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    魏喜雯, 孙丽萍, 许述正, 杨扬, 杜春晓. 基于应力波传播速度模型的原木缺陷定量检测[J]. 北京林业大学学报, 2020, 42(5): 143-154. DOI: 10.12171/j.1000-1522.20190420
    引用本文: 魏喜雯, 孙丽萍, 许述正, 杨扬, 杜春晓. 基于应力波传播速度模型的原木缺陷定量检测[J]. 北京林业大学学报, 2020, 42(5): 143-154. DOI: 10.12171/j.1000-1522.20190420
    Wei Xiwen, Sun Liping, Xu Shuzheng, Yang Yang, Du Chunxiao. Quantitative detection of log defects based on stress wave propagation velocity model[J]. Journal of Beijing Forestry University, 2020, 42(5): 143-154. DOI: 10.12171/j.1000-1522.20190420
    Citation: Wei Xiwen, Sun Liping, Xu Shuzheng, Yang Yang, Du Chunxiao. Quantitative detection of log defects based on stress wave propagation velocity model[J]. Journal of Beijing Forestry University, 2020, 42(5): 143-154. DOI: 10.12171/j.1000-1522.20190420

    基于应力波传播速度模型的原木缺陷定量检测

    Quantitative detection of log defects based on stress wave propagation velocity model

    • 摘要:
      目的研究应力波在原木上传播速度变化情况,建立不同方向角和纵截面夹角的应力波传播速度模型,以期进一步认识应力波在原木不同方向角度纵截面内的传播规律,为树木内部缺陷的二维成像技术提供理论与实验依据。
      方法首先通过理论分析,建立应力波在原木不同方向角度纵截面的传播速度模型;然后以东北地区4种具有代表性的树种为样本,采用Arbotom应力波木材无损检测仪测量应力波在不同方向角、不同截面夹角和不同方向角度纵截面上的传播速度,对健康原木样本的应力波传播速度v\left(\alpha \right)与方向角α,应力波传播速度v\left(\beta \right)与截面夹角β,以及应力波传播速度v\left(\alpha,\beta \right)αβ之间的关系进行回归分析。
      结果在同一纵截面上,应力波传播速度随方向角的增大而增大,水平方向速度最小;在同一方向角度的不同纵截面上,应力波传播速度随截面夹角的增大而减小,径向传播速度最大。健康样本实验数据的拟合结果与理论数学模型非常吻合,决定系数均大于0.87,显著性P都小于0.01,模型都具有较高的拟合优度。针对落叶松原木试样,人工设计了直径为7.5 cm的空洞缺陷,利用相关系数0.97,均方根误差17.81的健康多元回归模型v\left(\alpha,\beta \right) = 109.2\alpha ^2 - 182.1\beta ^2 + 36.78\alpha ^2\beta ^2 - 34.76\alpha ^2\beta ^4 + 1 \; 627进行二维成像。当应力波传播路径位于原木的健康区域时,传播速度随方向角和截面夹角的变化趋势满足该模型;但当应力波经过原木的缺陷区域时,传播速度明显降低,不再符合正常情况下的传播速度模型。基于二维成像结果,图像的拟合度高达92.06%,测量缺陷空洞的误差率为8.63%。
      结论应力波在健康原木不同角度纵截面上传播的多元回归模型对树木内部缺陷检测具有很好的指导作用,利用该模型结合二维成像技术,能准确地检测出原木内部缺陷位置和大小,为三维成像技术提供了理论与实验依据。

       

      Abstract:
      ObjectiveThis paper aims to study the variation of stress wave propagation velocity in the longitudinal section of trees at different angles, and to establish the corresponding propagation velocity model, so as to further understand the propagation law of stress wave in the longitudinal section of trees at different angles, and to provide theoretical and experimental basis for the two-dimensional imaging technology of internal defects of logs.
      MethodFirstly, through theoretical analysis, the propagation velocity model of stress wave in longitudinal section of logs with different directions was established. Then, four representative tree species in the northeastern region of China were taken as test samples, and the propagation velocity of stress wave in longitudinal section of logs with different directions, angles of different sections and angles of different directions was measured by stress wave wood nondestructive testing instrument. The relationship of healthy samples between stress wave propagation velocity v\left(\alpha \right) and direction angle α, propagation velocity v\left(\beta \right) and longitudinal section angle β, v\left(\alpha,\beta \right) and α, β were obtained, respectively by regression analysis.
      ResultIn the same longitudinal section, the propagation velocity of stress wave increased with the increase of direction angle, and the velocity of the horizontal direction was the smallest. At the same direction angle, the propagation velocity of the stress wave increased with the increase of longitudinal section angle, and the propagation velocity of radial direction was the greatest. The fitting results of the health sample test data were in good agreement with the theoretical mathematical model. The determination coefficient R2 was all greater than 0.87, and the significance P was less than 0.01. The models had higher goodness of fit. For the larch log samples, the cavity defects with diameters of 7.5 cm were designed artificially, and the two-dimensional imaging was performed using the healthy multiple regression model v\left(\alpha,\beta \right) = 109.2\alpha ^2 - 182.1\beta ^2 + 36.78\alpha ^2\beta ^2 - 34.76\alpha ^2\beta ^4 + 1 \; 627 with correlation coefficient R2 of 0.97 and root mean square error RMSE of 17.81. When the propagation path of stress wave was located in the healthy area of the wood, the variation trend of the propagation velocity with the direction angle and longitudinal section angle fitted the model; but when the stress wave passed through the defective area of the wood, the propagation velocity was significantly reduced, no longer in normal condition. Based on the results of two-dimensional imaging, the fitness of the images was 92.06%, and the error rate of measuring defect cavities was 8.63%.
      ConclusionThe analysis showes that the regression model of stress wave propagation in different longitudinal sections of healthy logs is in good agreement with the theoretical model proposed in this paper, and further verifies that the velocity model has a good guiding role in the detection of internal defects of healthy logs.

       

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