基于信息融合的化学需氧量绿色检测新方法

Dichromate method is currently the standard way for determination of Chemical Oxygen Demand (COD) in water at home and abroad. The disadvantages including high cost, complicated operation, and secondary pollution exist due to consumptions of chemical reagent during the detection process, such as chromium, silver and mercury. Thus, how to make the environmental monitoring more environment-friendly is badly in need of resolution for COD detection technique in water. In terms of the definition of COD, the multi-sensors will be designed in this research project to detect the oxygen equivalent of organic matter consumption by using the ozone/UV catalytic oxidation method. On the base of studying the degradation mechanism and modeling methods based on ozone/UV, the kinetic model of the total organic matter will be studied in complex water quality, and a detection model for characteristic information of reducing substance degradation based on multi-sensor information fusion will be established. In addition, the applying basic research on the dynamic trend prediction and fault diagnosis for sensors will be also carried out..The method can avoid the use of chemical reagents from the detection principle so that to realize green detection of chemical oxygen demand in water. The research will break through the bondage of the traditional national standard method, and it not only have important scientific theory value, and develop a kind of new technology for water COD on-line detection and broaden the way of the development of environmental monitoring technology. This method can also be applied on monitoring of other parameters in water and shows a vast application prospects.

目前国内外测定水质化学需氧量的标准方法是重铬酸钾法。检测过程需消耗含铬、银、汞等化学试剂，存在运行成本高、操作复杂、容易造成二次污染等，致使环保监测不环保，是水质检测技术急需要解决的难题。本课题提出利用臭氧/紫外光催化协同氧化技术，根据化学需氧量的定义，采用多传感器信息融合的方法检测有机物消耗的氧当量。研究基于臭氧/紫外的降解机理和建模方法，建立复杂水样条件下总有机物的臭氧/紫外氧化体系动力学模型，构建基于多传感器信息融合的还原物降解特征信息检测模型，开展传感器动态运行趋势预测和故障诊断等应用基础研究。该方法从检测原理上避免了化学试剂的使用，真正实现水质化学需氧量的快速绿色检测。研究成果突破了传统国标方法的束缚，不仅具有重要的科学理论价值，而且开拓了一种水质COD在线检测的新技术，拓宽了环境监测技术的发展思路。此外，该方法还可以推广应用到水质监测的其它特征参数检测中，具有广阔的应用前景。

针对现有的水质COD在线检测标准方法，检测过程需消耗含铬、银、汞 等化学试剂，存在运行成本高、操作复杂、容易造成二次污染等问题，本项目重点研究了利用臭氧/紫外光催化协同氧化技术，根据化学需氧量的定义，采用多传感器信息融合的方法检测有机物消耗的氧当量。研究了基于臭氧/紫外的降解机理，建立了复杂水样条件下总有机物的臭氧/紫外氧化体系动力学模型，构建了基于多传感器信息融合的还原物降解特征信息检测模型，并围绕上述研究内容，开展了相关检测传感器和水质在线监测装置的故障诊断等应用基础研究。在多传感器信息融合的还原物降解特征信息检测模型的基础上，分别提出了一种用于对COD检测模型补偿的消解过程气体溶解量估计方法和消解终止自动确定的检测方法。.多传感器信息融合方法从检测原理上避免了化学试剂的使用，真正实现了水质化学需氧量的快速绿色检测。研究成果突破了传统国标方法的束缚，开拓了一种水质COD在线检测的新技术，拓宽了环境监测技术的发展思路。.研究工作按计划已经达到了预期目标。完成了COD在线监测装置样机一套和蓝藻在线监测装置样机一套的开发工作；授权发明专利2项，申请发明专利2项（其中包括PCT专利1项） 。课题资助或部分资助发表论文57篇，其中SCI期刊论文20篇，EI期刊论文9篇。培养博士研究生3名和硕士研究生8名。研究的部分理论成果已应用于COD、总氮、总磷在线监测装置和蓝藻在线监测装置的样机中。