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1.
【目的】木材的基本密度在木材质量等级评定中起着重要的作用,是木材分流及精细化利用的重要依据。利用近红外光谱技术,实时监测木材性质,掌握木材性质的变化,为进一步制定和改善林木培育方法提供理论依据。【方法】借助树木生长锥对椴树活立木取样,以椴树样品基本密度真值和近红外光谱数据为输入,分别通过卷积平滑、一阶导数和二阶导数预处理方法来实现近红外光谱数据的预处理,建立了基于偏最小二乘法(PLS)的椴树木材基本密度的近红外估测模型。【结果】在350~2 500 nm波段范围内,一阶导数预处理的椴树木材基本密度模型是最优的,校正集相关系数为0.964 8,校正均方根误差为0.002 7,验证集相关系数为0.943 2,预测均方根误差为0.003 3。在对近红外光谱数据进行去噪优化处理,构建椴树木材基本密度模型后,在500~2 300 nm波段范围内,一阶导数预处理椴树木材基本密度模型依旧最优,其校正集相关系数为0.987 1,校正均方根误差为0.001 6,验证集的相关系数是0.948 6,预测的均方根误差是0.002 1。【结论】选择特定的预处理方法,结合样本特征,建立椴树木材基本密度模型,可以显著降低建模成本,提高模型预测精度,快速测定椴树木材的基本密度。  相似文献   

2.
采用近红外光谱技术对乙酰化大青杨和樟子松木材的增重率进行快速预测。在近红外波长780~2500 nm范围内,利用偏最小二乘法( PLS)建立木材横切面原始光谱及不同预处理(一阶导数、二阶导数、归一化处理和消噪)光谱乙酰化木材增重率数学模型,并进行比较分析。结果表明:乙酰化大青杨和樟子松木材分别选用归一化处理光谱和消噪光谱建立的增重率校正模型预测效果较好,预测模型相关系数( R)分别为0.90和0.70,预测标准差(RMSEP)分别为1.0072和1.3012,其中乙酰化大青杨木材增重率预测模型实测能力较佳,表明利用木材横切面近红外光谱建立的数学模型可以实现乙酰化木材增重率的快速预测。  相似文献   

3.
采用偏最小二乘法(PLS),建立近红外光谱快速预测栓皮栎木材气干密度的方法。以来自4棵栓皮栎木材不同径向部位的131个样品为研究对象,按GB/T1933—2009《木材密度测定方法》测定气干密度,并采集其近红外光谱,结果显示采用横切面光谱建立的模型效果最佳。通过梯度法选择多个建模样本集建立了多个PLS模型,模型的校正及预测相关系数均大于0.9。研究表明近红外光谱法快速预测栓皮栎木材气干密度具有可行性。  相似文献   

4.
采用近红外光谱结合化学计量学的方法,对桉木和相思木及其属间6种木材的判别分类进行了研究。首先采集了尾巨桉、尾叶桉L11、尾叶桉U6、蓝桉、马占相思、厚荚相思,共计86个样本的近红外光谱图,采用偏最小二乘法判别分析(PLS-DA)建立了桉木和相思木的分类模型,校正集和验证集的预测值与实际值之间的回归线基本重合,决定系数(R2)分别为0.99和0.97,模型效果较好,且对未知样本的识别正确率为100%。为了对属间的6种木材作进一步的判别,采用MSC和Savitzky-Golay平滑对4000~7500 cm-1光谱进行预处理后,结合主成分分析(PCA)建立判别模型,模型识别率和验证正确率均为100%。结果表明基于近红外光谱结合化学计量学算法可以对桉木和相思木的不同属进行快速鉴别。  相似文献   

5.
近红外光谱分析技术在木材机械性能检测中的研究进展   总被引:1,自引:0,他引:1  
近红外光谱技术具有快速、无污染、成本低廉、准确性高等优点,相比其他无损检测方法,被广泛应用于农业、医学、化工、造纸等各个领域。国内外许多科研工作者在木材材性分析和检测方面也作了大量的探索。本文主要介绍木材材性分析的重要性、近红外光谱技术的基本原理和特点,国内外林业科技工作者在辐射松、蓝桉、火炬松和粗皮桉等不同树种木材的抗弯强度、抗弯弹性模量、密度和压缩强度等物理力学性质检测方面所做出的贡献和取得的进展,通过介绍可以看出NIR技术具有很大的潜能,它可以快速、准确的获悉木材的性质,从而对木材进行科学合理的利用。  相似文献   

