摘要
提出了采用无背景傅里叶变换红外 (FTIR)光谱对多组分气体体系进行定量分析的方法 ,并用于燃烧废气的检测。得到待测样品吸收光谱的通常方法是 ,将样品的透射光谱和不含样品的背景光谱进行差减计算。而本文提出的方法在缺少背景光谱的情况下 ,采用样条插值法通过数值计算的方法从样品透射光谱中得到了吸收光谱 ,并提取了光谱的定量特征 ,然后通过神经网络技术得到了谱峰强度和气体浓度之间的非线性映射关系。这种方法的突出特点是不需要测量背景光谱 ,所以适合于开放光程和以太阳为光源的FTIR光谱测量。而且 ,它能够在光谱中含有各种非线性成分 ,成功地对低信噪比光谱进行定量分析。
The author proposed for a novel method of multi\|component gaseous system quantitative analysis using Fourier Transform Infrared (FTIR) spectra without background measurement. The common used method of getting the absorption spectrum is to subtract the background spectrum from the transmission spectrum of the sample. Instead, the method proposed in this paper calculates the absorption spectrum from the transmission spectrum of the sample using a Spline Interpolation Method (SIM) in the absence of background spectrum and thus extracts the quantitative feature of the spectrum. After that, the technique of Artificial Neural Network (ANN) is utilized to obtain the relationship between the spectral strength and the consistence of the sample gas. The prominent characteristic of this method is that it can work well in the absence of the background spectrum, so it is very suitable for open\|path and solar FTIR spectral measurement. Also, it has the ability to successfully perform the quantitative analysis of very low Signal to Noise Ratio (SNR) spectrum with the presence of various non\|linear factors in the spectrum.
出处
《计算机与应用化学》
CAS
CSCD
2000年第3期251-256,共6页
Computers and Applied Chemistry
关键词
傅里叶变换红外光谱
废气检测
大气污染
spline interpolation method, FTIR spectrum, artificial neural network,exhaust gas detection, atmosphere pollution
