|Table of Contents|

Flow Pattern Identification Based on Neural Network in ERT System

《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

Issue:
2008年06期
Page:
31-34
Research Field:
计算机与控制工程
Publishing date:

Info

Title:
Flow Pattern Identification Based on Neural Network in ERT System
Author(s):
SHEN Chao-qun WEI Hui-yu CHEN De-yun
(School of Computer Science and Technology, Harbin University of science and Technology, Harbin 150080, China)
Keywords:
electrical resistance tomography flow pattern neural network fuzzy neural network
PACS:
-
DOI:
-
Abstract:
In the investigation of the two -phase flow measurement, the exact identification of flow regime is the foundation of other parameter exact measurement, therefore, the relatively high rate of flow pattern identification is goal of this study. The research in this paper is based on 12 - electrode resistance imaging system, First, fuzzy clustering is adopted to fuzzy the measurement voltage data of the ERT system, then the fuzzy data is taken as input information of the BP network, the fuzzy data of measure voltage are trained repeatedly in BP network, so the four kinds of two - phase flow regime can be identified. Through the experiment simulation analysis, the four kinds of flow regime' s recognition rate is up to 89.4%, veracity of the flow pattern identification is imoroved.

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Last Update: 2017-06-27