Prediction of Fabric Tensile Strength By Modelling the Woven Fabric

Özetçe-Sıvı gıda imalatının gerçekleştirildiği işletmelerdeTetra Brik Aseptik karton paketlerdeki şerit dikişlerin kalite kontrol işlemi uzman işçiler tarafından geleneksel şekillerde yapılmaktadır. Bu denetim süreci insana dayalı olduğu için birçok dezavantaja sahiptir. Bu çalışmada, çeşitli görüntü işleme teknikleri kullanılarak karton paketlerdeki şerit dikişlerin kalite kontrolünün bilgisayar destekli bir sistem aracılığıyla yapılabilmesi amaçlanmıştır. Piksel-bazlı görüntü bölütleme ve Çok Katmanlı Sinir Ağı modeli bir arada kullanılmış ve DİMES firmasından sağlanan karton paketlerin görüntüleri üzerinde test edilmiştir. Sunulan sistemin sonuçları tatmin edici düzeyde bulunmuş ve gelecek çalışmalar için önerilerde bulunulmuştur. Anahtar Kelimeler-Tetra brik aseptik karton paket, görüntü işleme, piksel-bazlı görüntü bölütleme, enine şerit dikişler, kalite kontrolü.Abstract-The quality control process of the seal seams at Tetra Brik Aseptic carton package is traditionally performed by specialized workers in liquid food manufacturing businesses. Because it is based on the people, this control process has many drawbacks. In this study, it is aimed to perform the quality control of seal seams at carton package by a computer-aided system. Pixel-based image segmentation and Multi Layer Neural Network methods were used together, and it is tested on the images of carton packages provided by DIMES company. The results of the presented system were found to be satisfactory, and the recommendations are provided for the future studies. Keywords-Tetra Brik Aseptic carton package, image processing, pixel-based image segmentation, transversal seal seams, quality control.

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Prediction of Mechanical Properties of Woven Fabrics by ANN

ElKateb

2022

Fibres &Amp; Textiles in Eastern Europe

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This study aims to obtain an accurate prediction model of mechanical properties of woven fabric to achieve customer satisfaction. Samples of plain woven fabric were produced from different yarn counts and blend ratios of cotton and polyester of weft yarn at different weft densities. Mechanical properties such as tensile strength, bending stiffness and elongation% in both the warp and weft directions were tested. The prediction model was based on Artificial Neural Networks (ANNs). For each model, thirty-nine samples were used for training and fifteen for testing prediction performance. Findings indicated that the ANN achieved a perfect performance in predicting all properties.

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Prediction of Fabric Tensile Strength By Modelling the Woven Fabric

Cited by 4 publications

References 36 publications

Influence of Textile Fabrics Structures on Thermal, UV Shielding, and Mechanical Properties of Textile Fabrics Coated with Sustainable Coating

Influence of Textile Fabrics Structures on Thermal, UV Shielding, and Mechanical Properties of Textile Fabrics Coated with Sustainable Coating

Imaging processing based quality control of transversal seams in Tetra Brik Aseptic cartons

Prediction of Mechanical Properties of Woven Fabrics by ANN

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