Evaluation of surface smoothness by laser displacement sensor 1: effect of wood species

The best methods for determining surface roughness in an industrial environment are of the noncontact variety, with reproduction of the profile. The objective of this work was to compare the roughness profile obtained by a contact stylus with a commercial laser displacement sensor (LDS). Measurements were done using 15 wood species with different densities and colors, based on which special triangle profiles were prepared. The accuracy of the laser sensor was examined by statistical analysis of roughness parameters measured from the profiles. Experimental results show that LDS profiles were imitated correctly. However, LDS accuracy depends on the scanned wood properties (density and color), installation position of the sensor, and profile shape. It was found that evaluation of dark and high-density wooden surfaces was imperfect.Part of this work was presented at the 50th Annual Meeting of the Japan Wood Research Society, Kyoto, April 2000; and at the 51st Annual Meeting of the Japan Wood Research Society, Tokyo, April 2001     

Locating and identifying splits and holes on sugi by the laser displacement sensor

The split and the hole are two common defects on sugi (Cryptomeria japonica D.Don). They have a common feature in that they are associated with surface irregularities. We have developed a laser scanning system to detect the splits and the holes based on their thickness, which correlates spatially with the profile information. The displacements measured by the laser sensor were converted to pixel values to generate the displacement profile image. Both the splits and the holes manifested well in the image. A dedicated image-processing program written in Visual Basic has been developed. The defects regions were accurately located by the image processing. To identify the defects, eight recognition rules based on four features have been utilized. Furthermore, a method based on the pixel model was proposed to compute the area of the defect. The results indicated that the defects could be identified correctly, and the areas could be computed accurately using the pixels model.     

激光传感器定量测量木材表面粗糙度的研究

1IntroductionThe surface roughness of wood is one of the important parameters that can be used to operate the automatic woodcutting machinery,and alsoto evaluatethe quality of products . Withthe development of computertechnology,automaticmeasurement methods of the machined surface roughness have been proposed.Inrecent years ,newnon_contact methodshave been studiedto measure the roughness of machined surfaces .For example ,ultrasonic sensor was usedto measuringsurface roughness(Blessinget al.,…     

木材弹性模量自动检测的研究进展

论述了国内外木材弹性模量动态检测技术的研究现状与发展趋势．为今后国内发展木材力学性能的无损检测研究,自主研制实时木材强度分级生产线提供参考依据。     

木材纵横向切削过程中的声发射特性

研究了木材纵横向切削过程中的声发射特性。结果表明,切削方向与纤维方向之间的夹角,对切削过程中的声发射活动影响显著;当夹角为0°时声发射最强,90°时声发射最小;声发射强度随木材表面粗糙度的减小而逐渐增大。通过获得的试验数据,可进一步完善切削理论,指导木制品生产,监控产品质量。     

响应面法优化低共熔溶剂增加木材渗透性的工艺研究

为了探索一种绿色高效提高木材渗透性的方法,选取氯化胆碱（ChCl）与乳酸（LA）组成的低共熔溶剂（deepeutecticsolvent,DES）作为处理液,对轻木进行增渗处理。基于单因素试验结果,采用响应面优化法综合探究DES中氯化胆碱与乳酸的量比,即n（ChCl）∶n（LA）,DES体积分数和处理时间对木材渗透性的影响,以1h吸水增重率作为木材渗透性的评价指标,确定优化处理方案。试验结果表明,各因素对响应值的影响顺序为：处理时间>DES体积分数>n（ChCl）∶n（LA）;优化的工艺为：n（ChCl）∶n（LA）=1∶10、DES体积分数73%、处理时间6.6h、处理温度90℃,在此条件下处理材1h吸水增重率为416.34%,较未处理材提高了168.81%。场发射扫描电镜与压汞测试结果表明,纤维细胞壁结构保持完整,但在胞间层与细胞角隅处产生大量的微观孔隙,射线薄壁细胞与轴向排列的纤维间产生裂隙,孔隙率较未处理材提高了7.28%。     

刀具前角和切削深度对木塑复合材料切削性能的影响

采用硬质合金刀具切削2种木塑复合材料（聚乙烯与木粉的质量比,试材A为6∶4,试材B为3∶7）,研究刀具前角（2°、6°和10°）和切削深度（0.5、1.0和1.5mm）对试材切削力、切削温度和表面粗糙度的影响。结果表明：随着刀具前角从2°增大到10°,试材A的切削力、切削温度以及表面粗糙度,在精加工时（切削深度为0.5mm）分别降低了约41%、12%和17%;在粗加工时（切削深度为1.5mm）分别降低了约28%、21%和13%;随着切削深度从0.5mm增加到1.5mm（刀具前角为2°时）,试材A的切削力、切削温度以及表面粗糙度分别提高了约55%、17%和26%;试材B的变化趋势与试材A一致。实际生产时,建议在粗加工过程中,适当增大切削深度,来提高生产效率;但在精加工过程中,建议增大刀具前角并选取较小的切削深度,以此来提高木塑复合材料的表面加工质量。     

Toughening wood/polypropylene composites with polyethylene octene elastomer （POE）

Introduction Wood-Plastic Composite (WPC), due to its high stiffness, low density, low cost, environment friendly characteristics such as recyclablity and biodegradability, is gaining more and more interests, both in research and application. However, one…     

