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Morphological Grayscale Reconstruction and ATLD for Recognition of Organic Pollutants in Drinking Water Based on Fluorescence Spectroscopy

机译:基于荧光光谱的饮用水中有机污染物的形态灰度重构与ATLD

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摘要

This paper proposes a morphological grayscale reconstruction method combined with an alternating trilinear decomposition (ATLD) and threshold method based on 3D fluorescence spectroscopy to detect pollutants present at low concentrations in drinking water. First, the morphological grayscale reconstruction method was used to locate the fluorescence peaks of pollutants by comparing the original and reconstructed spectra obtained through expansion. The signal in the characteristic spectral region was then enhanced using an amplification factor. Feature extraction was subsequently performed by ATLD, and the threshold method was used to qualitatively distinguish water quality. By comparing the proposed method with the direct use of the ATLD and threshold method—which is a commonly used feature-extraction method—this study found that the application of the morphological grayscale reconstruction method can extrude characteristics of 3D fluorescence spectra. Given the typical spectral characteristics of phenol, salicylic acid, and rhodamine B, they were selected as experimental organic pollutants. Results illustrated that the morphological grayscale reconstruction with ATLD improved the spectral signal-to-noise ratio of pollutants and can effectively identify organic pollutants, especially those present at low concentrations.
机译:本文提出了一种形态学灰度重建方法与基于3D荧光光谱的交替三线性分解(ATLD)和阈值法,以检测饮用水低浓度存在的污染物。首先,通过比较通过膨胀获得的原始和重建光谱来定位污染物的荧光峰来定位形态灰度重建方法。然后使用放大因子提高特征光谱区域中的信号。随后通过ATLD进行特征提取,阈值方法用于定性区分水质。通过将所提出的方法与直接使用ATLD和阈值方法进行比较 - 这是一种常用的特征提取方法 - 本研究发现,形态灰度重建方法的应用可以挤出3D荧光光谱的特性。鉴于酚醛,水杨酸和罗丹明B的典型光谱特性,它们被选为实验有机污染物。结果表明,ATLD的形态灰度重建改善了污染物的光谱信噪比,可以有效地识别有机污染物,尤其是在低浓度下存在的污染物。

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