Keywords:FTIR Multi-component alkane mixture On-line quantitative analysis Feature extraction and selection Calibration transfer 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 standard way 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 from FTIR with the ones from GC, it is shown that the logging curves analyzed with proposed method are good matches with the ones obtained from GC, which means that our analysis results are accurate. At the end of this paper, a calibration transfer is used to calibrate additional 18 instruments with a few sets of samples. And the work 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.
Currently, the oil-immersed power transformer on-site detecting and analysis systems for dissolved gas analysis (DGA) were usually based on the gas chromatography, electrochemical sensor array or other sensors. But these methods had the defects such as needing standard carrier gas, regularly instrument calibration, low security, long analysis time and so on. For these reasons, an innovative method of using Fourier transform infrared (FTIR) instrument to detecting and analysis the transformer oil dissolved gas was proposed in this paper. This method has the features, such as maintenance free, no carrier gas in site, analysis time shortly (time constant below one second is possible). The detecting and analysis system was consisted by the oil sample continuous automatic collection device, oil dissolved gases separation equipment, gases analytical instruments (FTIR), data acquisition and processing module. The situation of the transformer in-site operation was simulated and a complete experimental system was set up in the laboratory. When we used the FTIR to analyze the gases on site for a long time and continuously, some key technologies (spectral baseline drift and distortion, dimension reduction and so on) needed to resolve. For the spectral baseline drift and distortion problem, the spectral baseline correction by piecewise dividing (SBCPD) baseline correction algorithm was used to preprocess the spectral data. For the problem of high-dimensional data characteristic variables selection in the spectral analysis, Tikhonov regularization algorithm was used to select spectral features variable. After the above step, the dimensions of the original spectrum was reduced from 10165 to 3~7, the computing workload was greatly reduced and the accuracy of the calculation results was improved. Finally, the sparse partial least squares algorithm was adopted to establish the quantitative analysis model of transformer dissolved gas analysis on-line monitoring system, and 7 kinds of mixed gases were analyzed. The results showed that the sparse partial least squares algorithm was superior to the traditional partial least squares algorithm. The feasibility of Fourier transform infrared spectroscopy for oil dissolved gas multi-component on-line detection and analysis system was preliminary verified by the simulation and experiment system in the laboratory. Keywords-Fourier Transform infrared spectroscopy; dissolved gas analysis; oil-immersed power transformer; sparse partial least squares
In view of the existing virtual experimental teaching software is primarily demonstration, the lack of the people of the interactive system, the lack of authenticity in the process of simulation experiment teaching. In this paper, the development of 3 d virtual teaching laboratory based on virtools platform, in the process of chemistry teaching experiment, for example, and describes the development of the basic steps and key technology. Through the campus network, many people online at the same time condition test, has the feasibility to good effect.
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