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 classification 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% respectively. This detection method can not only recognize wood defect but also can accurately distinguish the defect type including voids, cracks, and decay.