A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi

Santhosh Krishnan Venkata, Binoy Krishna Roy

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

Original languageEnglish
Pages (from-to)31-39
Number of pages9
JournalJournal of The Institution of Engineers (India): Series B
Volume97
Issue number1
DOIs
Publication statusPublished - 01-03-2016

Fingerprint

Flow measurement
Density of liquids
Calibration
Neural networks
Networks (circuits)
Nozzles
Pipe
Liquids
Temperature
Electric potential

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

@article{940ac772d66d489cb67c5e3e9e2cecc8,
title = "A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi",
abstract = "Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 {\%} of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.",
author = "Venkata, {Santhosh Krishnan} and Roy, {Binoy Krishna}",
year = "2016",
month = "3",
day = "1",
doi = "10.1007/s40031-015-0187-3",
language = "English",
volume = "97",
pages = "31--39",
journal = "Journal of The Institution of Engineers (India): Series B",
issn = "2250-2106",
publisher = "Springer India",
number = "1",

}

TY - JOUR

T1 - A Practically Validated Intelligent Calibration Circuit Using Optimized ANN for Flow Measurement by Venturi

AU - Venkata, Santhosh Krishnan

AU - Roy, Binoy Krishna

PY - 2016/3/1

Y1 - 2016/3/1

N2 - Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

AB - Design of an intelligent flow measurement technique using venturi flow meter is reported in this paper. The objectives of the present work are: (1) to extend the linearity range of measurement to 100 % of full scale input range, (2) to make the measurement technique adaptive to variations in discharge coefficient, diameter ratio of venturi nozzle and pipe (β), liquid density, and liquid temperature, and (3) to achieve the objectives (1) and (2) using an optimized neural network. The output of venturi flow meter is differential pressure. It is converted to voltage by using a suitable data conversion unit. A suitable optimized artificial neural network (ANN) is added, in place of conventional calibration circuit. ANN is trained, tested with simulated data considering variations in discharge coefficient, diameter ratio between venturi nozzle and pipe, liquid density, and liquid temperature. The proposed technique is then subjected to practical data for validation. Results show that the proposed technique has fulfilled the objectives.

UR - http://www.scopus.com/inward/record.url?scp=85029815384&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85029815384&partnerID=8YFLogxK

U2 - 10.1007/s40031-015-0187-3

DO - 10.1007/s40031-015-0187-3

M3 - Article

AN - SCOPUS:85029815384

VL - 97

SP - 31

EP - 39

JO - Journal of The Institution of Engineers (India): Series B

JF - Journal of The Institution of Engineers (India): Series B

SN - 2250-2106

IS - 1

ER -