不同数量传感器下云杉模拟缺陷材应力波成像规律探讨

以云杉原木圆盘为对象,研究不同面积、不同轮廓形状的空洞缺陷及用不同数量传感器情况时应力波成像技术检测缺陷图像与实际缺陷的关系.结果表明:应力波成像系统可以直观显示木材内部缺陷,其检测精度与空洞等实际缺陷面积和被测木材的截面积比率、使用传感器数量及空洞等缺陷轮廓形状有关;当空洞实际面积与被测木材截而积比从1.6％上升到25.0％时,应力波成像系统显示缺陷图像面积与实际缺陷面积相对误差从22.6％下降到9.7％;成像用传感器数量在6～24个之间时,应力波成像系统均能显示空洞等缺陷的存在,但成像用传感器的数量会影响检测精度;缺陷轮廓形状对应力波成像有一定影响,缺陷面积一定时,狭长形缺陷容易被检出,近圆形缺陷检测相对误差小.     

传感器数量对应力波检测原木内部缺陷精度的影响

木材无损检测技术是高效利用木材的方法之一.该文阐述了应力波法检测木材缺陷的原理,分析了传感器数量对图像的拟合度和误差率两个指标的影响.结果表明,当原木直径在20～40cm范围内时,若需对原木缺陷进行精确测量,要求图像拟合度接近90%和误差率在0.1左右时,至少需12个传感器才能满足要求;当不需要对原木缺陷进行精确测量,只需确定缺陷的大致位置时,宜选用10个传感器进行测量;当仅仅需要判断原木是否存在缺陷时,选用6个传感器就能满足要求.图3表4参8.     

Effect of sensor quantity on measurement accuracy of log inner defects by using stress wave

Wood nondestructive testing （NDT） is one of the high efficient methods in utilizing wood. This paper explained the principle of log defect testing by using stress wave, and analyzed the effects of sensor quantity on defect testing results by using stress wave in terms of image fitting degree and error rate. The results showed that for logs with diameter ranging from 20 to 40 cm, at least 12 sensors were needed to meet the requirement which ensure a high testing accuracy of roughly 90% of fitness with 0.1 of error rate. And 10 sensors were recommended to judge the possible locations of defects and 6 sensors were sufficient to decide whether there were defects or not.     

基于高斯-马尔可夫随机场的木材表面缺陷类型识别

为了识别死节、活节和虫眼三种木材表面缺陷类型,本文采用高斯-马尔可夫随机场模型提取木材表面缺陷图像的纹理参数,结合缺陷区域的矩形度和伸长度两个几何特征,形成14维特征向量.设计三层BP神经网络来识别缺陷的类型.试验表明,三种缺陷的整体识别正确率达到96.67％,验证了该方法的有效性.     

基于无人机影像的华南农业大学不同下垫面地表降温效益研究

以华南农业大学校园为研究对象,通过携带热成像传感器的无人机,获取了校园中心区域不同下垫面的热成像图片,分析不同下垫面的日地表温度变化,探讨其地表降温效果的影响因素。结果表明,一天中总体降温幅度从大到小的下垫面依次为水体、林地、乔-灌-草绿地/乔-草绿地、道路、建筑,水体和绿地尤其是林地的地表降温效益显著。林地的周长为0~600 m,面积为0~7000 m^(2)时,与林地的地表降温幅度呈正相关;林地的周长面积比、景观形状指数、分维数与地表降温幅度呈负相关,林地形状和边缘越简单,形状接近圆形,地表降温效益越好。     

基于人工神经网络的马尾松毛虫发生量预测模型的研究

运用人工神经网络的原理和方法，根据相关系数法和逐步回归法分别选取与马尾松毛虫有虫面积，虫口密度，虫株率相关关系密切的气象因子作为样本的输入特征，分别建立马尾松毛虫有虫面积，虫口密度，虫株率与气象因子的BP网络模型。结果表明，所建立的各BP模型，具有令人满意的拟合精度和预测精度。当隐含层神经元个数为15个，预报因子数为8个时，2组预留有虫面积的2a平均预测误差为3.15%，虫口密度BP模型的隐层神经元个数为8个，预报因子数为6个时，预留样本的平均预测误差为5.91%，虫株率BP模型的隐层神经元个数为4个，预报因子数为5个时，预留样本的平均预测误差为10.65%。     