6.
【目的】木材基本密度在木材质量等级评定中具有重要作用,是木材分流及精细化利用的重要依据。【方法】以东北林区典型针叶树种为研究对象,结合近红外光谱技术,构建红松、落叶松、云冷杉木材基本密度近红外估测模型,分析比较了不同波段优选算法并进行了模型优化。研究采用竞争性自适应重加权法(CARS)、无信息变量消除法(UVE)和间隔偏最小二乘法(iPLS)对木材近红外光谱波段进行优化,基于卷积平滑算法对近红外光谱数据进行预处理,结合偏最小二乘法(PLS)建立针叶木材基本密度估测模型。依据相关系数(R)、均方根误差(RMSEC)等模型参数对模型效果进行评价,对比分析确定最佳波段优选方法,得到最优针叶木材基本密度近红外估测模型。【结果】利用CARS、UVE、i PLS的波段优化方法对近红外光谱波段的筛选,可以起到优化针叶木材基本密度模型的作用,减少参与建模的近红外光谱的波段变量数,明显提升模型的运算速度,使得模型准确度更高、稳定性更好;利用间隔偏最小二乘法结合偏最小二乘法(iPLS-PLS)进行波段优选的针叶木材基本密度模型效果最好,其模型校正相关系数为0.938 0,校正均方根误差为0.021 8,验证相关系数为0.8959,验证均方根误差为0.028 0。【结论】基于波段优选及模型优化构建东北林区典型针叶树种基本密度近红外估测模型,可以有效提高运算速度及估测精度,实现针叶材基本密度的快速、准确、无损估测,为针叶木材材性研究和森林培育提供了理论依据与技术支撑,有利于进一步实现木材的高效节约与精细化利用。  相似文献   

7.
近红外光谱技术及其在木材科学中的应用   总被引:15,自引:1,他引:15  
近红外光谱技术是一项新的木材无损评价方法,能够迅速、准确地对生长锥、固体木材或木粉等试样的性质进行全面无损评价,目前已广泛应用于木材性质预测、木材加工利用等方面的研究中,并为林木的定向培育、木材的遗传改良和高效利用提供技术支持。本文介绍了近红外光谱技术的基本原理及其主要应用,重点介绍了木材的近红外光谱技术及其在木材化学组成、物理力学性质、木材加工利用和木质复合材料等方面的研究成果及应用。  相似文献   

8.
近红外光谱技术在木材性质预测中的应用研究进展   总被引:2,自引:0,他引:2  
林木定向培育和木材资源的优化利用, 都需要对大量木材样本的性质进行快速测试.然而, 传统的测试方法成本高、效率低, 不能满足生产和科研的需要.近红外光谱技术是一种新的无损评价方法, 能够迅速、准确地对木材试样的性质进行预测.文中主要介绍了近红外分析技术的基本原理、特点以及在预测木材化学组成、物理力学性质、解剖性质等方面的研究进展.  相似文献   

9.
蒙古栎抗弯弹性模量多模型共识的近红外检测方法   总被引:1,自引:0,他引:1  
利用近红外光谱技术预测蒙古栎(Quercus mongolica)抗弯弹性模量(MOE),提出GN(global and neigh-borhood)样本优选与CPLS多模型共识的建模方法。选取近红外光谱谱段为900~1 700 nm,径切面和弦切面采集。首先,采用一阶导数与S-G卷积平滑相结合的方法进行数据预处理;然后,利用GN算法计算光谱样本间的全局和邻域马氏距离,实现蒙古栎MOE异常样本的剔除与校正集、预测集的自动划分;最后,融合具有多个成员样本子集的PLS模型,构建CPLS共识模型,取平均值作为最终预测结果。实验采用135个300 mm×20 mm×20mm的无疵小试样为样本,剔除异常样本12个,并选取其中78个为校正集样本,45个为预测集样本。结果表明,一阶导数处理能够消除光谱背景平缓区域干扰,S-G能消除小峰值无关吸收峰的影响;GN样本优选与CPLS结合的建模方法,预测相关系数为085,相对分析误差(RPD)为193,预测效果比传统PLS建模更好,且稳定性有所提高,但该改进模型方法的RPD依然小于25,因此,可做初步分析,准确地进行定量预测依然存在局限性。  相似文献   

