摘要： 针对目前近红外光谱分析中模型传递现有方法的局限性，文章介绍了一种简便的近红外光谱标准化方法，并构造了一种新的光谱标准化误差指标(spectra standard error，SSE)作为评价传递结果的指标。SSE为J2和J1的比值，这里，J2表示同一样本在不同仪器上测得的谱线的距离，J1表示目标机的不同样本相对中心谱线的平均距离。文章首先对不同光谱仪所测得的吸光度谱图进行多项式卷积平滑处理以去除基线，接着采用标准归一法以实现谱图的标准化，并采用多项式卷积滤波以去除噪声。为使SSE达到最小，在处理过程中可进行波长范围和卷积窗口宽度的优化。经过上述处理后的标准化谱图可用于光谱建模分析。该方法不需要预先获得大量样本，也不需要将同一样本在不同光谱仪上测得的谱图进行比较。针对一批汽油样本的试验结果表明，借助于此方法可使SSE从1.418下降至0.167，谱图标准化效果令人满意。
关键词：近红外光谱;光谱标准化误差指标;预处理;模型传递;波长选择;汽油辛烷值
Abstract：Due to the limitation of current algorithms for NIR spectral analysis model transfer, a simple and convenient algorithm to standardize the spectra was proposed, and a new performance index called spectra standard error (SSE) was also constructed to evaluate the validity of model transfer algorithms. SSE expresses the ratio of J2 to J1, where J2 describes the distances between the spectra of the same sample using different instruments, and J2 describes the average distance between the spectra of different samples using the original instrument for their central spectrum. In the present paper we first used Savitzky-Golay smoothing to realize baseline correction for different spectra, and then applied standard normal variate method to standardize spectra and polynomial filtering to avoid noise. Besides, we optimized the wavelength range and the window width in Savitzky-Golay smoothing in order to minimize the SSE. After these steps, the standardized spectra can be applied to spectral analysis modeling. By the new algorithm, neither collecting a great number of samples nor need measuring all spectra of training samples using different instruments are needed. For a set of gasoline samples, SSE can be reduced from 1.418 to 0.167 via the new standardization algorithm and satisfactory results were obtained.
Key words：NIR spectra;Spectra standard error;Preprocessing;Model transfer;Wavelength selection;Gasoline octane number
包鑫，戴连奎*. 一种简便的近红外光谱标准化方法[J]. 光谱学与光谱分析, 2008, 28(04): 829-833.
BAO Xin,DAI Lian-kui*. A Simple and Convenient Standardization Algorithm of NIR Spectra. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2008, 28(04): 829-833.
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