BP神经网络用于总氮测定过程中I^-、Br^-的干扰消除

Elimination of Interference from Br^-,I^- in the Process of Determination of Total Nitrogen Base on BP Neural Network

在碱性过硫酸钾消解-紫外分光光度法测定水体总氮过程中,碘离子和溴离子的存在会对测定结果产生干扰。针对这一现象,提出采用BP神经网络建立NO3-、I-、Br-含量的预测模型,经过训练后的预测模型能够较准确的预测到NO3-、I-、Br-的含量,从而消除I-、Br-对总氮测定的干扰。此法不需要物理和化学的分离,分析速度快,精度较高,可以消除总氮测定过程中的I-、Br-干扰,有很好的应用价值。

In the process of determination of total nitrogen by UV spectrophotometry with potassium peroxydisulfate in alkaline solution,the iodine ion and bromine ion in solution will interfere the result.In response to this phenomenon,a prediction model using BP neural network was established to predict the content of NO-3,I-,Br-.The prediction model was trained,and can more accurately predicate content of NO-3,I-,Br-with the eliminations of interference from Br-,I-on the determination of total nitrogen.This method does not require the physical and chemical separation.It can get the result very rapidly,have high accuracy,and can eliminate interference of I-,Br-,there is a high value in the process of determination of total nitrogen.