Discriminant analysis of wood-based materials with weathering damage by near infrared spectroscopy
Discriminant analysis of wood-based materials with weathering damage by near infrared spectroscopy
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DOI：
10.1255/jnirs.390
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发表时间：
2003-01-01
影响因子：
1.8
通讯作者：
Yamato, K
中科院分区：
文献类型：
--
作者：
Tsuchikawa, S;Yamato, K
本研究旨在通过近红外光谱分析和多种化学计量学手段，寻找一种适合于模拟废旧木材状况的木质材料风化损伤的识别技术。对马氏广义距离、K近邻(KNN)或软独立类比模型(SIMCA)作为木质材料分类方法的可行性进行了详细的研究。还考虑了以分光光度计(例如，实验室使用和现场使用)、近红外光谱的预处理或波长范围作为解释变量在分类准确性方面的差异。将五类木质材料(实木、层压木材、刨花板或纤维板、浸渍木材和覆盖木材)暴露在户外阳光下长达六个月。由于近红外光谱随样品类别的不同而有很大差异，因此很难将马氏广义距离应用于五种物质类型的分类。独立于分光光度计，KNN和SIMCA的分类正确率均在93%以上。这些结果支持了近红外光谱技术在实际工厂和工作现场废旧木材分类中的适用性。
This research was aimed at finding a suitable discriminate technique for wood-based materials which had suffered from weathering damage, as an analogue of waste wood condition, by means of near infrared (NIR) spectroscopy and several kinds of chemometrics. The feasibility of Mahalanobis generalised distance, K nearest neighbours (KNN) or soft independent modelling of class analogy (SIMCA) as the classification method of wooden materials was examined in detail. The differences in the accuracy of classification with the spectrophotometer (for example, laboratory use and field use), pre-treatment of NIR spectra or the wavelength range as the explanatory variables were also taken into account. Five categories of wood-based materials (solid wood, laminated wood, particle or fibreboard, impregnated wood and overlaid wood) were exposed to outdoor sunlight for up to six months. It was difficult to apply Mahalanobis generalised distance to the classification of five material types where the NIR spectra varied greatly with the sample categories. Both of KNN and SIMCA presented the highest correct classification of over 93%, independent of the spectrophotometer. These results support the applicability of NIR spectroscopy to the classification of waste wood at the actual factory and job site.