An Approach to Spunlace Fabrics: A Prediction on the Tensile Strength Using Artificial Neural Network and the Improvement of the Production Quality Using Fuzzy-Logic Controller

Abstract

In this study, firstly, the tensile strength of the spunlace fabric has been estimated by Artificial Neural Networks (ANN) method. For this purpose, an artificial neural network model was developed by taking the tensile strength values of spunlace fabric samples as reference values. In the production of spunlace fabric with water jet, it is the water jet that provides the mechanical bonding of the fibers and hence affects directly the breaking and tearing strength values of the fabric. The water jet pressure is controlled by pressure sensors, and a blockage in the water jet causes the pressure sensors to measure incorrectly and, as a result, a quality failure. In this respect, secondly aim of this study is to conceive a method to controller the water jet pressure using a fuzzy-logic controller (FLC) instead of pressure sensor control. During the production, the DC electric motor revolutions used in the water jet were kept constant by the fuzzy logic controller according to these reference values. And hence, it was provided that the strength quality of the spunlace fabric were maintained.