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基于多环芳烃中苯并[k]荧蒽(BkF)的强荧光特性,构建了荧光检测实验系统,并制备了10个不同浓度的BkF甲醇溶液样品,分析了样品荧光特性。为了更好地进行定性和定量分析,采用经验模态分解(EMD)改进阈值法结合数学形态学对荧光光谱信号进行去噪处理,并与EMD阈值去噪法进行对比。结果表明,提出的方法使去噪后的荧光光谱更加平滑,荧光强度与样品浓度的线性相关系数更高,达到0.99746;信噪比有所提高;原始信号与去噪后信号的均方误差由0.0053降低至0.0012。提出的方法去噪效果显著,有效地提高了光谱的分析精度,为荧光光谱预处理提供了一种新方法。
Based on the strong fluorescence of benzo [k] fluoranthene (BkF) in polycyclic aromatic hydrocarbons (PAHs), a fluorescence detection system was constructed and 10 different concentrations of BkF methanol solution were prepared. The fluorescence characteristics of the samples were analyzed. In order to conduct better qualitative and quantitative analysis, EMD threshold method and mathematical morphology were used to denoise the fluorescence spectrum signal and compared with EMD threshold denoising method. The results show that the proposed method smoothes the fluorescence spectrum after de-noising, and the linear correlation coefficient between the fluorescence intensity and the sample concentration is higher, reaching 0.99746; the signal-to-noise ratio is improved; the mean square error of the original signal and the de-noised signal is from 0.0053 to 0.0012. The proposed method has significant denoising effect and effectively improves the spectral analysis accuracy, providing a new method for fluorescence spectrum pretreatment.