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157722

Application of Artificial Neural Network in Predicting Circular Knitted Fabric Appearance.

Article

Last updated: 22 Jan 2023

Subjects

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Tags

Textile Engineering

Abstract

The main purpose of this paper is to develop a system to predict the amount of cloudiness and non-homogeneous appearance of the circular knitted fabric, by utilizing the various cotton yarn quality characteristics which produced that fabric.
A novel approach was developed using Artificial Neural Network (ANN) and satisfied results were obtained. A learning phase for the system was initially conducted on circular knitting machine fitted with an image processing system to capture an on-line image of the weft knitted fabric which was produced using one yarn cone (the machine was modified and adapted to use one cone instead of 24 yarn cones) in order to eliminate yarn cone to cone variation and to differentiate between 14 different typesof yarn from 14 different producers, All kinds of physical tests on yarn quality characteristics were conducted on the yarns in order to be used as a comprehensive input set of data for the prediction of the appearance and cloudiness of knitted fabric. The developed (ANN) System was successfully capable of predicting the appearance and cloudiness with satisfied agreement with actual results.

DOI

10.21608/bfemu.2021.157722

Authors

First Name

Ihab

Last Name

El-Sayed

MiddleName

-

Affiliation

Faculty of Engineering., Jazan University., Kingdom of Saudi Arabia.

Email

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City

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Orcid

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Volume

34

Article Issue

3

Related Issue

18584

Issue Date

2009-09-01

Receive Date

2009-07-11

Publish Date

2021-03-18

Page Start

1

Page End

10

Print ISSN

1110-0923

Online ISSN

2735-4202

Link

https://bfemu.journals.ekb.eg/article_157722.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=157722

Order

11

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

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Details

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Article

Created At

22 Jan 2023