基于形态学重构的实木地板缺陷分割方法研究

针对传统区域生长方法中,由于噪声种子存在及种子点单步邻域搜索所导致的分割时间长、检测精度低的问题,提出基于形态学重构的实木地板在线缺陷分割方法。方法首先定义不同阈值下的两幅模版图像,其中低阈值图像用于种子优化,高阈值模版用作种子膨胀生长;通过定义腐蚀终止准则,完成低阈值图像下的缺陷骨架提取;运用"去毛刺"操作,最终实现缺陷骨架内的种子点优选;然后,运用测地膨胀,结合高阈值模版,完成板材缺陷区域的快速生长;最后,应用"孔洞填充"、"去毛刺"优化边缘,实现缺陷目标的提取。实验分别在像素512*512、256*256和128*128下进行,通过与传统区域生长方法的比较,表明方法实现了缺陷区域的准确分割,分割速度与精度能够满足地板在线分选要求。     

手杖式测树仪立木树高量测研究

【目的】树高是森林经营决策中最重要的一个参量,常用于估计森林生长、年龄、材积、生物量和碳储量等立木参数,其精度对立木质量的评价及森林生长的预测分析影响重大。为解决传统的树高量测仪器移动不便,测量周期长,人力耗损大等问题。【方法】以近景摄影测量为基础,构建了一种以登山杖绑定安卓智能手机为测量平台的便携、快捷的树高测量装备;针对立木生长环境有无坡度,拍摄是否产生倾角等情况建立了树高量测模型。在手机环境下,研制了立木树高测量软件APP。APP采用上下分屏技术,利用手机成像系统以及坐标系转换,使屏幕与待测立木建立关联,从而自动解算立木的深度信息;结合手机内部方向传感器的强大性能,单站作业可实时获取树高估计值。在北京市平谷区红石门村选取不同坡度的307株立木作为研究对象,使用该装备分别在上坡位和下坡位对其进行量测,将测定结果与全站仪多次量测求得的平均值进行对比分析。【结果】结果表明,树高估计值平均绝对误差为0.21 m,平均相对误差为2.11%,整体精度达到97.89%。当处于下坡位观测时,树高估计值平均绝对误差为0.11 m,平均相对误差为1.16%,树高精度高达98.84%。当处于上坡位观测时,树高估计值平均绝对误差为0.32 m,平均相对误差为3.07%,树高精度达到96.93%。智能手机倾斜角较大时,精度达到95.19%,智能手机倾斜角较小时,精度高达99.03%,说明手杖式测树仪观测时所产生倾角越小,精度越高。量测同一株立木时,下坡位观测的精度优于上坡位。【结论】此装备的研发满足国家森林资源连续清查中的测量精度要求,且装备成本低、灵活性强、不依赖其他设备获取深度信息、携带方便、具有较高利用价值,未来可作为森林资源调查树高测量装备。     

MICROCOMPUTER PROCESSING THE PHOTOGRAPH OF TIMBER WITH HOLE KNOTS

THRESHoLDWhenthetimberswiththeho1eknotsarepassedthesystemofX-raynon-de-structiveinvestigation,thesimulatednu-meralsfigureoftheholeknotsappearinthemonitor.Thesimulatednumeralsfigureisshownintablel.Meanwhilethehistogramofthisfigurearedoublepeakcertainly.Inordertoidentifytheedgeoftheholeknotswithnakedeyeandcarryoutautomatictreatment,Wetakethebinaryva1uetreatmentforthefigure'Thechoos-ingthresholdisaveryimportantpartinthebinaryvaluetreatment.Howtochooseasuitablethreshold?Weshouldpaymuchattenti…     

