Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement

Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement

An attempt to use differential pressure induced by control valve for flow measurement has been proposed. The flow rate obtained by NFM model is closer to the actual value with the maximum error being ± 3.28 %. In NNM model, the error is 92.2% in the lower flow and 4.39 % in the higher flow rate. The...

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Bibliographic Details
Main Authors: R. Kumar, P. Sivashanmugam
Format: Article
Language:English
Published: IFSA Publishing, S.L. 2009-10-01
Series:Sensors & Transducers
Subjects:
Flow measurement
NFM model
Control valve
Pressure drop
ARM 7 processor
Online Access:http://www.sensorsportal.com/HTML/DIGEST/october_09/P_506.pdf
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spelling doaj-f7c4bf36744d4ac49448f2aade49baf62020-11-24T23:14:12ZengIFSA Publishing, S.L.Sensors & Transducers2306-85151726-54792009-10-01109102128Neuro and Fuzzy Computing Approach for the Flow Sensorless MeasurementR. Kumar0P. Sivashanmugam1Modelling and Simulation Research Laboratory, Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli-620 015, IndiaModelling and Simulation Research Laboratory, Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli-620 015, IndiaAn attempt to use differential pressure induced by control valve for flow measurement has been proposed. The flow rate obtained by NFM model is closer to the actual value with the maximum error being ± 3.28 %. In NNM model, the error is 92.2% in the lower flow and 4.39 % in the higher flow rate. The air flow increases more linearly in NFM than NNM with valve position and pressure drops. ARM 7 processor used in this work is a high speed and low power consuming processor and this can be integrated with field bus, CAN bus and internet based system, which is being standardized internationally. http://www.sensorsportal.com/HTML/DIGEST/october_09/P_506.pdfFlow measurementNFM modelControl valvePressure dropARM 7 processor
collection DOAJ
language English
format Article
sources DOAJ
author R. Kumar
P. Sivashanmugam
spellingShingle R. Kumar
P. Sivashanmugam
Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
Sensors & Transducers
Flow measurement
NFM model
Control valve
Pressure drop
ARM 7 processor
author_facet R. Kumar
P. Sivashanmugam
author_sort R. Kumar
title Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
title_short Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
title_full Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
title_fullStr Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
title_full_unstemmed Neuro and Fuzzy Computing Approach for the Flow Sensorless Measurement
title_sort neuro and fuzzy computing approach for the flow sensorless measurement
publisher IFSA Publishing, S.L.
series Sensors & Transducers
issn 2306-8515
1726-5479
publishDate 2009-10-01
description An attempt to use differential pressure induced by control valve for flow measurement has been proposed. The flow rate obtained by NFM model is closer to the actual value with the maximum error being ± 3.28 %. In NNM model, the error is 92.2% in the lower flow and 4.39 % in the higher flow rate. The air flow increases more linearly in NFM than NNM with valve position and pressure drops. ARM 7 processor used in this work is a high speed and low power consuming processor and this can be integrated with field bus, CAN bus and internet based system, which is being standardized internationally.
topic Flow measurement
NFM model
Control valve
Pressure drop
ARM 7 processor
url http://www.sensorsportal.com/HTML/DIGEST/october_09/P_506.pdf
work_keys_str_mv AT rkumar neuroandfuzzycomputingapproachfortheflowsensorlessmeasurement
AT psivashanmugam neuroandfuzzycomputingapproachfortheflowsensorlessmeasurement
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