Study on hybrid yarns integrity through image processing and artificial intelligence techniques

Abstract

The commingled hybrid yarns of different structures have been used to investigate the variation in their abrasion resistance over those of simple yarns by calculating the abrasion destruction index. The cotton yarns of the counts 20Ne and 30Ne and cotton-polyester yarns  of the same counts (20Ne and 30Ne) at 20, 40 and 60 bar pressure, have been commingled using flat and textured polyester yarns of 150 den. The produced samples are then abraded by a standard metallic object at four different stages including 150 abrasion cycles in each stage. Through image analyzing technique, the abrasive damage of the samples has been investigated and the abrasion indexes are calculated. The Kohonen neural network is used to cluster the samples in 5 classes as per their abrasion resistance. The cotton-polyester yarn (30Ne), hybrid samples from cotton (30Ne) and textured polyester at 20, 40 and 60 bar; and the hybrid yarn made from cotton-polyester (30Ne) and flat polyester at 60 bar are found to be the best. Furthermore, the abrasion resistance of samples improves on increasing the pressure of commingling process. Generally, cotton yarn and textured polyester yarn show the better abrasion resistance in comparison with the other samples.