高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于应力波传播速度模型的原木缺陷定量检测

魏喜雯 孙丽萍 许述正 杨扬 杜春晓

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

doi: 10.12171/j.1000-1522.20190420
基金项目: 黑龙江省自然科学基金(LC2018012),黑龙江省高等教育教学改革项目(SJGY20180433)
详细信息
    作者简介:

    魏喜雯,博士生。主要研究方向:传感器与执行器一体化、木材无损检测。Email:wxw198806@163.com 地址:150040 黑龙江省哈尔滨市香坊区和兴路26号东北林业大学机电工程学院

    责任作者:

    孙丽萍,博士,教授。主要研究方向:智能检测与监控。Email:zdhslp@163.com 地址:同上

  • 中图分类号: S781;TS67

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。

     

  • 图  1  应力波在立体原木中传播示意图

    O代表应力波发射端传感器的位置,SRR1代表应力波接收端传感器的位置。OL代表纵向轴,与木纹方向平行;OR代表径向轴,与生长环垂直;OT代表正切轴,与生长环相切。α为应力波径向与纵向传播之间的夹角,即方向角。β为应力波径向与横向传播之间的夹角,即弦向角。O represents the position of the stress wave emitting end sensor, S, R, R1 represent the positions of stress wave receiving end sensor. OL represents the longitudinal axis, parallel to the grain direction; OR represents the radial axis, perpendicular to the growth ring; OT represents the tangent axis, tangent to the growth ring. α is the angle between the radial and longitudinal propagation of stress wave, that is, the direction angle; β is the angle between the radial and cross propagation of the stress wave, that is, the chord angle.

    Figure  1.  Sketch map of stress wave propagation in a three-dimensional log

    图  2  不同方向角度纵截面传感器布置示意图

    1 ~ 12表示12个传感器。α表示方向角,β表示截面夹角。1−12 represent 12 sensors. α represents the direction angle, β represents the longitudinal section angle.

    Figure  2.  Distribution of stress wave sensors of longitudinal section in different directions

    图  3  4种健康原木不同方向角的应力波传播速度拟合曲线

    Figure  3.  Fitting curves of stress wave propagation velocity of 4 healthy logs in different direction angles

    图  4  4种健康原木不同截面夹角的应力波传播速度拟合曲线

    Figure  4.  Fitting curves of stress wave propagation velocity of 4 healthy logs in different longitudinal section angles

    5  健康落叶松不同方向角度纵截面夹角的应力波速度拟合曲面

    5.  Fitting curved surfaces of stress wave propagation velocity of healthy larch in longitudinal section with different direction angles

    图  6  缺陷直径为7.5 cm的落叶松原木二维成像图

    Figure  6.  Two-dimensional images of larch log with defect diameter of 7.5 cm

    图  7  完整的缺陷区域成像图

    Figure  7.  Complete images of defect area

    图  8  不同截面夹角下的缺陷区域成像图

    Figure  8.  Images of defect area with different cross section angles

    表  1  原木样本基本情况

    Table  1.   Basic information of sample log

    样木编号
    No. of
    Sample log
    胸径
    DBH/cm
    样本高度
    Height of
    sample tree/cm
    密度
    Density/
    (g·cm− 3)
    含水率
    Moisture
    content/%
    N117.4370.80.60745.99
    N220.8271.60.68656.06
    N333.6375.60.58460.45
    N420.7284.20.59451.23
    注:N1为白桦,N2为水曲柳,N3为榆树,N4为落叶松。Notes: N1 is Betula platyphylla, N2 is Fraxinus mandshurica, N3 is Ulmus pumila, and N4 is Larix gmelinii.
    下载: 导出CSV

    表  2  健康原木不同方向角的应力波传播速度

    Table  2.   Stress wave propagation velocities in different direction angles of healthy log m/s

    样木编号 No. of sample tree角1-12 Angle 1-12角1-11 Angle 1-11角1-10 Angle 1-10角1-9 Angle 1-9角1-8 Angle 1-8角1-7 Angle 1-7
    N11 5841 6901 7151 7921 8331 854
    N21 6141 8031 7951 9141 9762 094
    N31 7641 8051 8931 9861 9542 064
    N41 5931 6671 6491 7541 8331 855
    下载: 导出CSV

