基于三维荧光和多传感器信息融合的水中嗅味物质快速检测方法研究

With the increasingly prominent environmental problems, water environment protection and ecological construction have risen to the strategic height of the national development. The problem of taste and odor (T&O) pollution in water is directly related to people's safety and health, and has been arousing more and more widespread concern. Current T&O detection technologies either relies on human senses or complex instrument operation, which are affected by human factors, time-consuming and expensive. Consequently, they are difficult to meet the intelligent requirements in water environment monitoring. This project is aiming at developing a low cost, accurate and rapid detection technology of T&O substances in water. This innovative detection method is based on three-dimensional fluorescence spectral analysis and multi-sensor information fusion. Based on multi-model correction, the spectrum preprocessing and feature region extraction methods are studied and proposed, to reduce the impact on spectrum from complex and changeable water environment. The relationship between T&O substances and their spectral information are investigated by using advanced information processing technology. And three-dimensional fluorescence characteristic models and spectral fingerprint database of typical T&O substance in water will be established. Furthermore, water quality information obtained by multi-sensor is used to study the mapping relationship between T&O substances and multiple water quality indices. Multi-level information fusion methods are studied to make comprehensive use of three-dimensional fluorescence spectroscopy and multi-sensor information. Based on that, a low cost, accurate, rapid detection method of T&O substances in water will be established and the detection system prototype will be developed. As part of interdisciplinary in environment, detection technology and information, this project will provide theory, new method and technical support for water environment monitoring and water pollution prevention field.

随着环境问题日渐突出，水环境保护和生态建设已经上升到国家战略发展高度。水体异嗅异味问题直接关系人民安全健康，引起了越来越广泛的关注。现有水中嗅味检测技术依赖人体感官、耗时长、成本高，难以满足水环境智能监测的要求。本项目以水中嗅味物质低成本、准确、快速检测为研究目标和重点，建立以嗅味物质三维荧光光谱特征提取为基础、结合多传感器信息融合技术的水中嗅味物质检测新理论、新方法。针对水环境复杂多变，提出基于多模型校正的光谱预处理及特征区域提取方法；运用先进信息处理技术，研究嗅味物质与光谱信息的关联关系，建立水中嗅味物质三维荧光特征模型及光谱指纹库；同时利用多传感器水质信息，研究嗅味物质与水质指标映射关系；综合利用三维荧光光谱及多传感器信息进行分布式、多层次融合，建立水中典型嗅味物质检测方法和系统原型。本项目作为环境、检测、信息等多学科交叉的前沿内容，为水环境监测和水污染防治提供理论、方法和技术支持。

近年来，随着环境问题日渐突出，水环境保护和生态建设已经上升到国家战略发展高度。水体异嗅异味问题直接关系人民安全健康，引起了越来越广泛的关注。现有水中嗅味检测技术依赖人体感官、耗时长、成本高，难以满足水环境智能监测的要求。本项目以三维荧光光谱为主要检测手段，围绕三维荧光光谱和多源信息融合在水中嗅味物质检测与识别问题，从提高检测准确性、快速性、适应性等角度出发，深入进行了光谱预处理技术、嗅味物质特征提取与建模方法、多指标融合技术、多源信息检测方法等研究工作。针对检测环境复杂带来的检测干扰等问题，进行了三维荧光光谱预处理技术及信号增强方法研究；针对嗅味物质种类多样、相似物质难检出、长期检测适应性低等问题，进行了三维荧光光谱特征及背景检测基线提取方法研究；针对多指标间存在冲突、单一信息源检测准确率低等问题，进行了指标互相关建模及多数据融合检测方法研究。解决了三维荧光和水质指标联用在嗅味物质在线异常检测和识别中的关键问题，形成了面向不同应用场景的嗅味物质异常检测和分类识别模型，研发完成了基于荧光光谱的便携式嗅味物质检测设备和分析平台。为水中典型嗅味物质提供快速、可靠的在线检测新手段、新方法和新方案，为水环境监测特别是异嗅异味监测提供更有效的方法，为供水安全保障和水污染防治提供有力支撑。项目执行期间共发表学术论文12篇，其中SCI收录期刊论文10篇，国内学术会议论文1篇，国际学术会议论文1篇（EI收录），申请国家发明专利8项（已授权3项）。