知识与财富的链接
信噪比作为光谱仪的重要指标之一,体现了光谱仪对微弱信号的检测能力。为了考察信噪比对光谱分析精度的影响,首先介绍了影响光谱信噪比的主要因素,然后以绿茶产地鉴别为例,通过实验分析了光谱信噪比对绿茶产地溯源分析模型精度的影响,同时拟合出光谱信噪比与光谱分析模型预测精度之间的关系,讨论了提高光谱信噪比的方法。结果表明,随着光谱信噪比的降低,训练集和预测集建模模型的准确度均呈现先缓慢下降,然后直线下降,最后趋于平缓的趋势。通过计算可知,为实现模型对预测集样本预测准确度达到90%和85%,要求光谱信噪比分别高于23.42 dB和21.16 dB。实验结果对新型在线分析用光谱类仪器的研制提供一定参数支持,尤其是对仪器信噪比这一指标。
As one of the important indicators of spectrometer, signal-to-noise ratio（SNR） reflects the ability of spectrometer to detect weak signals. To investigate the influence of SNR on the prediction accuracy of spectral analysis, we first introduce the major factors affecting the spectral SNR. Taking green tea as an example, the influence of spectral SNR on the prediction accuracy of the origin identification model is analyzed by experiments. At the same time, the relationship between the spectral SNR and prediction accuracy of spectral analysis model is fitted. Based on this, the common methods for improving the spectral SNR are discussed. The results show that the accuracy of the prediction set model first decreases slowly, then decreases linearly, and finally tends to be flat as the spectral SNR decreases. Through calculation, in order to achieve the prediction accuracy of prediction model reaching 90% and 85%, the spectral SNR is required to be higher than 23.42 dB and 21.16 dB, respectively. The overall results provide certain parameters support for the development of new online analytical spectroscopic instruments, especially for the technical indicators of SNR.
