An Investigation Of Using Grey Scale Image Analysis For Predicting The Amount Of Deposited Electrospun Nanofibres

Abdul Hamid, Nurfaizey and Mohd Daud, Mohd Ahadlin and Muhammad, Noryani and Mansor, Muhd Ridzuan and Che Long, Faizah and Tucker, Nick (2019) An Investigation Of Using Grey Scale Image Analysis For Predicting The Amount Of Deposited Electrospun Nanofibres. Journal of Mechanical Engineering and Sciences, 13 (1). pp. 4679-4692. ISSN 2289-4659

Text 2019 AN INVESTIGATION OF USING GREY SCALE IMAGE ANALYSIS FOR PREDICTING THE AMOUNT OF DEPOSITED ELECTROSPUN NANOFIBRES.PDF Download (515kB)

Abstract

When electrospinning, the amount of electrospun fibres deposited is difficult to determine due to the extremely small size and light weight of the fibres. Several methods have been used to predict the amount of deposited fibres including weighing, imaging and direct measurement. Yet, these methods have drawbacks that make them unsuitable for commercial scale process control. In this study, an image analysis method is used to predict the amount of deposited fibres over a significant area. When images of electrospun fibres are converted into grey scale images, it is suggested that the amount of fibres deposited can be predicted by measuring the grey scale intensity. Weighing method was used to validate the image analysis results. Weighing method was found wanting when the deposition time was short (p>0.05) due to the insignificant fibre masses compared to the variation of substrates. The results suggest that image analysis method could be used to predict the amount of deposited electrospun nanofibres. Test on different polymers and substrates showed that the method was still capable to distinguish the samples. The developed method has the potential to be applied as an in-line non-destructive quality control method for electrospun fibre manufacture.

Item Type:	Article
Uncontrolled Keywords:	Electrospinning, Electrospun nanofibres, Grey scale, Image analysis
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	03 Dec 2020 09:07
Last Modified:	03 Dec 2020 09:07
URI:	http://eprints.utem.edu.my/id/eprint/24809
Statistic Details:	View Download Statistic

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