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Identification of Natural Gas Components Using the Support Vector Machine Model

  • INNOVATIVE TECHNOLOGIES OF OIL AND GAS
  • Published:
Chemistry and Technology of Fuels and Oils Aims and scope

Identification of natural gas components is vital for the natural gas measurement and determination of the gas flow. The accurate evaluation of the natural gas composition is particularly vital for thermal methods of measurement. The thermal measurement principle is the focus of the current research and development trend of natural gas control technology. Therefore, in this study, we propose a method based on principal component analysis. To eliminate the partial correlation error between the samples and retain maximum information, the dimensionality reduction and pre-classification methods are performed on the data obtained by analyzing the physical parameters of the target natural gas. To reduce the input into the network and ensure recognition efficiency, the new samples are used as the input for the support vector machine. The method can be applied for providing an accurate classification of the existing types of natural gas and obtaining reliable data for thermal metering methods.

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Acknowledgments

This research work was financially supported by the Chongqing Research Program of Basic Research and Frontier Technology (cstc2018jcyjAX0519), Artificial Intelligence Key Laboratory of Sichuan Province (2020RYY01), and Sichuan Provincial Key Lab of Process Equipment and Control (GK201801).

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Authors and Affiliations

  1. College of Mechanical Engineering, Sichuan University of Science and Engineering, Zigong, 643000, China

    Bo Huang, Zegang Sun & Fuzhong Zheng

  2. School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, 401331, China

    Tao Peng, Yuan Zhai, Jinliang Shi & Ying Wu

  3. Jiangsu Province Laboratory of Mining Electric and Automation, China University of Mining and Technology, Xuzhou, 221008, China

    Chenyang Xia

Authors
  1. Bo Huang
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  2. Tao Peng
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  3. Chenyang Xia
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  4. Yuan Zhai
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  5. Jinliang Shi
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  6. Zegang Sun
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  7. Fuzhong Zheng
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  8. Ying Wu
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Corresponding authors

Correspondence to Fuzhong Zheng or Ying Wu.

Additional information

Translated from Khimiya i Tekhnologiya Topliv i Masel, No. 4, pp. 109–115, July–August, 2021.

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Huang, B., Peng, T., Xia, C. et al. Identification of Natural Gas Components Using the Support Vector Machine Model. Chem Technol Fuels Oils 57, 713–723 (2021). https://doi.org/10.1007/s10553-021-01297-w

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  • DOI: https://doi.org/10.1007/s10553-021-01297-w

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