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蒙古栎木材MOR与MOE的近红外光谱预测模型分析

张怡卓 苏耀文 李超 门洪生

张怡卓, 苏耀文, 李超, 门洪生. 蒙古栎木材MOR与MOE的近红外光谱预测模型分析[J]. 北京林业大学学报, 2016, 38(8): 99-105. doi: 10.13332/j.1000-1522.20150505
引用本文: 张怡卓, 苏耀文, 李超, 门洪生. 蒙古栎木材MOR与MOE的近红外光谱预测模型分析[J]. 北京林业大学学报, 2016, 38(8): 99-105. doi: 10.13332/j.1000-1522.20150505
ZHANG Yi-zhuo, SU Yao-wen, LI Chao, MEN Hong-sheng.. Analysis of MOR and MOE prediction model of Quercus mongolica wood by near infrared spectroscopy.[J]. Journal of Beijing Forestry University, 2016, 38(8): 99-105. doi: 10.13332/j.1000-1522.20150505
Citation: ZHANG Yi-zhuo, SU Yao-wen, LI Chao, MEN Hong-sheng.. Analysis of MOR and MOE prediction model of Quercus mongolica wood by near infrared spectroscopy.[J]. Journal of Beijing Forestry University, 2016, 38(8): 99-105. doi: 10.13332/j.1000-1522.20150505

蒙古栎木材MOR与MOE的近红外光谱预测模型分析

doi: 10.13332/j.1000-1522.20150505
基金项目: 

948国家林业局引进项目(2015-4-52)。

详细信息
    作者简介:

    张怡卓,博士,教授。主要研究方向:图像处理与模式识别。Email:nefuzyz@163.com地址:150040黑龙江省哈尔滨市香坊区和兴路26号东北林业大学机电工程学院。

Analysis of MOR and MOE prediction model of Quercus mongolica wood by near infrared spectroscopy.

  • 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 mm20 mm20 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、iPLS、MWPLS、CSMWPLS、BiPLS、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2.552.5;MOE预测相关系数为0.88,SEP为2.73,RPD为2.582.5。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。

     

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  • 收稿日期:  2015-12-18
  • 刊出日期:  2016-08-31

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