多菌灵农药激光拉曼光谱的小波去噪方法研究
Study for wavelet denoising methods of laser Raman spectrum of carbendazim pesticide
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摘要: 利用激光拉曼光谱仪采集多菌灵农药标准品拉曼信号,分别采用移动平均平滑法、小波软阈值法和小波硬阈值法对光谱信号进行去噪处理,对比各方法的去噪效果。结果表明:小波硬阈值法可获得最优去噪质量,当小波基函数为sym2,尺度分解为5,阈值量化为‘Heursure’,硬阈值处理,重构光谱的信噪比最大(为60.927),均方根误差最小(为11.429)。研究表明:小波硬阈值法能有效去除多菌灵农药拉曼光谱信号的噪声,最大程度保留拉曼光谱特征信息,为食品及农产品中农药残留的拉曼光谱快速检测提供方法支持。Abstract: Raman signal of carbendazim pesticide was collected by laser Raman spectrometer. Moving- average smoothing method, wavelet soft- threshold method and wavelet hard- threshold were applied respectively to denoise the acquired Raman signals, and their denoising effects were compared.The results showed that wavelet hard- threshold could obtain the optimal denoising quality. When wavelet base function being sym2, scale decomposition being 5, the threshold quantization being ‘Heursure', hard- threshold value being processed, signal to noise ratio ( SNR) of the reconstructed spectral was maximum which was 60.927, and root mean square error ( RMSE) was minimum which was 11.429. The study showed that wavelet hard- threshold could effectively remove the noise information of the raw Raman signals of carbendazim pesticide, and saved the most number of spectra details.The study could provide a methodological support for the rapid detection of pesticide residue in food and agricultural products based on Raman spectrum.