10.
应用便携式近红外光谱仪快速检测制浆材时,如果能实现同系列不同型号仪器之间分析模型共享,将极大降低仪器建模和维护成本。为实现混合木材木质素含量的近红外分析模型从1台主机向2台不同型号从机的模型传递,收集了5种常见制浆材的82个原木样品,经粉碎预处理后分别在3台便携式光谱仪上采集其近红外光谱信号,采用差谱、光谱的平均差异和光谱间的欧氏距离等方法,定量表征了仪器间的信号差异,分析并讨论了差异产生的原因。利用偏最小二乘回归建立了样品主机近红外光谱与木质素含量的关联模型,再分别采用斜率截距、直接校正和典型相关分析算法进行主机与两台从机间的模型传递,比较了模型传递前后预测精度。结果表明,便携式光谱仪间的差异多为非线性,且不同型号从机光谱仪间差异更为复杂。尽管主机向同型号的从机模型传递效果更优,但经直接校正算法和典型相关分析算法传递后两台不同型号从机预测相关系数均大于0.98、预测相对标准偏差均大于3、预测标准偏差均小于1.1%,可实现木材木质素含量的近红外光谱分析模型在3台便携式光谱仪间的传递。该研究结果对于不同型号便携式光谱仪分析模型共享具有重要意义。  相似文献   

11.
试验以采集的100份桉树不同组合杂交子代的木芯及木粉样品作为研究对象,以常规方法测定所取木材样品的木材密度、纤维长度和纤维宽度并用 Polychromix 手持式近红外仪采集了自然风干状态木粉的近红外光谱信息。光谱数据的处理及建模用 Unscrambler 9.7软件完成。建模结果显示:木材密度、纤维长度和纤维宽度的预测精度均可达90%以上。建模过程中,木材密度较纤维长度和纤维宽度所需的校正样本集数量要多,说明要达到一定的预测精度,纤维长度和纤维宽度其所建模型的预测范围会相应变小。  相似文献   

12.
The visible and near infrared (NIR) (350-2500 nm) spectra and the MOE of 438 small clear wood samples from Chinese fir, eucalyptus and poplar 72 were measured. Using partial least-square (PLS) modeling, the NIR spectra could be used to predict MOE and MOR of the clear-wood samples from Chinese fir and eucalyptus solid wood. NIR spectra could only be used to Predict MOE but not MOR of poplar clear-wood samples. With the exception of MoR of poplar clear-wood samples, the correlations between NIR and the mechanical properties are very strong, and the calibration and test correlation coefficients are both above 0.80.  相似文献   

13.
The aim of this study was to investigate convenient spectroscopic evaluation method of Para rubber quality. Ultra violet–near infrared (UV–NIR 370–1085 nm) spectra of latex were measured in transmittance mode. Calibrations for total solid content (TSC) and dry rubber content (DRC) were developed using spectral data set with aid of partial least square regression analysis using 57 samples. UV–NIR spectra of latex provided good regression models between measured and predicted values of TSC and DRC with determination coefficient for cross-validation of 0.96 and 0.97, respectively. The ranks were 2 and 1, respectively. This study suggests high accuracy in-line quality control of latex using UV–NIR spectroscopy. The long wavelength NIR spectra of bark were scanned to check the feasibility of on-site evaluation of latex quality by measuring the NIR spectra of standing tree. From the observation of near infrared spectra, it was shown that there was more latex signal in outer part of wood bark than in inner part of wood bark. This result suggests that the focal point should be on the outer part of bark to get the signal of latex when we measure the spectra of standing tree.  相似文献   

