Distribution water quality anomaly detection from UV optical sensor monitoring data by integrating principal component analysis with chi-square distribution.
Distribution water quality anomaly detection from UV optical sensor monitoring data by integrating principal component analysis with chi-square distribution.
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DOI：
10.1364/oe.23.017487
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发表时间：
2015-06
期刊：
影响因子：
3.8
通讯作者：
D. Hou;Jian Zhang;Zheling Yang;Shu Liu;Pingjie Huang;Guangxin Zhang
中科院分区：
文献类型：
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作者：
D. Hou;Jian Zhang;Zheling Yang;Shu Liu;Pingjie Huang;Guangxin Zhang
由于有害污染物的潜在威胁，配水水质安全保障问题最近引起了全球的关注。基于紫外光学传感器的实时监测是一项很有前途的技术。该方法无需试剂、维护成本低、分析快速、覆盖范围广。但紫外吸收光谱尺寸较大，容易受到干扰。在现场应用中，在确定之前几乎没有潜在污染物的光谱特征等先验知识。同时，正常水质的概念也因运行状况的不同而不同。本文提出了一种基于多元统计分析的程序，用于基于紫外光学传感器检测配水水质异常。首先，采用主成分分析从光谱矩阵中捕获主要品种特征并降维。然后构造一个新的统计变量，并根据主成分子空间中的卡方分布来评估局部偏离程度。通过累加相邻先前观测值的离群度来计算最近观测值出现异常的可能性。为了开发更可靠的异常检测程序，讨论了几个关键参数。利用所提出的方法，可以检测配水水质异常和光学异常变化。污染物侵入实验是在中试规模的分配系统中通过注入苯酚溶液进行的。最后使用实验光谱数据证明了所提出程序的有效性。
The issue of distribution water quality security ensuring is recently attracting global attention due to the potential threat from harmful contaminants. The real-time monitoring based on ultraviolet optical sensors is a promising technique. This method is of reagent-free, low maintenance cost, rapid analysis and wide cover range. However, the ultraviolet absorption spectra are of large size and easily interfered. While within the on-site application, there is almost no prior knowledge like spectral characteristics of potential contaminants before determined. Meanwhile, the concept of normal water quality is also varying due to the operating condition. In this paper, a procedure based on multivariate statistical analysis is proposed to detect distribution water quality anomaly based on ultraviolet optical sensors. Firstly, the principal component analysis is employed to capture the main variety features from the spectral matrix and reduce the dimensionality. A new statistical variable is then constructed and used for evaluating the local outlying degree according to the chi-square distribution in the principal component subspace. The possibility of anomaly of the latest observation is calculated by the accumulation of the outlying degrees from the adjacent previous observations. To develop a more reliable anomaly detection procedure, several key parameters are discussed. By utilizing the proposed methods, the distribution water quality anomalies and the optical abnormal changes can be detected. The contaminants intrusion experiment is conducted in a pilot-scale distribution system by injecting phenol solution. The effectiveness of the proposed procedure is finally testified using the experimental spectral data.