基于红外热像技术的木材内部缺陷检测的研究

运用红外热像技术对加工有孔洞的两个毛赤杨方材作内部缺陷无损检测。通过实验得出用红外热像仪准确检测该方材内部缺陷的条件：①采用双面法检测;②在热源距试样25cm的前提下,加热试样20min左右;③若缺陷在中间,则试样中央标识线上最高温度以下0．4℃范围可以准确反映出缺陷的大小,若在一倒则最高温度以下0．5℃范围可以准确反映缺陷的大小。在上述条件下应用此方法检测方材内部缺陷的误差范围为±5mm,相对误差为12．5％,说明使用红外热像糟术舯太耕肉都按陷拂轩枪测善可行的。     

Estimating stand transpiration in a Eucalyptus populnea woodland with the heat pulse method: measurement errors and sampling strategies

Sap flow measurement techniques, such as the heat pulse (compensation) method, are practical means for estimating the water use of individual trees and are often the only reasonable alternative for measuring forest and woodland transpiration in complex heterogeneous terrain. The need to scale estimates of water use from a sample of individual stems to a stand (population) of known area may be satisfied by applying scalars of flux based on tree size or domain. We estimated the aggregate errors in applying the heat pulse technique to the estimation of stand transpiration in a poplar box (Eucalyptus populnea F.J. Muell.) woodland in southeastern Queensland, Australia, by a combination of precision analyses, experimental validation and Monte Carlo simulations of sampling errors. Errors in sap flux density measurements were approximately 13%. The potential error in the flux estimates for individual stems with stratified sampling of sap flux density with depth and bole quadrant based on four sensors was an additional 25%. Conducting wood area, diameter at 1.3 m, leaf area and domain based on Ecological Field Theory all proved excellent scalars of flux at the stand level. With a sample size of six trees stratified by diameter, coefficients of variation in scaling to the stand level were approximately 5% for any of these scalars. The greatest potential source of error in estimating stand transpiration by the heat pulse method was in the measurement of the fluxes of individual stems; scaling these measurements to a homogeneous stand of trees involved less uncertainty.     

油松针叶面积估计模型及比叶面积的研究

叶面积和比叶面积是植物生长过程中的重要参数.本研究基于河北木兰围场实测油松数据,通过winSEEDLE种子和针叶图像分析系统获得油松522个单个针叶的表面积LA、针叶长度L、针叶宽W、针叶周长P,分别建立了以针叶长、针叶宽、针叶周长等形状属性为自变量的叶面积估计模型和以针叶干质量为自变量的叶面积估计模型.用总相对误差、平均相对误差、平均相对误差绝对值、均方根误差、预估精度5个统计量来检验模型的误差和拟合优度,经检验模型LA=-2.761 +0.464 L +6.608W和LA =1.345 +0.501X分别为这两种模型中最好,X为针叶干质量.通过对算术平均法、比估计法、最小二乘法3种方法的比较,得到油松的比叶面积为7.08 m2 ·kg-1.本研究为油松叶面积的估计提供了一个简单可靠的方法.     

基于叶形分类的淡竹叶面积预测模型研究

竹子叶片极易卷曲的特性增加了叶面积测量的难度，本研究致力于建立淡竹快速、便捷、准确测量叶片面积的模型。通过对淡竹叶片的形态特点进行分类，将叶面积仪测量面积作为对照，利用叶长、叶宽数据和扫描实际叶面积进行建模，并采用均方根误差、残差平方和、预测精度来检验模型的精度。结果表明：1）根据淡竹叶片的长宽比将叶片分为3类：长宽比≤ 5.770，5.770<长宽比≤ 6.682，长宽比>6.682；2）形态学指标相关性显示，淡竹叶片长宽积与叶面积相关性最大，相关系数为0.990；3）以叶片长宽的积建立了叶形分类拟合模型，模型的预测精度为97.11%，其预测结果优于整体拟合和叶面积仪测量结果。研究提出的淡竹叶片面积分类拟合模型可快速、准确地预测叶片面积，解决了淡竹叶片面积测量难的问题，为淡竹相关的生态学研究和经营生产提供了基础。     

