On-line flow regime identification in pipeline-risers based on signals of incomplete cycles

Sui Feng Zou; Lie Jin Guo; Chen Xie; Tian Yao

On-line flow regime identification in pipeline-risers based on signals of incomplete cycles

Sui Feng Zou
, Lie Jin Guo
, Chen Xie
, Tian Yao

能源与动力工程学院

Xi'an Jiaotong University

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

A method based on signal analysis of incomplete cycles is studied for time reduction in flow regime recognition in pipeline-risers. Short signals of pressure and differential pressure in different stages of severe slugging are analyzed. Local flow characteristics are fused by SOM networks to describe the spatial feature of flow in the whole pipeline-riser system and distinguish the regime. Over 90% of stable and unstable regimes are correctly recognized within the velocity range of our experiment, thus the method is preliminary proven to be feasible.

源语言	英语
页（从-至）	1966-1970
页数	5
期刊	Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics
卷	36
期	9
出版状态	已出版 - 1 9月 2015

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title = "On-line flow regime identification in pipeline-risers based on signals of incomplete cycles",

abstract = "A method based on signal analysis of incomplete cycles is studied for time reduction in flow regime recognition in pipeline-risers. Short signals of pressure and differential pressure in different stages of severe slugging are analyzed. Local flow characteristics are fused by SOM networks to describe the spatial feature of flow in the whole pipeline-riser system and distinguish the regime. Over 90\% of stable and unstable regimes are correctly recognized within the velocity range of our experiment, thus the method is preliminary proven to be feasible.",

keywords = "Incomplete cycle, Network, Pipeline-riser, Real-time recognition, SOM neural, Unstable flow regime",

author = "Zou, \{Sui Feng\} and Guo, \{Lie Jin\} and Chen Xie and Tian Yao",

year = "2015",

month = sep,

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language = "英语",

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pages = "1966--1970",

journal = "Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics",

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TY - JOUR

T1 - On-line flow regime identification in pipeline-risers based on signals of incomplete cycles

AU - Zou, Sui Feng

AU - Guo, Lie Jin

AU - Xie, Chen

AU - Yao, Tian

PY - 2015/9/1

Y1 - 2015/9/1

N2 - A method based on signal analysis of incomplete cycles is studied for time reduction in flow regime recognition in pipeline-risers. Short signals of pressure and differential pressure in different stages of severe slugging are analyzed. Local flow characteristics are fused by SOM networks to describe the spatial feature of flow in the whole pipeline-riser system and distinguish the regime. Over 90% of stable and unstable regimes are correctly recognized within the velocity range of our experiment, thus the method is preliminary proven to be feasible.

AB - A method based on signal analysis of incomplete cycles is studied for time reduction in flow regime recognition in pipeline-risers. Short signals of pressure and differential pressure in different stages of severe slugging are analyzed. Local flow characteristics are fused by SOM networks to describe the spatial feature of flow in the whole pipeline-riser system and distinguish the regime. Over 90% of stable and unstable regimes are correctly recognized within the velocity range of our experiment, thus the method is preliminary proven to be feasible.

KW - Incomplete cycle

KW - Network

KW - Pipeline-riser

KW - Real-time recognition

KW - SOM neural

KW - Unstable flow regime

UR - https://www.scopus.com/pages/publications/84969263025

M3 - 文章

AN - SCOPUS:84969263025

SN - 0253-231X

VL - 36

SP - 1966

EP - 1970

JO - Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics

JF - Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics

IS - 9

ER -

On-line flow regime identification in pipeline-risers based on signals of incomplete cycles

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