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- W2369072282 abstract "To study the flow regime of gas-liquid two-phase in vertical upward pipe,the conductance fluctuation information of four typical flow regimes was collected by measuring system with self-made multiple conductance probes.Since the wavelet packet transform has the characteristic of decomposing conductance fluctuation signals to any frequency bands,the collected conductance fluctuation signals were decomposed into three-layer wavelet packets,and the information entropy eigenvectors in various frequency range were calculated,then Elman neural network was trained using the eigenvectors as feature parameters and the flow regime intelligent identification was realized.The results show that such method can well identify the four flow regimes,and can abstract characters conveniently.Therefore,a kind of powerful approach is supplied for the identification of flow regimes." @default.
- W2369072282 created "2016-06-24" @default.
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- W2369072282 date "2009-01-01" @default.
- W2369072282 modified "2023-09-26" @default.
- W2369072282 title "Method for identifying gas-liquid two-phase flow patterns based on multi-scale information entropy feature" @default.
- W2369072282 hasPublicationYear "2009" @default.
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