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    王忠铖, 杨娜, 李久林. 无损检测指标与木材横纹局部抗压强度和密度的相关性[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20230367
    引用本文: 王忠铖, 杨娜, 李久林. 无损检测指标与木材横纹局部抗压强度和密度的相关性[J]. 北京林业大学学报. DOI: 10.12171/j.1000-1522.20230367
    Wang Zhongcheng, Yang Na, Li Jiulin. Correlation between non-destructive testing indicators and local transverse compressive strength and density of wood[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20230367
    Citation: Wang Zhongcheng, Yang Na, Li Jiulin. Correlation between non-destructive testing indicators and local transverse compressive strength and density of wood[J]. Journal of Beijing Forestry University. DOI: 10.12171/j.1000-1522.20230367

    无损检测指标与木材横纹局部抗压强度和密度的相关性

    Correlation between non-destructive testing indicators and local transverse compressive strength and density of wood

    • 摘要:
      目的 探索不同类型和数量的无损检测(NDT)指标与木材横纹局部抗压强度和密度的相关性差异,确定最优NDT指标组合,为基于无损检测手段评估木材横纹局部抗压强度和密度的研究提供参考。
      方法 以某典型藏式古建筑木结构梁构件为研究对象,锯解得到横纹局部抗压无疵试样。通过物理力学试验和NDT试验,获得无疵试样的密度ρ、横纹局部抗压强度flc,以及顺纹应力波速vl、横纹应力波速v和微钻阻力F,计算不同NDT指标或指标组合与ρflc的线性相关系数,进而对比讨论。
      结果 (1)使用单一NDT指标预测ρ时,vl效果较好,二者相关系数绝对值为0.662,补充微钻阻力均值Fm后可提高15.56%,达到0.765;使用单一NDT指标预测flc时,Fm效果较好,二者相关系数为0.526,在此基础上补充横纹应力波速均值vm可使相关系数提升26.80%,达到0.667;进一步补充vl后相关系数继续提升7.20%,达到0.715。(2)当两组NDT指标中的基本指标构成一致时,即便基本指标的形式存在差异,两组NDT指标与被预测参数的相关系数也近似。(3)当两个与被预测参数相关性较好的NDT指标组合时,相关系数可能进一步提高;当相关性较好的指标与较差的指标组合时,相关系数接近于前者;当相关性较差的指标与不相关指标组合时,相关系数可能大幅提升,也可能仍然较低;当两个均不显著相关的指标组合时,指标组合与被预测参数仍不具有显著相关性。
      结论 确定合理的NDT指标比一味增加指标数量对提高相关系数影响更大。综合考虑相关系数提升效果和由此可能增加的测试工作量,预测木材密度和横纹局部抗压强度时建议分别使用“vlFm”和“Fmvm”的NDT指标组合。

       

      Abstract:
      Objective The differences in correlation between different types and quantities of non-destructive testing (NDT) indicators and the local transverse compressive strength and density of wood were studied, and the optimal combination of NDT indicators were determined, in order to provide reference for the evaluation of transverse local compressive strength and density of wood based on NDT methods.
      Method The beam components from a typical Tibetan ancient building wooden structure were taken as the research object, and the local transverse compressive samples were sawn off. By conducting physical and mechanical tests and NDT tests, the density (ρ), local transverse compressive strength (flc), longitudinal and transverse stress wave velocity (vl and v), and micro drilling resistance (F) were measured. The linear correlation coefficients between different NDT indicators or indicator combinations and ρ, flc were calculated, and then comparatively discussed.
      Result (1) The correlation coefficient between vl and ρ was the highest when using single NDT index, at 0.662, after supplementing the Fm (the mean value of F), it can be increased by 15.56%, reaching 0.765. The correlation coefficient between Fm and flc was the highest when using single NDT indicator, at 0.526, after supplementing the vm (mean value of v), it can be increased by 26.80%, reaching 0.667; after further supplementing the vl, it can be further increased by 7.20%, reaching 0.715. (2) When the basic indicators in two sets of NDT indicator combinations are consistent, even if there are differences in the form of basic indicators, the correlation coefficients between the two sets and the predicted parameters are approximate. (3) When two NDT indicators with good correlation with the predicted parameters are combined, the correlation coefficient of the combined model may further increase; when NDT indicators with good correlation are combined with indicators with poor correlation, the correlation coefficient of the combination model is close to the former; when NDT indicators with poor correlation are combined with unrelated indicators, the correlation coefficient may increase significantly or remain poor; when two NDT indicators that are not significantly correlated are combined, the combination of NDT indicators still does not have a significant correlation with the predicted parameters.
      Conclusion Determining reasonable NDT indicators has a greater impact on improving the correlation than simply increasing the number of indicators. Taking into account the improvement effect of correlation coefficients and the potential increase in testing workload, it is recommended to use the combination of “vl, Fm” and “Fm, vm” for predicting the density and local transverse compressive strength of wood, respectively.

       

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