14.
Five Populus x euramericana wood samples representing three different sites were selected and nearinfrared (NIR) spectra were obtained. For these sections, basis weight, brightness and three mechanical properties (tensile index, tearing index and bursting index) were determined by standard analytical methods. Calibrations were developed for each paper property using the NIR spectra, data on paper properties, using partial least squares (PLS) regression. The results show that the coefficients of correlation of calibration and validation for basis weight were 0.8824 and 0.8299, respectively; the standard error of calibration (SEC) and prediction (SEP) were 1.150 and 1.170, respectively. In testing for brightness, the correlation coefficient of calibration was 0.9621 and for validation 0.9612, while the SEC and SEP were 0.997 and 1.300, respectively; paper brightness and NIR spectroscopy were highly correlated. NIR spectroscopy can be used to predict tensile, tearing and bursting indices of paper samples rapidly. We found that the paper properties fitted by NIR and GB methods were highly correlated. The coefficients of correlation of calibration and validation for basis weight exceeded 0.8000, while the SEC and SEP were very small. These results reveal that the five paper properties of Populus x euramericana and those predicted by the NIR model were highly correlated. We conclude that the NIR models can be used for the prediction of paper properties.  相似文献   

15.
木材顺纹抗压强度是评价木材力学性能的重要指标,而传统测量方法操作复杂、精确度低。以桦木为例,提出基于近红外光谱技术(NIR)的SEPA-VISSA-RVM木材顺纹抗压强度模型,实现对其更加精确的预测。试验选取100个木材试件,在900~1700 nm近红外光谱波段上采集数据并测量抗压强度真值;然后采用卷积平滑(SG)方法进行光谱预处理;使用采样误差分布分析(SEPA)作为变量空间迭代收缩算法(VISSA)的改进策略进行特征波长优选;最后通过粒子群优化算法(PSO)优化核函数参数并建立相关向量机(RVM)的预测模型。试验表明:在特征波长优选方面,以偏最小二乘法(PLS)建模为基础的SEPA-VISSA方法,其预测决定系数为0.9593,预测均方根误差为2.8995,相对分析误差为3.0256,光谱变量数由512减小到111个,占总波长的22%,均优于VCPA、CARS和VISSA算法;在建模预测方面,以SEPA-VISSA所选波长为基础的RVM模型,PSO优化的拉普拉斯(Laplacian)核函数的核宽度为10.4043,决定系数为0.9449,预测均方根误差为2.0432,相对分析误差为4.2936,预测效果优于PLS和SVR。因此,基于近红外光谱的SEPA-VISSA-RVM建模能够实现对桦木顺纹抗压强度更准确和稳定的无损检测。  相似文献   

16.
This work was undertaken to investigate the feasibility of using near infrared spectroscopy (NIR) and partial least squares regression (PLS) as a tool to characterize the basic wood properties of Norway Spruce (Picea abies (L.) Karst.). The wood samples originated from a trial located in the province of Västerbotten in Sweden. In this trial, the effects of birch shelterwoods (Betula pendula Roth) of different densities on growth and yield in Norway spruce understorey were examined. All Norway spruce trees in each shelterwood treatment were divided into three growth rate classes based on diameter at breast height (1.3?m) over bark. Five discs were cut from each tree (i.e. from the root stem, and at 20%, 40%, 60%, and 80% of the total height). The discs from 40% tree height were used (i.e., where the largest variations in annual ring widths and wood density were found). A total of 27 discs were selected. The discs were used for measuring annual ring widths, wood density, average fiber length and the fiber length distributions. Milled wood samples prepared from the discs were used for recording NIR spectra. PLS regression was used to generate prediction models for the wood properties (Y-matrix) and NIR spectra (X-matrix) as well as between the wood properties (Y-matrix) and the fiber length distributions (X-matrix). One set of models was generated using untreated spectra and fiber length distributions. For a second set of models the structure in the X-matrix, which was orthogonal to the matrix described by the wood properties, was eliminated using a soft target rotation technique called orthogonal signal correction (OSC). The PLS model obtained using “raw” untreated NIR spectra and fiber length distributions had a poor modeling power as evidenced by the cumulative Q2 values. For the PLS models based on untreated NIR spectra the cumulative Q2 values ranged from a minimum of 16% (wood density) to a maximum of 46% (no. of annual rings). Orthogonal signal correction of the X-matrix (NIR spectra or fiber length distributions) gave PLS models with a modeling power corresponding to cumulative Q2 values well in excess of 70%. The improvement in predictive ability accomplished by the OSC procedure was verified by placing four of the 27 observations in an external test set and comparing RMSEP values for the test set observations without OSC and with OSC.  相似文献   