    表  3  健康原木不同截面夹角的应力波传播速度

    Table  3.   Stress wave propagation velocities in different longitudinal section angles of healthy log m/s

    样木编号
    No. of sample tree
    − 75°− 60°− 45°− 30°− 15°15°30°45°60°75°
    N11 3981 5661 6371 6381 7271 7151 7251 6471 6331 5771 388
    N21 2071 4351 5961 7081 7381 7951 8031 6881 5641 4951 205
    N31 5671 7091 7891 8621 8671 8931 8671 8441 7861 6951 593
    N41 3921 5171 5631 6331 6751 6491 6711 6771 5981 5321 411
    下载: 导出CSV

    表  4  健康落叶松和含空洞(直径7.5 cm)落叶松在不同方向角度纵截面的应力波传播速度

    Table  4.   Stress wave propagation velocities of healthy larch and defective larch (7.5 cm) in longitudinal sections with different directions

    发射端–接收端 Transmitter-receiver项目
    Item
    − 75°− 60°− 45°− 30°− 15°015°30°45°60°75°
    4–12 v1/(m·s− 1) 1 493 1 574 1 663 1 709 1 742 1 720 1 924 1 742 1 703 1 594 1 442
    v2/(m·s− 1) 1 442 1 583 1 684 1 703 1 727 1 757 1 773 1 712 1 654 1 577 1 456
    Δv/% 3.42 0.57 1.26 0.35 0.86 2.15 7.85 1.72 2.88 1.07 0.97
    4–11 v1/(m·s− 1) 1 432 1 548 1 607 1 644 1 685 1 684 1 832 1679 1 594 1 501 1 402
    v2/(m·s− 1) 1 386 1 524 1 617 1 640 1 684 1 703 1 649 1 645 1 607 1 521 1 386
    Δv/% 3.21 1.55 0.62 0.24 0.06 1.13 9.99 2.03 0.82 1.33 1.14
    4–10 v1/(m·s− 1) 1 366 1 492 1 544 1 589 1 603 1 755 1 639 1 663 1 632 1 493 1 337
    v2/(m·s− 1) 1 360 1 460 1 563 1 452 1 459 1 453 1 483 1 436 1 602 1 463 1 354
    Δv/% 0.44 2.14 1.23 8.62 8.98 17.21 9.52 13.65 1.84 2.01 1.27
    4–9 v1/(m·s− 1) 1 295 1 409 1 508 1 586 1 584 1 639 1 426 1 498 1 507 1 437 1 298
    v2/(m·s− 1) 1 312 1 409 1 502 1 583 1 570 1 647 1 585 1 598 1 502 1 408 1 302
    Δv/% 1.31 0 0.4 0.19 0.88 0.49 11.15 6.68 0.33 2.02 0.31
    4–8 v1/(m·s− 1) 1 337 1 485 1 561 1 603 1 588 1 624 1 657 1 607 1 590 1 469 1 354
    v2/(m·s− 1) 1 357 1 472 1 538 1 625 1 638 1 702 1 657 1 606 1 559 1 470 1 340
    Δv/% 1.50 0.88 1.47 1.37 3.15 4.80 0 0.06 1.95 0.07 1.03
    4–7 v1/(m·s− 1) 1 406 1 536 1 604 1 667 1 674 1 708 1 703 1 638 1 607 1 533 1 417
    v2/(m·s− 1) 1 408 1 538 1 594 1 672 1 685 1 709 1 638 1 648 1 632 1 538 1 389
    Δv/% 0.14 0.13 0.62 0.30 0.66 0.06 3.82 0.61 1.56 0.33 1.98
    注:v1v2 分别表示应力波在健康和含空洞落叶松原木不同方向角度纵截面的传播速度,Δv = $ \left|\frac{ {v}_{1}-{v}_{2} }{ {v}_{1} }\right| $。Notes: v1 and v2 respectively represent the propagation velocity of stress wave of healthy and cavitation-containing larch logs in longitudinal section with different direction angles, Δv = $\left|\frac{ {v}_{1}-{v}_{2} }{ {v}_{1} }\right| $.
    下载: 导出CSV

