Use of Artificial Neural Networks for Modelling of Seam Strength and Elongation at Break

• Autorzy: Yildiz Z. , Dal V. , Ünal M. , Yildiz K.

Warianty tytułu

PL

Zastosowanie sztucznych sieci neuronowych dla modelowania wytrzymałości szwów i wydłużenia przy zerwaniu

• Języki publikacji: EN

Abstrakty

EN

The strength and elongation at break of a seam are very important characteristics of comfort clothing. Optimum seam strength must be durable enough to do our daily activities easily. Some parameters such as the type and count of the sewing yarn, the seam density, the size of the sewing needle, and type of stitch affecting the strength and elongation at break of the seam. In this study two kinds of fabrics (gabardine and poplin) were chosen for experiments. As sewing parameters, two different types of stitches (plain and chain stitch), five seam densities (3, 4, 5, 6 and 7 seams/cm), two kinds of sewing needles (SPI and SES), and three kinds of sewing yarns (cotton, core-spun, and PBT yarns) were used in experiments. With these materials 120 different seam variations were developed. Each sampless seam strength was tested according to the ISO 13935-1[1] standard using an Instron 4411 instrument. After the testing process, an artificial neural network model was developed to predict the seam strength and elongation at break values. The test results were applied to multi layer perceptron and radial basis function neural network modeling. These two neural network types were compared in terms of the accuracy of the modeling system. The results show that the artificial neural network model produces reliable estimates of seam strength and elongation at break (R=1, MSE=3.33E-05).

PL

Wytrzymałość szwu i wydłużenie przy zerwaniu są bardzo ważnymi cechami ubrań z punktu widzenia wygody noszenia. Optymalna wytrzymałość szwu musi być wystarczająco duża, aby z łatwością wykonywać nasze codzienne czynności. Niektóre z parametrów, takich jak typ oraz numer przędzy, gęstość szwu, rozmiar igły do szycia, typ ściegu wpływają na wytrzymałość szwu i wydłużenie przy zerwaniu. Badania przeprowadzono na dwóch rodzajach tkanin (gabardyna i popelina), stosując dwa różne rodzaje szwów (proste i łańcuszkowy), szwy o pięciu gęstościach (3, 4, 5, 6 i 7 szwy/cm), dwa rodzaje igieł (SPI i SES) i trzy rodzaje przędz (bawełniana zwykła, rdzeniowa i przędze PBT), otrzymując 120 wariantów szwów. Wytrzymałość każdej próbki została zbadana zgodnie z normą ISO 13935-1 za pomocą przyrządu Instron 4411. Następnie, opracowano model sztucznej sieci neuronowej w celu przewidzenia wartości wytrzymałości szwów i wydłużenia przy zerwaniu. Wyniki badań zostały przetworzone w wielowarstwowym perceptronie i funkcji radialnej modelowania sieci neuronowej. Obydwa typy sieci neuronowych zostały porównane pod względem dokładności modelowania. stwierdzono, że za pomocą modelu sztucznych sieci neuronowych można uzyskać wiarygodne wyniki (R = 1, MSE = 3.33E-05).

Słowa kluczowe

EN

textile fabrics; artificial neural networks; seam strength; modeling

PL

tekstylia; sztuczne sieci neuronowe; szew wytrzymałościowy; modelowanie; wydłużenia przy zerwaniu

• Wydawca: Sieć Badawcza Łukasiewicz - Łódzki Instytut Technologiczny
• Czasopismo: Fibres & Textiles in Eastern Europe
• Rocznik: 2013
• Tom: Vol. 21, no. 5 (101)
• Strony: 117--123
• Opis fizyczny: Bibliogr. 32 poz., rys., tab.

Twórcy

autor

Yildiz Z.

• Department of Textile Education, Faculty of Technical Educationn, University of Marmara, Istanbul, Turkey

autor

Dal V.

• Department of Textile Education, Faculty of Technical Educationn, University of Marmara, Istanbul, Turkey

autor

Ünal M.

• Department of Electronic-Computer Education, Faculty of Technical Educationn, Marmara University, Istanbul, Turkey

autor

Yildiz K.

• Department of Electronic-Computer Education, Faculty of Technical Educationn, Marmara University, Istanbul, Turkey

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