Classification of waste materials using Fourier transform infrared spectroscopy and soft independent modeling of class analogy.
Classification of waste materials using Fourier transform infrared spectroscopy and soft independent modeling of class analogy.
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DOI：
10.1016/j.wasman.2007.08.003
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发表时间：
2008
期刊：
影响因子：
8.1
通讯作者：
E. Smidt;K. Meissl;Manfred Schwanninger;P. Lechner
中科院分区：
文献类型：
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作者：
E. Smidt;K. Meissl;Manfred Schwanninger;P. Lechner
傅里叶变换红外光谱法结合多元数据分析正在开发中，作为一种分类废物的方法。样品的化学成分由红外光谱的一系列区域反映，这些区域用作多变量数据分析的变量。在这项研究中，收集了分离的生物废物收集、机械生物处理废物（MBT废物）和旧垃圾填埋场材料，以提供代表不同分解阶段的材料。共记录了819个FTIR吸收光谱。主成分分析（PCA）进行软独立建模类类比（SIMCA）分类的废物材料。强分类发生的分析光谱碳酸盐地区，并为另一个分析时，他们没有。SIMCA模型使未知样品的区分和分类，根据这三个类别在这两种情况下。这里开发的分类方法提供了一种评估工具，监管机构在评估来自不确定过程的经处理的废物是否可以归类为堆肥或MBT废物时可能希望探索。
Fourier transform infrared (FTIR) spectroscopy combined with multivariate data analysis is under development as a method to classify waste materials. The chemical composition of the sample is reflected by a series of regions of the infrared spectrum which are used as variables for multivariate data analysis. In this study, separated biowaste collection, mechanically-biologically treated waste (MBT-waste), and old landfill materials were collected to provide materials representing different stages of decomposition. A total of 819 FTIR absorbance spectra were recorded. Principal component analyses (PCA) were performed followed by soft independent modeling of class analogy (SIMCA) for classification of waste materials. Strong classification occurred for an analysis where spectral carbonate regions were included, and for another analysis when they were not. The SIMCA model enabled the differentiation and the classification of unknown samples according to the three categories in both cases. The classification methods developed here provide an assessment tool that regulatory authorities may wish to explore when assessing whether a treated waste from an uncertain process can be classed as compost or MBT-waste.