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Detection of specific contamination events in water distribution system using ultraviolet spectra

机译:使用紫外线光谱检测供水系统中的特定污染事件

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In recent years, issues surrounding water quality's security have attracted attention. The use of UV/VIS spectrum, for the in-situ detection of water-quality anomalies, has several advantages: it is free of reagent, has a low cost and facilitates rapid analysis. For these reasons, it is one of the more popular research trends for urban distribution water systems. This paper proposes using the UV-VIS spectrum detection method to resolve the problems of existing methods, which cannot distinguish specific contaminants. We made a pretreatment using orthogonal projection to correct the gap between different batches of spectral data. We then used Partial Least Squares Discriminatory Analysis to extract features from the data set. A comparison of the alarm signal with the optimal threshold, revealed outliers from the training set. Finally, we used the Sequential Bayesian Method to update the probability of Contaminate Intrusion Events and to obtain the alarm sequence. Our results show that this new method is effective in detecting specific contamination, which can assist existing methods to confirm contamination types.
机译:近年来,围绕水质安全的问题引起了人们的关注。使用UV / VIS光谱对水质异常进行原位检测具有以下优点:无试剂,成本低且便于快速分析。由于这些原因,它是城市供水系统最受欢迎的研究趋势之一。本文提出了使用UV-VIS光谱检测方法来解决现有方法无法识别特定污染物的问题。我们使用正交投影进行了预处理,以校正不同批次的光谱数据之间的间隙。然后,我们使用偏最小二乘判别分析从数据集中提取特征。警报信号与最佳阈值的比较显示了训练集中的异常值。最后,我们使用顺序贝叶斯方法来更新污染入侵事件的概率并获得警报序列。我们的结果表明,这种新方法可以有效地检测特定的污染物,这可以帮助现有方法确定污染物的类型。

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