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Feature extraction of wood-hole defects using empirical mode decomposition of ultrasonic signals
NDT & E International ( IF 4.2 ) Pub Date : 2020-05-18 , DOI: 10.1016/j.ndteint.2020.102282
Mohsen Mousavi , Mohammad Sadegh Taskhiri , Damien Holloway , J.C. Olivier , Paul Turner

Holes and knots are common defects that occur in wood that affect its value for both structural and high-end aesthetic applications. When these defects are internal to wood they are rarely evident from visual inspection. It is therefore important to develop techniques to detect and analyse these defects both in standing trees prior to harvesting them and in processed timber and/or completed wooden structures. This paper presents an effective method to detect and analyse hole defects in wood. The method uses the recorded output wave signal from an ultrasonic device tested on rectangular wood samples. The ultrasonic wave signal is decomposed into its constructive modes using Empirical Mode Decomposition (EMD). This process decomposes a non-stationary non-linear wave signal into its semi-orthogonal bases known as intrinsic mode functions (IMFs). A matrix of all IMFs (except the residual IMF) is then assembled and its covariance matrix derived. The research demonstrates through several experimental studies that the maximum eigenvalue of the proposed covariance matrix is more sensitive to hole defects in wood than traditionally used measures such as time-of-flight. The results provide evidence that the proposed damage sensitive feature (DSF) can successfully detect hole defects in hardwood samples but further work is recommended on its application to other materials. It is anticipated that this method will have wide applicability in the forestry and timber industries for aiding in product value determination.



中文翻译:

利用超声信号的经验模态分解提取木孔缺陷特征

孔和结是木材中常见的缺陷,会影响其在结构和高端美学应用中的价值。当这些缺陷在木材内部时,从目视检查中几乎看不到。因此,重要的是要开发一种技术,以检测和分析立木采伐前的缺陷以及加工过的木材和/或完整的木质结构中的缺陷。本文提出了一种有效的方法来检测和分析木材中的孔缺陷。该方法使用在矩形木材样品上测试过的超声波设备记录的输出波信号。使用经验模式分解(EMD)将超声波信号分解为其构造模式。此过程将非平稳非线性波信号分解为其半正交基,称为本征模函数(IMF)。然后组装所有IMF的矩阵(剩余IMF除外),并导出其协方差矩阵。该研究通过多项实验研究证明,与传统使用的飞行时间测量方法相比,拟议的协方差矩阵的最大特征值对木材中的孔缺陷更敏感。结果提供了证据,表明所提出的损伤敏感特征(DSF)可以成功检测硬木样品中的孔缺陷,但建议将其进一步应用于其他材料。预计该方法将在林业和木材工业中广泛应用于辅助产品价值确定。该研究通过多项实验研究证明,与传统使用的飞行时间测量方法相比,拟议的协方差矩阵的最大特征值对木材中的孔缺陷更敏感。结果提供了证据,表明所提出的损伤敏感特征(DSF)可以成功检测硬木样品中的孔缺陷,但建议将其进一步应用于其他材料。预期该方法将在林业和木材工业中广泛用于辅助产品价值确定。该研究通过多项实验研究证明,与传统使用的飞行时间测量方法相比,拟议的协方差矩阵的最大特征值对木材中的孔缺陷更敏感。结果提供了证据,表明所提出的损伤敏感特征(DSF)可以成功检测硬木样品中的孔缺陷,但建议将其进一步应用于其他材料。预计该方法将在林业和木材工业中广泛应用于辅助产品价值确定。结果提供了证据,表明所提出的损伤敏感特征(DSF)可以成功检测硬木样品中的孔缺陷,但建议将其进一步应用于其他材料。预计该方法将在林业和木材工业中广泛应用于辅助产品价值确定。结果提供了证据,表明所提出的损伤敏感特征(DSF)可以成功检测硬木样品中的孔缺陷,但建议将其进一步应用于其他材料。预计该方法将在林业和木材工业中广泛应用于辅助产品价值确定。

更新日期:2020-05-18
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