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Analysis and Tensile-Tear Properties of Abraded Denim Fabrics Depending on Pattern Relations Using Statistical and Artificial Neural Network Models
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  • Analysis and Tensile-Tear Properties of Abraded Denim Fabrics Depending on Pattern Relations Using Statistical and Artificial Neural Network Models
  • Analysis and Tensile-Tear Properties of Abraded Denim Fabrics Depending on Pattern Relations Using Statistical and Artificial Neural Network Models
저자명
Bilisik. Kadir,Demiryurek. Oguz
간행물명
Fibers and polymers
권/호정보
2011년|12권 3호|pp.422-430 (9 pages)
발행정보
한국섬유공학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The aim of this study is to develop new pattern denim fabrics and characterize the mechanical properties of these fabrics after abrasion load. Furthermore, tensile and tear strengths of these fabrics have been analysed by using the Artificial Neural Network (ANN) and statistical model. All denim fabrics were first abraded and subsequently tensile and tearing tests were applied to the abraided fabrics seperately. Actual data generated from the tests were analyzed by ANN and regression model. The regression model has shown that tensile strength properties of the abraded large structural pattern denim fabrics are generally low compared to that of the small structural pattern and traditional denim fabrics. On the other hand, when the abrasion cycles are increased tensile properties of all denim fabrics are generally decreased. Tearing strength of weft and warp in the abraded large structural pattern denim fabrics are between small structural pattern and traditional denim fabric. On the other hand, when the abrasion cycles are increased tearing strength properties in the weft and warp for all denim fabrics are generally decreased. The results from ANN and regression models were also compared with the measured values. It is concluded that almost all values from ANN are accurately predicted compared with those of the regression model. Therefore, we suggest that both methods can be used in this study as viable and reliable tools.