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采用FS920荧光光谱仪分析了苯并[k]荧蒽(BkF)、苯并[b]荧蒽(BbF)和两者混合物的荧光特性.结果表明BkF的两个荧光峰分别位于306nm/405nm和306nm/430nm,BbF的两个荧光峰分别位于306nm/410nm和306nm/435nm.BkF和BbF不同浓度配比及其相互间的荧光干扰,使得混合物荧光特性差异较大,荧光强度和浓度间关系变得复杂.为准确测定混合物中BkF和BbF的浓度,采用递阶算法优化的径向基神经网络对其进行检测,结果表明BkF和BbF的平均回收率分别为98.45%和97.71%.该方法能够实现多环芳烃类污染物共存成分的识别和浓度预测.
Fluorescence characteristics of benzo [k] fluoranthene (BkF), benzo [b] fluoranthene (BbF) and their mixtures were analyzed by FS920 fluorescence spectrometer.The results showed that the two fluorescence peaks of BkF were at 306nm / 405nm and 306nm / 430nm, the two fluorescence peaks of BbF are located at 306nm / 410nm and 306nm / 435nm, respectively.Buf and BbF ratio of different concentrations and mutual interference of fluorescence, making the mixture of fluorescence characteristics vary greatly, the relationship between fluorescence intensity and concentration becomes In order to accurately determine the concentration of BkF and BbF in the mixture, the radial basis neural network (RBFNN) was used to test the concentration of BkF and BbF. The results showed that the average recoveries of BkF and BbF were 98.45% and 97.71% Identification and Concentration Prediction of Coexisting Components of Polycyclic Aromatic Hydrocarbons.