Intelligent identification method of two-phase flow pattern based on principal component analysis and support vector machine
Through the combination of principal component analysis and support vector machine, the problem of gas-liquid two-phase flow type recognition in porous media is solved, and fast and accurate flow type recognition is achieved, which reduces the calculation amount and improves the recognition accuracy. It is suitable for gas-liquid two-phase flow type detection in porous media.
Patent Information
- Application Number
- CN202310306889.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-03-27
- Publication Date
- 2025-08-12
- Estimated Expiration
- 2043-03-27
AI Technical Summary
The prior art is difficult to quickly and accurately identify the two-phase flow patterns of gas-liquid flow in porous media, and research has been mainly focused on conventional pipelines and cannot be effectively applied to porous media structures.
The method of combining principal component analysis and support vector machine is adopted to construct coupled feature vectors through pressure differential signal acquisition, time domain and frequency domain analysis, and feature extraction, and flow type recognition is used by support vector machines to achieve intelligent gas-liquid two-phase flow flow type recognition in porous media.
It realizes rapid and accurate identification of two-phase gas-liquid flow patterns in porous media, reduces the calculation amount, improves the recognition accuracy, and provides technical support for actual industrial production.
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Abstract
Citation Information
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