17.
  • ? Methods based on near infrared spectroscopy used to assess wood properties are susceptible to variations in physical parameters (temperature, grain size, etc.). As wood is a hygroscopically sensitive material, we studied the effects of moisture on near infrared absorbance and calibration to accurately determine the application potential of this technique under routine.
  • ? A collection of Eucalyptus urophylla × E. grandis hybrid wood pieces were analysed to obtain reference calibration of polyphenol contents in wood extracts via NIR spectra acquired under constant moisture conditions. Other specimens from the same source were assessed to obtain spectra for eight moisture contents spanning a broad variation range. The effects of moisture on absorption and on estimates based on a reference model were analysed.
  • ? An increase in moisture content prompted a rise in near infrared absorption over the entire spectrum and for water O-H absorption bands. The polyphenol content estimates obtained by assessing specimens against the reference calibration at variable moisture contents revealed prediction bias. Five correction methods were then tested to enhance the robustness relative to moisture.
  • ? In-depth calibration and external parameter orthogonalization (EPO) were found to be the most efficient methods for offsetting this factor.
  •   相似文献   

    18.
    The use of calibrated near infrared (NIR) spectroscopy for predicting the chemical composition of Pinus taeda L. (loblolly pine) wood samples is investigated. Seventeen P. taeda radial strips, representing seven different sites were selected and NIR spectra were obtained from the radial longitudinal face of each strip. The spectra were obtained in 12.5 mm sections from pre-determined positions that represented juvenile wood (close to pith), transition wood (zone between juvenile and mature wood), and mature wood (close to bark). For these sections, cellulose, hemicellulose, lignin (acid soluble and insoluble), arabinan, galactan, glucan, mannan, and xylan contents were determined by standard analytical chemistry methods. Calibrations were developed for each chemical constituent using the NIR spectra, wood chemistry data and partial least squares (PLS) regression. Relationships were variable with the best results being obtained for cellulose, glucan, xylan, mannan, and lignin. Prediction errors were high and may be a consequence of the diverse origins of the samples in the test set. Further research with a larger number of samples is required to determine if prediction errors can be reduced.  相似文献   

    19.
    Mechanical properties and the visible and near infrared (NIR) (350–2500 nm) spectra obtained from longitudinal and transverse face of 155 small clear wood samples of Chinese fir (Cunninghamia lanceolata) were measured, and 103 of them were used to establish calibration models. Calibrations were tested on an independent set (52 samples). Differences between calibrations developed by using the longitudinal and transverse face were small. The calibrations developed by using NIR spectra (350–2500 nm) collected from transverse face were slightly inferior to those developed by using NIR spectra collected from longitudinal face. When reducing the spectral range to between 780 and 1050 nm, the calibrations developed by using NIR spectra collected from longitudinal face were slightly inferior to those developed by using NIR spectra collected from transverse face, and reducing the spectral range causes no decrease in the quality of the models developed using NIR spectra collected from transverse face. Partial lease square (PLS) modeling and test showed that calibrations developed using the visible and NIR spectra from transverse and longitudinal faces and calibrations developed by using the reducing spectral range (780–1050 nm) from the transverse face were moderate, and have a RPD range from 1.51 to 1.90. It is concluded that NIR spectroscopy can be used as an initial screening. __________ Translated from Journal of Northwest Forestry University, 2007, 22(5): 149–154 [译自: 西北林学院学报]  相似文献   

    20.
    Near infrared (NIR) spectroscopy (500 nm–2400 nm), coupled with multivariate analytic (MVA) statistical techniques, have been used to predict the chemical and mechanical properties of solid loblolly pine wood. The samples were selected from different radial locations and heights of three loblolly pine trees grown in Arkansas. The chemical composition and mechanical properties were measured with traditional wet chemical techniques and three point bending tests, respectively. The microfibril angle was measured with x-ray scattering. These chemical and mechanical properties were correlated with the NIR spectra using projection to latent structures (PLS) models. The correlations were very strong, with the correlation coefficients generally above 0.80. The mechanical properties could also be predicted using a reduced spectral range (650 nm–1150 nm) that should allow for field measurements of these properties using handheld NIR spectrometers.  相似文献   

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