文冠果表型性状的相关性及主成分分析

文冠果种子产量低,这是制约其大力开发与利用的瓶颈。为给文冠果优良品种的选育和文冠果资源评价和利用提供科学依据,对新疆维吾尔自治区奇台县的160株文冠果单株的种子质量、结果个数、果实质量等21个性状指标进行了调查,并采用变异分析、相关性分析和主成分分析等分析方法,对影响其产量的主要因素进行了探讨。变异分析结果表明:被调查的160株文冠果单株各性状指标间均存在明显差异;其中,单株结果个数的变异系数最大,为82.98%;叶密度的变异系数最小,为8.77%。相关性分析结果表明:单株种子质量与树高、地径、冠幅、果实纵径、种子长、单果种子质量、单株结果个数、单株果实质量、百果质量、百粒种子质量、叶长、叶宽、叶面积、果皮厚度、单果种子粒数及种子宽之间均存在显著正相关。主成分分析结果表明:从21个性状指标中提取了7个主成分,即单果产量、单株产量、果实产量、叶形、种形、果形、树形这7个因子,其累积贡献率达74.693%;依据各主成分贡献率的大小,在育种中可选择单果种子质量大、单株结果个数多、单株果实质量大、叶长、种子长、果纵径长、冠幅大的单株作为优良高产植株。     

Feature extraction of wood-hole defects using wavelet-based ultrasonic testing

The primary bottleneck to extracting wood defects during ultrasonic testing is the accuracy of identifying the wood defects. The wavelet energy moment was used to extract defect features of artificial wood holes drilled into 120 elm samples that differed in the number of holes to verify the validity of the method. Wavelet energy moment can reflect the distribution of energy along the time axis and the amount of energy in each frequency band, which can effectively extract the energy distribution characteristics of signals in each frequency band; therefore, wavelet energy moment can replace the wavelet frequency band energy and constitute wood defect feature vectors. A principal component analysis was used to normalize and reduce the dimension of the feature vectors. A total of 16 principal component features were then obtained, which can effectively extract the defect features of the different number of holes in the elm samples.     

Application of modal analysis by transfer function to nondestructive testing of wood I: determination of localized defects in wood by the shape of the flexural vibration wave

This study was intended to detect nondestructively some defects such as knots and grain deviations in wood using modal analysis. The shapes of flexural vibration waves at the first mode generated by the tapping of wooden beams were determined using the transfer function. The wave shapes obtained were compared with the theoretical wave shape for a uniform material; and the possibility of detecting defects in wood was examined. The results are summarized as follows: (1) The shapes of flexural vibration waves at the first mode of wooden beams free of defects coincided almost completely with the theoretical wave shape. (2) The shapes of flexural vibration waves of wooden beams containing defects such as knots clearly differed from the theoretical wave shape, especially near the defect. (3) Based on these results, it should be possible to detect the presence of defects and to determine their location in wood.Part of this report was presented at the 49th Annual Meeting of the Japan Wood Research Society, Tokyo, April 1999. This article is translated from the Japanese edition published inMokuzai Gakkaishi Vol. 47, No. 4, 1988     

Classification of defects in cork planks using image analysis

Summary Image analysis techniques were used on cork surfaces of transverse sections of planks and multivariate analysis was applied to differentiate pores (lenticular channels) from important defects such as nail (horizontal and vertical) and insect galeries. The discriminant analysis showed that the variables area, perimeter, specific length and width, diameters in the radial and in the tangential direction, as well as the optical density could be combined in three discriminant functions that could make the classification. Defect specific classification functions gave good results for the automatic classification of pores, insect galeries and horizontal nail (error <10%), and acceptable for vertical nail (20% error).     

