| 论文简介 |
Fourier transform infrared spectrometer (FTIR) has been widely used to analyze multi-component gas mixture
for more than ten years because of its potential benefits. However, it is a challenge to analyze multicomponent
alkane mixture on-line with FTIR because their absorption spectra overlap with each other extensively.
In this paper, the methods of feature extraction and selection based on Tikhonov regularization (TR), and the
modeling methods based on neural network (NN) are discussed in the practical conditions of alkane mixture
analysis with FTIR. Then, the proposed methods compared with gas chromatograph (GC), normally regarded
as the standardway for quantitative gas analysis, are used for gas well logging to analyze the mixture of methane,
ethane, propane, iso-butane and n-butane on-line. By comparing the well logging curves obtained fromFTIRwith
the ones fromGC, it is shown that the logging curves analyzed with proposed method are good matches with the
ones obtained fromGC,which means that our analysis results are accurate. At the end of this paper, a calibration
transfer is used to calibrate additional 18 instrumentswith a fewsets of samples. And thework introduced in this
paper demonstrates that FTIR can also be used in analyzing multi-component gas with close molecular structure
accurately and the analyzer can be produced in mass. |
(创新港)
