基于计算机断层扫描技术的木材密度检测研究

使用计算机断层扫描技术进行原木无损检测,通过对原木树种断层 CT 值的统计,对 CT 设备在检测过程中的窗宽与窗位进行了设定,同时拟合出了木材 CT 值一密度值的线性方程,为原木缺陷的无损检测及木材密度的测定提供一种新方法。     

计算机断层扫描技术检测木材缺陷的研究

木材无损检测技术是一门新兴的、综合性的木材非破坏性检测技术，可以应用计算机断层扫描技术（Cr）对原木进行无损检测。计算机断层扫描技术是X射线无损检测的一个分支，是对X射线的应用。本论文通过对Cr的利用，通过对Cr图像的提取、分析和处理，找出了一套方便于Cr图像的重建和去除噪声的算法，从而提出利用计算机断层技术（Cr）对木材进行缺陷检测，该方法是可行的。     

基于多重分形理论的原木CT腐朽图像分析与处理

使用计算机断层扫描技术进行原木无损检测,采用多重分形频谱分析方法可以对原木CT图像进行有效的边缘检测,该方法首先计算图像各像素点的H lder指数α(x,y),然后估计出其多重分形频谱f(α)的值,对图像的像素点进行分类,f(α)=1为平滑边缘点,1≤f(α)<1.5为奇异边缘点。根据多重分形理论,平滑点和奇异点的集合即为图像的边缘点。实验结果表明,该方法对原木CT图像的边缘检测具有良好的效果,并具有较好的局部性,为原木CT图像的边缘检测提供了一种新方法。     

计算机断层扫描技术检测七叶树种子生活力

为了探讨能够快速、准确和无损检测大粒林木种子生活力的方法,本文对计算机断层扫描(CT)检测七叶树种子生活力的技术进行了研究.结果表明,用计算机断层扫描(CT)技术检测七叶树种子生活力是可行的,其检测结果与四唑测定的结果相当,但计算机断层扫描(CT)技术具有不损伤种子的优点.     

基于计算机断层扫描技术的木材节子检测算法研究

介绍了目前国内外通过计算机断层扫描技术(CT)结合各种算法对木材中节子部分进行无损检测所取得的研究进展,概述了以灰度阈值法、滤波算法、最大似然法和神经网络法为主的算法识别特点,并对其中应用广泛的神经网络算法进行了对比分析。现有研究表明,运用该技术结合多种算法可实现对原木中节子参数特征的提取与分析,通过算法的不断改进能够提高节子检测的准确率。文中还总结了CT技术在处理节子检测方面存在的主要问题,并对未来趋势进行了展望。     

工业CT扫描在原木内部缺陷检测中应用

利用工业CT对三组原木进行扫描,并通过VGStudioMAX软件将扫描数据进行三维重建,检测原木内部缺陷。结果表明:原木的三维重建体模型能反映出缺陷在原木中的三维空间分布情况,对原木截面的虚拟剖切,可直观了解缺陷的形状、位置和分布,精确获知缺陷的大小,实现优质和珍贵原木的利用率及利用价值最大化。     

计算机断层扫描技术在木材科学中应用研究进展

计算机断层扫描（CT）技术作为一种高质、高效的无损检测技术,具有重建图像分辨率高、速度快等优点。鉴于该技术在医学领域取得的重大成就,国内外学者基于CT技术对木材做了大量研究,并将其应用于木材科学研究领域,验证了CT技术在木材检测和木材加工领域的可行性,同时取得了良好的使用效果。文中综述了CT技术在木材缺陷检测、木材宏观构造检测和木材切割中应用的研究进展,分析了现有技术存在的问题,展望了CT技术在木材科学领域的应用前景。     

具有图像处理功能的原木X射线检测系统

选择 X 射线作为检测源透射原木,根据检测透过被检物体后的射线强度差异,判断被检测原木内部是否存在缺陷和检测缺陷细节。检测过程中应用计算机数字图像处理技术对原始的 X 射线图像进行中值滤波、图像增强、差分和边缘检测,使得处理后的图像更加清晰,图像中的目标易于人眼识别。实验结果表明这种方法行之有效。     

