TITLE

A research of dynamic compensation of coriolis mass flowmeter based on BP neural networks

AUTHOR(S)
Zheng, Dezhi; Peng, Peng; Fan, Shangchun
PUB. DATE
May 2013
SOURCE
Instruments & Experimental Techniques;May2013, Vol. 56 Issue 3, p365
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
As a resonate sensor, Coriolis Mass Flowmeter (CMF) provides a direct measurement of mass flow and is widely used in flow measurement field. However, defect of dynamic characteristics has become the main factor which restricts its further application in batch filling processes. Based on theoretical analysis, a dynamic compensation system, BP (Back-Propagation) neural network dynamic compensation method is designed in order to solve this problem. Adding a neural network dynamic compensation segment after the sensor's output, the method uses the gradient descent method with an additional momentum factor for neural network training. Studies have shown that this method greatly improves the dynamic characteristics of the Coriolis mass flowmeter.
ACCESSION #
88060375

 

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