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Applying Artificial Neural Network Model on Investigating the Fiber Diameter of Polybutylene Terephthalate (PBT) Spunbonding Nonwovens: Comparison with Mathematical Statistical Method

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Abstract:

In this paper, two models are founded and introduced to predict the fiber diameter of polybutylene terephthalate spunbonding nonwovens from the spunbonding process parameters. The results indicate the artificial neural network model has good approximation capability and fast convergence rate, and it can provide quantitative predictions of fiber diameter and yield more accurate and stable predictions than the mathematical statistical method. This area of research has great potential in the field of computer assisted design in spunbonding technology.

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Periodical:

Key Engineering Materials (Volumes 426-427)

Pages:

692-696

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.426-427.692

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Online since:

January 2010

Authors:

Bo Zhao

Keywords:

Artificial Neural Network Model, Fiber Diameter, Mathematical Statistical Method, Polybutylene Terephthalate, Spunbonding Nonwoven

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© 2010 Trans Tech Publications Ltd. All Rights Reserved

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