302185，61472368）；浙江省科技厅项目（2012C21015，2013C31018，2013C24026，2014C31044）；浙江省自然科学基金项目（LQ13F020013）；浙江省大学生创新创业孵化项目（2013R412055）；浙江省林业智能监测与信息技术研究重点实验室资助项目 （）