    表  5  成像结果的定量评价

    Table  5.   Quantitative evaluation on fault imaging results

    截面夹角
    Longitudinal section angle/(°)
    实际缺陷面积
    Actual defect area (Sz)/cm2
    重建缺陷面积
    Reconstruction defect area (Sj)/cm2
    图像拟合度
    Image fitness (r)/%
    误差率
    Error rate (λ)/%
    044.1648.1891.669.10
    1545.7249.9891.489.32
    3050.9955.3992.068.63
    注:r为木材缺陷实际面积(Sz)与重建图像检测的缺陷面积(Sj)的相对比值,即r = (Sz/Sj) × 100%。λ反映检测的缺陷面积与实际缺陷面积之间的偏离程度,即λ = $ \frac{\left|{S}_{\mathrm{j}}-{S}_{\mathrm{z}}\right|}{{S}_{\mathrm{z}}} $ × 100%。Notes: r is the ratio of actual defect area to the defect area of the reconstructed image, that is, r = (Sz/Sj) × 100%. λ reflects the degree of deviation between the reconstructed defect area and the actual defect area, that is, λ = $ \frac{\left|{S}_{\mathrm{j}}-{S}_{\mathrm{z}}\right|}{{S}_{\mathrm{z}}} $ × 100%.
    下载: 导出CSV
  • [1] 杨学春, 王立海. 应力波技术在木材性质检测中的研究进展[J]. 森林工程, 2002, 18(6):11−12. doi: 10.3969/j.issn.1001-005X.2002.06.006

    Yang X C, Wang L H. Research progresses of testing wood properties using stress wave[J]. Forest Engineering, 2002, 18(6): 11−12. doi: 10.3969/j.issn.1001-005X.2002.06.006
    [2] 王欣, 申世杰. 木材无损检测研究概况与发展趋势[J]. 北京林业大学学报, 2009, 31(1):202−205.

    Wang X, Shen S J. Advances in non-destructive testing for lumber[J]. Journal of Beijing Forestry University, 2009, 31(1): 202−205.
    [3] 焦治, 李光辉, 武夕. 基于速度误差校正的林木应力波无损检测断层成像算法[J]. 北京林业大学学报, 2018, 40(1):108−119.

    Jiao Z, Li G H, Wu X. Tomography imaging algorithm based on velocity error correction for stress wave nondestructive evaluation of wood[J]. Journal of Beijing Forestry University, 2018, 40(1): 108−119.
    [4] 张厚江, 王喜平, 苏娟, 等. 应力波在美国红松立木中传播机理的试验研究[J]. 北京林业大学学报, 2010, 32(2):145−148.

    Zhang H J, Wang X P, Su J, et al. Investigation of stress wave propagation mechanism in American red pine tree[J]. Journal of Beijing Forestry University, 2010, 32(2): 145−148.
    [5] 安源. 基于应力波的木材缺陷二维成像技术研究[D]. 北京: 中国林业科学研究院, 2013.

    An Y. Two-dimensional imaging technique of wood defects based on stress wave[D]. Beijing: Chinese Academy of Forestry, 2013.
    [6] Du X, Li S, Li G, et al. Stress wave tomography of wood internal defects using ellipse-based spatial interpolation and velocity compensation[J]. BioResources, 2015, 10(3): 3948−3962.
    [7] Li G, Weng X, Du X, et al. Stress wave velocity patterns in the longitudinal-radial plane of trees for defect diagnosis[J]. Computers and Electronics in Agriculture, 2016, 124: 23−28. doi: 10.1016/j.compag.2016.03.021
    [8] 杨学春, 王立海. 应力波在原木中传播理论的研究[J]. 林业科学, 2005, 41(5):132−138. doi: 10.3321/j.issn:1001-7488.2005.05.024

    Yang X C, Wang L H. Study on the propagation theories of stress wave in log[J]. Scientia Silvae Sinicae, 2005, 41(5): 132−138. doi: 10.3321/j.issn:1001-7488.2005.05.024
    [9] 徐华东, 王立海, 游祥飞, 等. 应力波在旱柳立木内的传播规律分析及其安全评价[J]. 林业科学, 2010, 46(8):145−150.

