基于计算机视觉的定向刨花板内部三维结构信息挖掘方法构建与应用

石允峰; 洪吾俊; 段衍筠; 李万兆; 梅长彤

doi:10.12326/j.2096-9694.2025026

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基于计算机视觉的定向刨花板内部三维结构信息挖掘方法构建与应用
Construction and Application of Three-Dimensional Structural Data Mining Method for OSB Based on Computer Vision
南京林业大学材料科学与工程学院，江苏南京 210037
2025年39卷第3期页码：49-57
DOI： 10.12326/j.2096-9694.2025026
稿件说明：

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石允峰,洪吾俊,段衍筠等.基于计算机视觉的定向刨花板内部三维结构信息挖掘方法构建与应用[J].木材科学与技术,2025,39(03):49-57. DOI： 10.12326/j.2096-9694.2025026.

SHI Yunfeng,HONG Wujun,DUAN Yanjun,et al.Construction and Application of Three-Dimensional Structural Data Mining Method for OSB Based on Computer Vision[J].Chinese Journal of Wood Science and Technology,2025,39(03):49-57. DOI： 10.12326/j.2096-9694.2025026.

摘要

定向刨花板（oriented strand board，OSB）是一种以长片大刨花为主要原材料的木质结构人造板，其物理力学性能与内部结构密切相关。为了深入解析OSB构效关系，研究提出一种基于计算机视觉重构OSB内部三维结构的方法。选用旋切单板裁切刨花制备1.2 cm厚OSB，拍摄记录铺装过程，利用计算机视觉技术捕捉刨花铺装的位置，并对铺装后层叠刨花进行单片刨花轮廓提取，再结合断面密度梯度（vertical density profile，VDP）数据计算板坯厚度方向的压缩率，使用Python软件重构OSB内部三维结构。制备5 cm×5 cm（长×宽）的试件并记录质量，检测VDP、内部三维结构和孔隙率。结果表明，制备OSB用刨花总数为2 299片，计算机正确识别所有刨花，其中2 232片刨花完整分割（占比97.1%）。试件实测预测质量、孔隙率、VDP的决定系数

分别为0.976、0.951、0.812。对比X射线断层扫描（X-ray CT）结果和计算机视觉重构结果发现，三维可视化结构一致性好。基于重构结果，可进一步量化所有刨花的定向角度、面积和施胶效果。计算机视觉方法能够准确可视化和量化OSB试件内部三维结构，为OSB构效关系研究提供可靠基础数据。

Abstract

Oriented strand board (OSB) is a wood-based structural panel

which is primarily composed of long strands. The physical and mechanical properties are closely related to its internal structure. Since the internal structure of OSB is formed through directional alignment and random layered overlapping of strands

precise characterization of the internal structure is crucial for understanding its structure-property relationships. This study proposes a computer vision-based method for constructing the three-dimensional internal structure of

OSB. Strands were prepared by cutting peeled veneer sheets

and 1.2 cm thick OSB panels were fabricated. The mat-forming process was continuously recorded using imaging technology. Computer vision-based techniques were employed to capture strand positions after forming

followed by individual strand contour extraction. Combined with vertical density profile (VDP) data for calculating thickness-direction compression ratios

Python software was utilized to reconstruct the 3D internal structure of OSB. Specimens (5 cm × 5 cm) were prepared to measure weight

VDP

3D structure

and porosity. Results showed that the total number of strands in fabricated OSB was 2 299

with all strands correctly identified and 2 232 strands (97.1%) completely segmented through computer processing. Determination coefficient (

) between measured and predicted values reached 0.976 for weight

0.951 for porosity

and 0.812 for VDP respectively. Comparative analysis with X-ray computed tomography (CT) showed excellent consistency in 3D visualization. Vision-based construction enables quantitative analysis of orientation angles

surface areas

and resin distribution for all strands. This computer vision approach provides exact visualization and quantification of OSB's internal 3D structure

establishing reliable fundamental data for investigating structure-property relationships in OSB.

关键词

Keywords

references

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