蒙古栎木材MOR与MOE的近红外光谱预测模型分析
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摘要
蒙古栎是重要的结构用材,对其抗弯强度(MOR)与抗弯弹性模量(MOE)进行快速准确的无损检测是具有工程应用价值的科学问题。为实现蒙古栎木材MOR与MOE的快速无损检测,以900~1 700 nm的便携式近红外光谱仪为检测手段,提出一阶导数与S-G卷积平滑处理相结合的数据预处理方法,采用木材径切面与弦切面2个切面近红外光谱的平均值作为建模数据,利用Isomap-PLS算法建立预测模型估计木材的MOR、MOE。试验采用135个300 mm×20 mm×20 mm的无疵小试样为样本,其中90个组成校正集,45个组成预测集。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卷积处理能滤除高频噪声;采用径切面与弦切面光谱的平均值,比采用单一切面建模效果好,校正相关系数大,校正标准误差小;Isomap-PLS模型优于PLS、i PLS、MWPLS、CSMWPLS、Bi PLS、LLE-PLS模型,MOR预测相关系数为0.89,预测标准误差(SEP)为11.43,相对分析误差(RPD)为2.55>2.5;MOE预测相关系数为0.88,SEP为2.73,RPD为2.58>2.5。可见,所建近红外模型可以完成蒙古栎无疵木材快速有效的无损检测。
The detection of modulus of rupture( MOR) and modulus of elasticity( MOE) of Quercus mongolica as an important structural material is of scientific significance with engineering application value. In order to undertake nondestructive detection rapidly,a portable near infrared spectrometer with 900- 1 700 nm is used. Firstly,the first derivative and S-G convolution smoothing method was implemented for signal pre-processing; and then the model dataset was built by the average value of two sections,i. e.,radial plane and tangent plane; finally,the MOR and MOE were estimated by using the isometric mapping partial least squares( Isomap-PLS) algorithm. The experiments used 135 small clear wood samples whose size was 300 mm × 20 mm × 20 mm,of which 90 were calibration samples and 45 were prediction samples. The experimental results show that the first order derivative is able to eliminate the spectral background and high frequency noise,and the average value of S-G can be used to filter out the high frequency noise. What's more,the average section model is better than the single section,which owns a higher correlation and lower standard error. Compared with partial least squares( PLS),interval partial least squares( iP LS),moving window partial least squares( MWPLS),changeable size moving window partial least squares( CSMWPLS),back interval partial least squares( BiP LS) and locally linear embedding partial least squares( LLE-PLS),Isomap-PLS is the best,whose prediction correlations of MOR and MOE are 0. 89 and 0. 88 respectively,standard errors of prediction( SEP) are 11. 43 and 2. 73 respectively,ratios of performance to standard deviation( RPD) are 2. 55 and 2. 58 respectively,and RPD is more than 2. 5. Hence,this near infrared model can be used to complete the fast and effectivenondestructive testing of Q. mongolica wood with no defect.
The detection of modulus of rupture( MOR) and modulus of elasticity( MOE) of Quercus mongolica as an important structural material is of scientific significance with engineering application value. In order to undertake nondestructive detection rapidly,a portable near infrared spectrometer with 900- 1 700 nm is used. Firstly,the first derivative and S-G convolution smoothing method was implemented for signal pre-processing; and then the model dataset was built by the average value of two sections,i. e.,radial plane and tangent plane; finally,the MOR and MOE were estimated by using the isometric mapping partial least squares( Isomap-PLS) algorithm. The experiments used 135 small clear wood samples whose size was 300 mm × 20 mm × 20 mm,of which 90 were calibration samples and 45 were prediction samples. The experimental results show that the first order derivative is able to eliminate the spectral background and high frequency noise,and the average value of S-G can be used to filter out the high frequency noise. What's more,the average section model is better than the single section,which owns a higher correlation and lower standard error. Compared with partial least squares( PLS),interval partial least squares( iP LS),moving window partial least squares( MWPLS),changeable size moving window partial least squares( CSMWPLS),back interval partial least squares( BiP LS) and locally linear embedding partial least squares( LLE-PLS),Isomap-PLS is the best,whose prediction correlations of MOR and MOE are 0. 89 and 0. 88 respectively,standard errors of prediction( SEP) are 11. 43 and 2. 73 respectively,ratios of performance to standard deviation( RPD) are 2. 55 and 2. 58 respectively,and RPD is more than 2. 5. Hence,this near infrared model can be used to complete the fast and effectivenondestructive testing of Q. mongolica wood with no defect.
引文
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