基于时间序列光谱数据的水中污染物检测方法研究

项目名称： 基于时间序列光谱数据的水中污染物检测方法研究

项目编号： No.61308063

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 于绍慧

作者单位： 合肥师范学院

项目金额： 24万元

中文摘要： 光谱技术是目前对水中污染物进行监测的重要技术，它具有灵敏度高，分析速度快，没有二次污染等特点，十分利于在线实时监测。以连续监测产生的时间序列数据为研究对象，对所获取的光谱数据进行有效的特征提取和数据解析是一项重要而有意义的工作。本项目在充分调研现有的光谱分析法的基础上，以三维荧光光谱技术为研究重点，将主要解决三方面的问题：第一，结合时间序列光谱数据特点，完成光谱的特征提取，解决普遍存在的腐殖酸等有机物的荧光光谱的波长范围广、强度大，影响着其他痕量有机物监测的困难；第二，建立时间序列荧光光谱的多组分有机物定性和定量分析的数学模型，重点探讨异常子序列（即突发性污染）的检测；第三，在前两部分的研究基础上，从时间序列分析的角度，实现不同有机物浓度的短期预测。通过本项目的研究，水中有机污染物检测的精确度会大大提高。

中文关键词： 时间序列；特征区域；数据压缩；结构相似度；

英文摘要： The spectral detection is one of the important techniques for monitoring the contaminants in water. It is very beneficial to online monitoring with high sensitivity , fast response and no secondary pollution etc. Generally, large amounts of spectral data will be produced by continuous monitoring, so it becomes specially significant to analyze the data such as feature extraction etc. In this project, focusing on three-dimensional spectroscopy,we will carry out the following research. Fistly, the feature extraction will be effectively completed by combing the characteristic of time series spectral data. This will resolved the impact of humic acid which affects the spectral signal of other pollutants, because humic acid is characterized by wide wavelength and strong intensity. Secondly, we will found the mathematical models which is used to complete the qualitative and quantitive analysis of muti-component organic compound according to the time series fluorescence spectroscopy. Mostly, the detection of the abnormal sequence, namely the accidental pollution, will be discussed. Lastly, on the basis of the first two parts, the short forecast of the organic compound concentration will be studied by time series data. In brief, the detection accuracy of different organic pollutants in water can be greatly improved

英文关键词： time series；characteristics region；data compression；structural similarity；