杨树速生丰产林天牛危害的调查与防治试验

杨树(Populusspp )经过多年人工选育栽培形成了大量的品系,同时杨树也是感染病虫害较多的一个树种之一,在速生丰产林的营造过程中如果不注意病虫害的防治,多年造林成果可能会毁于一旦。在杨树病虫害中,蛀干类害虫光肩星天牛(AnoplophoranobilisGanglbauer)、黄斑星天牛(AnoplophoraglabripennisMotsch )以危害主干,隐蔽性强,繁殖率高而成为杨树速生丰产林建设的主要防治对象[1～4]。1　试验地概况试验地位于宁夏中卫县赛金塘治沙林场,地处黄灌区与北部沙漠交界的地区,海拔1211 4～1221 6m,积温较高,日照充足,光能丰富,干旱少雨,蒸腾强烈,…     

生长调节剂对欧洲鹅耳枥水培生根的影响

【目的】筛选适合欧洲鹅耳枥水培生根的植物生长调节剂处理方法,并讨论欧洲鹅耳枥水培苗与土培苗的差异,为欧洲鹅耳枥生根机制研究及进一步生理生化研究提供理论基础。【方法】以欧洲鹅耳枥硬枝枝条为试材,研究不同植物生长调节剂种类、质量浓度和处理时间对生根率、愈伤组织率、存活率、平均根数、平均根长、皮部生根枝条率、皮部平均根数、切口平均根数的影响及生根过程中的指标动态,并研究水培苗与土培苗形态、生理、根显微结构的区别。【结果】欧洲鹅耳枥水培既存在切口生根,也存在皮部生根,可通过不同的生长调节剂来诱导不同的生根方式。欧洲鹅耳枥水培生根最佳的生长调节剂处理方式为800 mg/L ABT1处理1 h,在此条件下,欧洲鹅耳枥枝条生根率60.14%,愈伤组织率75.25%,存活率96.67%,其生根方式主要为切口生根,生根数量较少但粗壮,大小一致,便于标准化生产;采用1 200 mg/L NAA浸泡1 h的处理方式,获得的水培苗全部为皮部生根,生根数量多但较细弱,发根位置不定,有大量根很长,不适合移植土壤但适合水培观赏根系。水培苗根含水量是土培苗根含水量的1.90倍,水培苗的根系活力显著低于土培。水培根系呈白色至浅褐色,基本没有木质化,不定根长且直,二级根少且短,缺少三级根,缺少角质层,且皮层的薄壁细胞体积大、形状不规则、排列疏松,维管柱占根横截面积比例较小。【结论】欧洲鹅耳枥水培既存在切口生根,也存在皮部生根,可通过不同的生长调节剂来诱导不同的生根方式。欧洲鹅耳枥水培苗与土培苗相比,根系形态及显微结构都发生明显变化。     

基于Faster R-CNN的实木板材缺陷检测识别系统

我国木材资源有限,为了提高木材的利用率,采用机器视觉来实现木材缺陷快速而稳定的检测,不仅可以克服人工检测的低效率和木材缺陷识别的低准确率,而且对提高木材加工企业的智能化水平具有重要意义。为了高效、快速、准确地进行无损检测,采用深度学习方法,建立了一种基于快速深度神经网络的实木板材缺陷识别模型。首先采用Resnet V2结构对采集到的实木板材缺陷图像进行特征提取,然后应用该模型对节子、孔洞等实木板材缺陷进行训练学习,最后构建了Faster R-CNN检测框架,并使用tensorflow开发平台对节子、孔洞等实木板材缺陷进行预测输出。具体选取了2 000块杉木样本,通过旋转对原始的实木板材图像进行数据扩充,扩充后图像的80%作为训练集,20%作为验证集来进行仿真。仿真结果表明,该模型对实木板材节子缺陷检测正确率为98%,对实木板材孔洞缺陷检测正确率为95%,验证了将深度学习算法应用于实木板材缺陷检测中的有效性。