    Xu H D, Wang L H, You X F, et al. Analysis of stress wave propagation in Hankow willow standing trees and stability assessment[J]. Scientia Silvae Sinicae, 2010, 46(8): 145−150.
    [10] 翁翔, 李光辉, 冯海林, 等. 应力波在树木径切面内的传播速度模型[J]. 林业科学, 2016, 52(7):104−112.

    Weng X, Li G H, Feng H L, et al. Stress wave propagation velocity model in RL plane of standing trees[J]. Scientia Silvae Sinicae, 2016, 52(7): 104−112.
    [11] Li G H, Wang X P, Feng H L, et al. Analysis of wave velocity patterns in black cherry trees and its effect on internal decay detection[J]. Computers and Electronics in Agriculture, 2014, 104: 32−39. doi: 10.1016/j.compag.2014.03.008
    [12] Mascia N T, Nicolas E A, Cammpinas S, et al. Comparison between tsai-wu failure criterion and hankinson’s formula for tension in wood[J]. Wood Research, 2011, 56(4): 499−510.
    [13] Dikrallah A, Hakam A, Brancheriau L, et al. Experimental analysis of acoustic anisotropy of wood by using guided waves[C]//Proceedings of International Conference on Integrated Approach to Wood Structure, Behaviour and Application, Joint Meeting of ESWM and COST Action E35. Florence: Aalborg Universitet, 2006: 149−154.
    [14] 岳小泉, 王立海, 王兴龙, 等. 空洞缺陷形状对杉木圆盘电阻与应力波断层成像效果的影响[J]. 南京林业大学学报(自然科学版), 2016, 40(5):131−137.

    Yue X Q, Wang L H, Wang X L, et al. Effects of artificial cavity defects on electric resistance tomography and stress wave technology of Cunninghamia lanceolata discs[J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2016, 40(5): 131−137.
    [15] Liu W, Xie W, Dang Y, et al. Image reconstruction modeling, simulation and experimental study on wood fibrous paper[J/OL]. Journal of Natural Fibers, 2019: 1−14 [2019−11−01]. https://doi.org/10.1080/15440478.2019.1585309.
    [16] 冯海林, 李光辉, 方益明, 等. 应力波传播模型及其在木材检测中的应用[J]. 系统仿真学报, 2010, 22(6):1490−1493.

    Feng H L, Li G H, Fang Y M, et al. Stress wave propagation modeling and application in wood testing[J]. Journal of System Simulation, 2010, 22(6): 1490−1493.
    [17] Du X, Li J, Feng H, et al. Image reconstruction of internal defects in wood based on segmented propagation rays of stress waves[J]. Applied Sciences, 2018, 8(10): 1−18. doi: 10.3390/app8101778
    [18] 岳小泉, 王立海, 王兴龙, 等. 电阻断层成像、应力波及阻抗仪3种无损检测方法对活立木腐朽程度的定量检测[J]. 林业科学, 2017, 53(3):138−146. doi: 10.11707/j.1001-7488.20170315

    Yue X Q, Wang L H, Wang X L, et al. Quantitative detection of internal decay degree for standing trees based on three NDT methods: electric resistance tomography, stress wave imaging and resistograph techniques[J]. Scientia Silvae Sinicae, 2017, 53(3): 138−146. doi: 10.11707/j.1001-7488.20170315
    [19] Stroble J R A, De Carvalho M A G, Gonçalves R, et al. Quantitative image analysis of acoustic tomography in woods[J]. European Journal of Wood and Wood Products, 2018, 76(5): 1379−1389. doi: 10.1007/s00107-018-1323-y
    [20] Feng H, Li G, Fu S, et al. Tomographic image reconstruction using an interpolation method for tree decay detection[J]. BioResources, 2014, 9(2): 3248−3263.
  • 加载中
图(9) / 表(5)
计量
  • 文章访问数:  976
  • HTML全文浏览量:  663
  • PDF下载量:  19
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-11-04
  • 修回日期:  2019-12-02
  • 网络出版日期:  2020-05-04
  • 刊出日期:  2020-07-01

目录

    /

    返回文章
    返回