基于局部自相关函数熵的木材砂光表面粗糙度视觉检测方法

【目的】针对传统接触式粗糙度仪测量木材砂光表面粗糙度时存在的测量误差大、操作繁琐、在线检测困难等问题,提出一种基于局部自相关函数熵（LAEnt）的木材砂光表面粗糙度视觉检测方法,为木材砂光表面粗糙度测量提供高效、准确的非接触式检测手段。【方法】首先,阐明局部自相关函数熵检测表面粗糙度的机理,建立局部自相关函数熵算法;然后,采用正交试验法开展木材砂光试验,获取砂光表面图像和表面粗糙度;最后,探究砂带目数、砂带速度、气鼓轮进给量等因素对木材砂光表面粗糙度的影响,分析局部自相关函数熵和自相关函数熵（AEnt）与表面粗糙度的相关性,基于砂光表面的局部自相关函数熵和自相关函数熵数据,利用支持向量机（SVM）分别建立木材砂光表面粗糙度检测模型SVM-LAEnt和SVM-AEnt。【结果】砂带目数对木材砂光表面粗糙度的影响最显著,砂带目数与表面粗糙度呈强负相关,砂带速度和气鼓轮进给量对表面粗糙度的影响相对较小;局部自相关函数熵与木材砂光表面粗糙度呈显著线性相关,相关系数为0.973 3;且LAEnt特征提取效率显著优于AEnt,单张图像运算时间仅为AEnt的2.95%;基于SVM的建模结果表明,SVM-LAEnt模型拟合平均相对误差为2.56%（最大11.22%）,预测平均相对误差为5.13%（最大11.30%）,均优于SVM-AEnt模型（平均拟合相对误差8.98%,最大拟合相对误差20.68%,平均预测相对误差15.08%,最大预测相对误差31.13%）。【结论】局部自相关函数能够描述木材砂光表面的纹理特征和粗糙程度,在检测表面粗糙度时,采用局部自相关函数熵可更好地表征表面粗糙度。     

木材材色的定量表征

本文对木材材色的定量表征方法作了简要的评述,并就红种国产针、阔叶树材按CIE(1931)和CIE(1976)(L~*a~*b~*)做了详细的测定和分析。测定结果表明,表色参数(主波长、色纯度、亮度等)要具有可比性,所用的方法和测定条件必须相同。树种之间的色度坐标值的差异大于树种之内的差异。分析木材表面的反射率曲线,不同树种间的材色差异既反映在亮度上,也反映在色调上;但同一树种内的差异主要反映在亮度上。另外,树种之间与树种之内木材表面反射率与波长关系的曲线形状相似,趋向也一致,说明尽管材色的变异性很大,但有一定的规律性。因此采用了主成分分析法,简化表色空间,获得了综合材色参数的实验式;初步测试,实验式具有一定的可靠性与实用意义。为了能直观地表达材色,除了使用综合材色参数外,还给出了孟塞尔标号。     

基于Ru(bpy)2+3掺杂SiO2/漆酚复合物电化学发光传感器的制备及厚朴酚的检测

构建一种基于Ru(bpy)3^2+掺杂SiO2/漆酚复合物修饰电极的电化学发光传感器。利用厚朴酚对修饰电极电化学发光的增敏作用对厚朴酚进行检测。对影响修饰电极电化学发光的各因素进行了实验研究,优化了反应条件和各项测定参数。在最佳实验条件下,在8×10^-8~8×10^-5 g/L的质量浓度范围内,发光强度增量与其浓度呈良好的线性关系,检出限3.7×10^-8 g/L;对浓度为8×10^-6 g/L厚朴酚进行8次平行测定的RSD为3.5%。对合成样品中厚朴酚测定的回收率为99.8%~103%,表明传感器表现出良好的重现性和稳定性。     

基于改进YOLOv5s的木材表面缺陷检测模型

针对木材表面缺陷的复杂多样性和特征提取困难,提出一种基于改进YOLOv5s的木材表面缺陷（活节、死节、有裂缝节子和裂缝）检测模型。首先,在Backbone网络引入坐标注意力机制（coordinateattention,CA）增强每个通道之间的信息交互,然后采用混合空间金字塔池化（hybridspatialpyramidpooling-fast,HSPPF）结构减少信息损失,再使用GSConv卷积减少参数量,用改进的曲线高效交叉联合（curveefficientintersectionoverunion,CEIoU）作为训练时模型的损失函数,提升木材缺陷检测的准确性。试验结果表明,改进模型能够有效检测出木材表面缺陷,模型的平均精度均值（meanaverageprecision,mAP）为84.4%,比未改进之前提高了2%,检测速度达到73.9FPS,在模型参数量方面明显减少,同时优于其他主流模型,能够满足木材表面缺陷检测的要求。     

New cholinesterase inhibiting bisbenzylisoquinoline alkaloids from Abuta grandifolia

The phytochemical study of the stem bark and wood of Abuta grandifolia (Mart.) Sandwith led to the identification of four bisbenzylisoquinoline alkaloids (BBIQs), namely (R,S)-2 N-norberbamunine (1), (R,R)-isochondodendrine (2), (S-S)-O4″-methyl, Nb-nor-O6'-demethyl-(+)-curine (3), and (S-S)-O4″-methyl, O6'-demethyl-(+)-curine (4), together with the aporphine alkaloid R-nornuciferine (5), all obtained by countercurrent distribution separation (CCD) and identified on the basis of their spectroscopic data. Alkaloids 3 and 4 were new. All the isolated compounds were tested for acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitory activities. 1 was the most active against AChE, whereas 3 and 4 were the most potent against BChE. Interestingly, all tested alkaloids are more potent against BChE than against AChE. This selectivity of cholinesterase (ChE) inhibition could be important in order to speculate on their potential therapeutic relevance.