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Modelling of the discharge coeffcient of differential pressure flowmeters by the support vector machine
https://doi.org/10.32446/0368-1025it.2022-4-37-42
Abstract
The article discusses a method for modeling the differential pressure flowmeters of using machine learning methods. In the proposed work, a model in the form of a support vector machine is used as the discharge coefficient of the orifice plate. The paper describes in detail the learning process of the proposed model, and discusses its structure for the discharge coefficient in the form of a support vector machine, provides training parameters. The paper also provides simulation results, both during training and during testing of the model, which confirm the effectiveness of the proposed alternative method of reproducing the discharge coefficient. The authors of the article presented a comparative analysis of the obtained model for the discharge coefficient in the form of a support vector machine with the values of the current Reader-Harris and Gallagher equation. The paper shows that the model of the discharge coefficient in the form of a support vector machine is not inferior in accuracy and efficiency to the current models, and allows improving the systems for measuring the flow rate of liquids and gases. The obtained research results for differential pressure flow measurement systems of gas are relevant, and are of interest for natural gas production, transportation and storage facilities.
About the Authors
Z. A. Dayev
Baishev University
Kazakhstan
Kazakhstan
Zhanat А. Dayev
Aktobe
G. E. Shopanova
Baishev University
Kazakhstan
Kazakhstan
Gulzhan E. Shopanova
Aktobe
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Review
For citations:
Dayev Z.A., Shopanova G.E. Modelling of the discharge coeffcient of differential pressure flowmeters by the support vector machine. Izmeritel`naya Tekhnika. 2022;(4):37-42. (In Russ.) https://doi.org/10.32446/0368-1025it.2022-4-37-42
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