Please use this identifier to cite or link to this item:
Title: Prediction of fabric hand characteristics using extraction principle
Authors: Das, Apurba
Majumdar, Abhijit
Roy, Sukumar
Keywords: Artificial neural network;Nozzle extraction;Fabric handle;Extraction force;Shear force
Issue Date: Mar-2016
Publisher: NISCAIR-CSIR, India
Abstract: Prediction of fabric handle characteristics using extraction principle has been studied. An instrument for objective measurement of fabric handle characteristics has been developed using nozzle extraction method. This instrument measures the force exerted on the periphery of the nozzle by the fabric being drawn out of the nozzle on the periphery of the nozzle. This force, called the radial force, is a measure of the certain low stress mechanical characteristics of the fabric that determine handle. The instrument also measures the force required to extract the fabric through the nozzle. Woven fabric samples have been sourced from industry and categorized into suiting and shirting fabrics. The fabric samples were also tested in KES-F system. An attempt has been made to predict the shear force and bending rigidity by using artificial neural network. It has been observed that there are very good correlations between the extraction force values and the various KES-F parameters. The fabric extraction force obtained through nozzle extraction instrument is found to be well enough to predict fabric handle/feel value.
Page(s): 33-39
ISSN: 0975-1025 (Online); 0971-0426 (Print)
Appears in Collections:IJFTR Vol.41(1) [March 2016]

Files in This Item:
File Description SizeFormat 
IJFTR 41(1) 33-39.pdf241.93 kBAdobe PDFView/Open

Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.