木材CT图像的三维重构

运用CT技术对木材进行无损检测,运用多重分型频谱技术可以对木材CT图像进行有效的边缘检测.针对木材CT图像低对比度、原木缺陷边缘提取困难等问题,采用多重分型频谱技术对处理后的图像进行提取,提取的边缘信息清晰完整、准确度较高,为后续的木材CT图像的三维重建提供有效信息.使用线性插值法对木材CT图像进行三维重建,该方法具有便于理解、实现简单和运算速度快的特点.所运用的线性插值法对木材CT图像三维重建的过程有较好重建效果,具有重建图像直观、清晰的优点,这种重建理论为提高木材利用效率和原木的虚拟切割提供了一种有效的思路.     

基于模糊聚类分析的木材缺陷CT图像分割

为了提高木材的利用率,在木材加工之前对木材缺陷CT图像进行分割,将节子和空洞等缺陷分割出来,通过观察缺陷的位置便于工人师傅下锯。利用计算机断层扫描（CT）技术获取木材缺陷图像,将数字图像处理技术与模糊聚类算法相结合,在标准的模糊C均值算法的基础上改进,采用半模糊聚类的分析方法对木材缺陷图像进行分割检测。实验结果表明：基于半模糊聚类的图像检测方法在木材图像检测上取得了较好的效果,缺陷边缘处很平滑,细节保留完整,更多的保留了边缘上的信息。从而证明了半模糊聚类分析法在木材缺陷CT图像处理方面具有可行性。     

Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition

Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood.     

马尾松枕资下锯图的研究

为合理加工原木，提高出枕率和综合出枕率，提高企业经济效益。根据对福建省马尾松原木调查结果和原木出材率理论，建立了一系列枕资下锯的数学模型，编制了ＡＢＳＩＣ程序。此软件可供操作人员按实际生产需要，选择最佳方案。为进一步实现制材工业自动化提供了理论基础。     

Comparing predictability of board strength between computed tomography,discrete X-ray,and 3D scanning of Norway spruce logs

Strength graded boards of Norway spruce (Picea abies (L.) Karst.) are important products for many Scandinavian sawmills. If the bending strength of the produced boards can be predicted before sawing the logs, the raw material can be used more efficiently. In previous studies it is shown that the bending strength can be predicted to some extent using discrete X-ray scanning of logs. In this study, we have evaluated if it is possible to predict bending strength of Norway spruce boards with higher accuracy using computed tomography (CT) scanning of logs compared to a combination of discrete X-ray and 3D scanning. The method was to construct multivariate models of bending strength for three different board dimensions. Our results showed that CT scanning of logs produces better models of bending strength compared to a combination of discrete X-ray and 3D scanning. The main reason for this difference was the benefit of knowing the position of where the boards were cut from the logs and therefore detailed knot information could be used in the prediction models. Due to the small number of observations in this study, care should be taken when comparing the resulting prediction models to results from other studies.     

Measurement of spiral grain with computed tomography

Spiral grain is a feature of wood that affects the shape of the sawn timber. Boards sawn from logs with a large spiral grain have a tendency to twist when the moisture content changes. In sawmills the spiral grain in logs is judged manually. For research purposes the spiral grain in stems and logs is normally measured by destructive methods. In this study the spiral grain of the stems was measured nondestructively with a computed tomography (CT) scanner. Twelve Norway spruce (Picea abies) stems from two stands in Sweden were scanned with a CT scanner with one cross-sectional scan every 10mm along the stem. Concentric surfaces at various distances from the pith were reconstructed from the stack of CT images. In these concentric-surface images, which show various internal features of the log. the spiral grain angle was measured at different distances from the pith and at different heights in the stem. The destructive measurements of the spiral grain were carried out on disks from the top ends of the logs. On these disks the spiral grain was measured at different distances from the pith with a protractor. Finally, the results from the destructive method were compared with the results from analysis of the CT images. The nondestructive and destructive measurements were compared in pairs with the same radial and approximately the same height position in each pair. The correlations (r) between the two methods were 0.81 and 0.71. respectively, for the two stands. It was concluded that it is possible to measure the spiral grain angle nondestructively with a CT scanner.An outline of this study was presented at the 50th Annual Meeting of the Japan Wood Research Society, Kyoto     

