DocumentCode :
1964036
Title :
Natural gas infrared spectrum analysis based on multi-level and SVM-subset
Author :
Bai, Peng ; Duan, Xiaohu ; He, Changlong ; Li, Yan
Author_Institution :
Inst. of Sci., Air Force Eng. Univ., Xi´´an
fYear :
2009
fDate :
11-13 May 2009
Firstpage :
336
Lastpage :
339
Abstract :
Since non-linearity is obviously characteristic of natural gas analysis, and few ideal spectrum data samples can be actually obtained from the mass natural gas, the accuracy level of concentrating each component in the natural gas turns out to be far from high. In response to the dilemma above, a multi-level- and SVM-subset- based infrared spectrum analyzing method is proposed for the analysis of natural gas. According to the idea of natural gas distribution pattern recognitionrarrnatural gas analysis rarrresult output, the new analyzing method, as based on multi-level and SVM subset, consists of two levels: the pattern recognition level as well as the analysis and the result output level. The pattern recognition level serves to identify the natural gas distribution pattern, whereas the analysis and the result output level is the concrete natural gas component concentration analysis and the result output level, with the established SVM calibration model designed to analyze and calculate the natural gas component concentration. The experimental results show that the component concentration maximal deviation is 0.49% and maximal average deviation is 0.059%. The method can work for other natural gas infrared spectrum analyses, and therefore has the theoretic and application value.
Keywords :
calibration; chemical analysis; chemical engineering computing; infrared spectra; natural gas technology; pattern recognition; support vector machines; SVM-subset; calibration model; component concentration analysis; multilevel subset; natural gas infrared spectrum analysis; pattern recognition level; Calibration; Concrete; Force measurement; Infrared spectra; Natural gas; Pattern analysis; Pattern recognition; Probability; Support vector machine classification; Support vector machines; SVM; infrared; natural gas; spectrum analysis; subset;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Virtual Environments, Human-Computer Interfaces and Measurements Systems, 2009. VECIMS '09. IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1944-9410
Print_ISBN :
978-1-4244-3808-2
Electronic_ISBN :
1944-9410
Type :
conf
DOI :
10.1109/VECIMS.2009.5068920
Filename :
5068920
Link To Document :
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