Study on Measurement Method of Droplet Content in Natural Gas Pipeline Based on Curved Surface Probe Microwave Sensor (CSPMS)
The extraction of natural gas often results in the formation of a considerable number of droplets within the pipeline, particularly in underground storage reservoirs. These droplets, present at the micrometer level within the pipeline, not only impede the efficient transmission of the gas but also corrode and damage the pipeline via an electrochemical reaction with induced substances. In the case of China’s West-East Gas Transmission Project Department, for example, excessive droplet content in natural gas has caused several abnormal compressor shutdowns. The conventional offline mass method necessitates the subsequent weighing and analysis of the sample after sampling, a process that is plagued by significant latency and is incapable of meeting the demand for rapid measurement. This article proposes a curved surface probe microwave sensor (CSPMS) for gas storage reservoir extraction wells, a solution that facilitates the expeditious real-time measurement of droplet content in natural gas pipelines. The CSPMS model was developed using COMSOL and subsequently optimized. The accuracy of the CSPMS test prototype was verified through a combination of simulation and experimental testing. The findings indicate that the CSPMS test prototype exhibits heightened sensitivity in comparison to the prevailing microwave measurement techniques. The CSPMS test prototype facilitates the expeditious measurement of alterations in droplet content within the pipeline through <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${S}_{{11}}$ </tex-math></inline-formula> parameter changes and resonant frequency offsets. This will provide crucial reference guidance for the safe and stable operation of natural gas pipelines.
Authors
- Qiaoqi Xu
- X. Zhong (ORCID: https://orcid.org/0000-0002-1751-111X)
- Tianye He
- J. Chen (ORCID: https://orcid.org/0000-0002-6797-3750)
- Jianxia Liu (ORCID: https://orcid.org/0000-0001-5944-371X)
- Ao Li (ORCID: https://orcid.org/0000-0001-6597-4349)
- Tianyu Zhang (ORCID: https://orcid.org/0000-0002-6501-7562)
- Zhen Liu (ORCID: https://orcid.org/0000-0002-0108-386X)
- Zhongli Ji (ORCID: https://orcid.org/0009-0009-9216-4072)
- Qi Huang
Institutions
- Gas Turbine Research Establishment (IN)
- China University of Petroleum, Beijing (CN)
- Purdue University West Lafayette (US)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1109/jsen.2025.3552522
- Citations
- 1
- Primary Topic
- Icing and De-icing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 4.99
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China