Predicting the Stiffness of Sawn Products by X-ray Scanning of Norway Spruce Saw Logs

The aim of the study was to investigate the possibility of strength grading Norway spruce [Picea abies (L.) Karst.] saw logs on the basis of simulated X-ray LogScanner measurements and to evaluate the potential accuracy of X-ray LogScanner measurements of green heartwood density and percentage of heartwood. The study was based on 272 logs for strength grading and 29 logs for measurements of green heartwood density and percentage of heartwood. The logs were scanned using computed tomography (CT). After sawing, the modulus of elasticity (MOE) of the centre boards was measured using a strength-grading machine. The CT images were used for simulations of an X-ray LogScanner, resulting in simulated measurements of different variables such as diameter, taper, percentage of heartwood, density and density variations. Multivariate models for prediction of MOE were then calibrated using partial least squares (PLS) regression. The MOE of a log was defined as the mean value of the MOE of the two centre boards. The study showed that the simulated X-ray LogScanner measured the percentage of heartwood and green heartwood density with relatively high accuracy (R ² = 0.94 and R ² = 0.73, respectively, after removing two outliers) and that these and other variables measured by the simulated X-ray LogScanner could be used to predict the stiffness of the centre boards. These predictions were used to sort the logs according to the predicted MOE. When sorting out 50% of the logs (''high-strength'' logs), the percentage of C30 boards increased from 73% (all logs in the study) to 100% (only ''high-strength'' logs). The rest of the logs could then be divided into two groups, one of them with 100% C24 and C30 boards.     

A comparison between three different methods of measuring knot parameters in picea abies

Both foresters and sawmillers are interested in the knot structure of trees; in particular, position and number of knots, knot diameter, knot length and dead knot border. For research purposes, it is possible today to carry out non‐destructive measurements using computer tomography (CT) and image analysis. The aim of this study was to measure knot parameters on Norway spruce (Picea abies (L.) Karst.) using a non‐destructive method developed for Scots pine (Pinus sylvestris L.), and to compare the results of this method with the results of two different destructive methods. In order to do this, two Norway spruce stems were scanned by CT. Then five logs from one stem were cut into flitches 20 mm thick and the defects on the sawn surfaces were scanned manually. The other stem was cut just above every whorl and then each knot was split through its centre and the knot parameters were measured manually. The study showed that the CT method compares well with the destructive methods. It is a reasonably fast, non‐destructive method which measures position and diameter of knots and detects larger knots with acceptable accuracy. The study also showed that a large number of smaller knots were not found by the CT method and that the CT method measured knot length and dead knot border with low accuracy. This means that the CT method has to be adjusted to Norway spruce in order to improve its ability to measure knot length and dead knot border and to detect smaller knots.     

Log sawing position optimization using computed tomography scanning

When disjoining a log, several factors affect the value of the sawn timber. There are log features, such as outer shape, knots, rot, and so on. There are also sawing parameters, such as sawing pattern, log position, and so on. If full information about log features is available, sawing parameters can be adapted in order to maximize product value in sawmills. This is soon possible, since computed tomography (CT) scanners for the sawmill industry are being realized. This study aimed at investigating how CT data can be used to choose rotational position, parallel displacement, and skew of sawlogs, to maximize the value of the sawn products. The study was made by sawing simulation of 269 CT scanned logs of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies [L.] H. Karst.). The results showed that value recovery could be improved by 13% in average, compared to a sawing position based on log outer shape, and 21% compared to sawing logs centered and horns down. It can be concluded that a CT scanner, used in a sawline to optimize sawing parameters, has a large potential for increasing value recovery and thus profit.