应用近红外光谱技术检测木材含水率的方法
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摘要
运用近红外光谱技术(NIRS)结合偏最小二乘法(PLS),采用了中心化、标准化和导数处理等预处理方法,建立了胡桃楸、榆树以及两个树种混合的含水率预测模型,分析近红外光谱技术在木材含水率检测中的应用。结果表明:在光谱进行中心化和标准化处理后,胡桃楸样本的二阶导数光谱的预测模型最优,其验证集相关系数为0.928 3;榆树样本的一阶导数光谱的预测模型最优,其验证集相关系数为0.952 9;胡桃楸和榆树的混合近红外光谱经过中心、标准化和一阶导数处理后建立的预测模型最优,其验证集相关系数为0.930 9。在合适的光谱预处理和建模方法下,近红外光谱技术能够用于预测木材的含水率,同时利用近红外光谱技术建立混合木材的含水率模型是可行的。
The experiment was conducted to examine feasibility of using NIR spectroscopy combined PLS and some pretreatment methods( MSC,SNV,1 st Derivative and 2 nd Derivative) to predict moisture content of wood samples,including Juglans mandshurica,elm samples and mixed samples of two species. The optimal model of J. mandshurica was the pretreatment of MSC,SNV and 2 nd Derivative with the correlation coefficient of 0.928 3. The optimal model of elm was the pretreatment of MSC,SNV and 1 st Derivative with the correlation coefficient of 0.952 9. The optimal model of mixed species was the pretreatment of MSC,SNV and 1 st Derivative,with the correlation coefficient of 0.930 9. Therefore,the near infrared spectroscopy can be used to predict the moisture content of wood by using suitable spectral pretreatments and modeling methods,and it is feasible to predict moisture content of mixed wood samples by near infrared spectroscopy.
The experiment was conducted to examine feasibility of using NIR spectroscopy combined PLS and some pretreatment methods( MSC,SNV,1 st Derivative and 2 nd Derivative) to predict moisture content of wood samples,including Juglans mandshurica,elm samples and mixed samples of two species. The optimal model of J. mandshurica was the pretreatment of MSC,SNV and 2 nd Derivative with the correlation coefficient of 0.928 3. The optimal model of elm was the pretreatment of MSC,SNV and 1 st Derivative with the correlation coefficient of 0.952 9. The optimal model of mixed species was the pretreatment of MSC,SNV and 1 st Derivative,with the correlation coefficient of 0.930 9. Therefore,the near infrared spectroscopy can be used to predict the moisture content of wood by using suitable spectral pretreatments and modeling methods,and it is feasible to predict moisture content of mixed wood samples by near infrared spectroscopy.
引文
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[10]张慧娟,李耀翔,张鸿富,等.基于近红外光谱不同波段的红松木材含水率预测分析[J].东北林业大学学报,2011,39(4):83-85.
[11] ADCHA H,HSIEH C L. Measurement of moisture content for rough rice by visible and near-infrared(NIR)spectroscopy[J].Engineering in Agriculture,Environment and Food,2016,9(3):280-290.
[12] MATTHIEU C,YVES R,KLARA D,et al. Global regression model for moisture content determination using near-infrared spectroscopy[J]. European Journal of Pharmaceutics and Biopharmaceutics,2017,119(1):343-352.
[13]江泽慧,黄安民.木材中的水分及其近红外光谱分析[J].光谱学与光谱分析,2006,26(8):1464-1468.
[14]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005.
[15]刘亚娜,杨忠,吕斌,等.木材表面光泽度的近红外漫反射光谱技术快速测定研究[J].光谱学与光谱分析,2014,34(3):648-651.
[16] WORKMAN J,WEYER L. Practical guide to interpretive nearInfrared spectroscopy[M]. Boca Raton:CRC Press,Inc,2007.
[2]刘昊.基于应力波的木材含水率检测理论及影响因素研究[D].北京:北京林业大学,2014.
[3]李超,张明辉,于建芳.利用核磁共振自由感应衰减曲线测定木材含水率[J].北京林业大学学报,2012,34(4):142-145.
[4] HELA D G,YACINE O,MARIA M,et al. Wood moisture content prediction using feature selection techniques and a kernel method[J]. Neurocomputing,2017,237(6):79-91.
[5] TIEN C M,STEPHEN R,ZOUBIR M S,et al. Non-destructive evaluation of moisture content of wood material at GPR frequency[J]. Construction and Building Materials,2015,77(5):213-217.
[6]刘昊.基于应力波的木材含水率检测理论及影响因素研究[D].北京:北京林业大学,2014.
[7]吉海彦.近红外光谱仪器技术[J].现代科学仪器,2001,17(6):25-28.
[8]周新奇,叶华俊,张学锋,等.聚光科技新型近红外光谱分析仪器研制进展[J].现代仪器,2011,17(5):19-23.
[9]郝斯琪,宋博骐,李湃,等.基于近红外光谱与BP神经网络预测落叶松木屑的含水率[J].森林工程,2012,28(4):9-11.
[10]张慧娟,李耀翔,张鸿富,等.基于近红外光谱不同波段的红松木材含水率预测分析[J].东北林业大学学报,2011,39(4):83-85.
[11] ADCHA H,HSIEH C L. Measurement of moisture content for rough rice by visible and near-infrared(NIR)spectroscopy[J].Engineering in Agriculture,Environment and Food,2016,9(3):280-290.
[12] MATTHIEU C,YVES R,KLARA D,et al. Global regression model for moisture content determination using near-infrared spectroscopy[J]. European Journal of Pharmaceutics and Biopharmaceutics,2017,119(1):343-352.
[13]江泽慧,黄安民.木材中的水分及其近红外光谱分析[J].光谱学与光谱分析,2006,26(8):1464-1468.
[14]严衍禄.近红外光谱分析基础与应用[M].北京:中国轻工业出版社,2005.
[15]刘亚娜,杨忠,吕斌,等.木材表面光泽度的近红外漫反射光谱技术快速测定研究[J].光谱学与光谱分析,2014,34(3):648-651.
[16] WORKMAN J,WEYER L. Practical guide to interpretive nearInfrared spectroscopy[M]. Boca Raton:CRC Press,Inc,2007.