Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline

The desire to satisfy demand of industrial sector by improving product quality and reducing environmental emission leads up to identify and monitor the behaving of the internal flows inside pipelines. The flow of solid particles through pipeline in vertical gravity flow rig system has been monitored...

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Main Author:	Elsawi Khairalla, Mutaz Mohamed Elhassan
Format:	Thesis
Language:	English
Published:	2012
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/34693/1/MutazMohamedElhassanElsawiKhairallaMFKE2012.pdf
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id	my-utm-ep.34693
record_format	uketd_dc
spelling	my-utm-ep.346932021-07-21T01:52:15Z Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline 2012 Elsawi Khairalla, Mutaz Mohamed Elhassan TK Electrical engineering. Electronics Nuclear engineering The desire to satisfy demand of industrial sector by improving product quality and reducing environmental emission leads up to identify and monitor the behaving of the internal flows inside pipelines. The flow of solid particles through pipeline in vertical gravity flow rig system has been monitored by 16-electrodynamic sensors that measure the charge carried by solid particles. The identification model has been built and developed based on the training of the captured data at different flow patterns. The final identification model consists of four ANFIS based fuzzy C-means clustering where every ANFIS is able to identify the presence of the flow inside specific quarter in the cross section of the pipe. It is shown that the four ANFIS models are able to work simultaneously to provide the expected output after applying simple thresholding for the ANFIS’ output. The identification model has been evaluated by ten different types of flow patterns. The accuracy of the identification model has improved at higher flow rate. As a result, the identified flow pattern has been used to acquire the concentration profile by using filtered back projection. The successful ANFIS model can be extended for horizontal pipeline to present the percentage of flow inside the pipe. 2012 Thesis http://eprints.utm.my/id/eprint/34693/ http://eprints.utm.my/id/eprint/34693/1/MutazMohamedElhassanElsawiKhairallaMFKE2012.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:83152?queryType=vitalDismax&query=+Neuro-fuzzy+technique+application+for+identifying+flow+regimes+of+particles+conveying+in+pneumatic+pipeline++&public=true masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Elsawi Khairalla, Mutaz Mohamed Elhassan Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
description	The desire to satisfy demand of industrial sector by improving product quality and reducing environmental emission leads up to identify and monitor the behaving of the internal flows inside pipelines. The flow of solid particles through pipeline in vertical gravity flow rig system has been monitored by 16-electrodynamic sensors that measure the charge carried by solid particles. The identification model has been built and developed based on the training of the captured data at different flow patterns. The final identification model consists of four ANFIS based fuzzy C-means clustering where every ANFIS is able to identify the presence of the flow inside specific quarter in the cross section of the pipe. It is shown that the four ANFIS models are able to work simultaneously to provide the expected output after applying simple thresholding for the ANFIS’ output. The identification model has been evaluated by ten different types of flow patterns. The accuracy of the identification model has improved at higher flow rate. As a result, the identified flow pattern has been used to acquire the concentration profile by using filtered back projection. The successful ANFIS model can be extended for horizontal pipeline to present the percentage of flow inside the pipe.
format	Thesis
qualification_level	Master's degree
author	Elsawi Khairalla, Mutaz Mohamed Elhassan
author_facet	Elsawi Khairalla, Mutaz Mohamed Elhassan
author_sort	Elsawi Khairalla, Mutaz Mohamed Elhassan
title	Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
title_short	Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
title_full	Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
title_fullStr	Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
title_full_unstemmed	Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
title_sort	neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2012
url	http://eprints.utm.my/id/eprint/34693/1/MutazMohamedElhassanElsawiKhairallaMFKE2012.pdf
_version_	1747816236408897536

Neuro-fuzzy technique application for identifying flow regimes of particles conveying in pneumatic pipeline

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