Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, y...Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, yarn diameter and linear density, and fabric structure. Selecting stitch density (wales per inch, course per inch) is essential to getting the appropriate fabric weight and desired quality. Usually, no rules or assumptions exist to get the desired stitch density in the finished fabric stage. Fifteen types of blended knit fabrics were prepared to conduct the study. The varying percentages of cotton, polyester, and elastane are incorporated in the blends. Regression analysis and regression ANOVA tests were done to predict the stitch density of finished fabrics. A suitable regression equation is established to get the desired results. The study also found that the stitch density value in the finished stage fabric decreases by approximately 15% compared to the stitch density in the grey fabric stage. This study will help the fabric manufacturers get the finished fabric stitch density in advance by utilizing the grey fabric stitch density data set. The author expects this research to benefit the knitting and dyeing industry, new researchers, and advanced researchers.展开更多
In the knitting industry the measurements of the stitch density and the stitch length are usually done manually, which may lead to lower efficiency and less definition and also bring subjective ideas into the test res...In the knitting industry the measurements of the stitch density and the stitch length are usually done manually, which may lead to lower efficiency and less definition and also bring subjective ideas into the test results. In order to improve the effect we can measure with Digital Image Processing Techniques. A piece of sample is scanned into computer and changed into a digital image, which is processed with media filtering. To acquire the power spectrum, the image in the spatial domain is converted into the frequency domain. Picking up the characteristic points describing the stitch density and the stitch length separately in the power spectra and reconstructing them, the values of the stitch density and the stitch length could be calculated. When measuring the stitch length, we should establish a geometric model of the stitch based en the digital image processing, which provides a method to transform the stitch length in the two-dimensien space into the three-dimensien space and to measure the value of the stitch length more accurately. This method also provides a new way to measure the stitch length without damaging the fabric.展开更多
文摘Stitch density is one of the critical quality parameters of knit fabrics. This parameter is closely related to other physical quality parameters like fabric weight, fabric tightness factor, fiber types, blend ratio, yarn diameter and linear density, and fabric structure. Selecting stitch density (wales per inch, course per inch) is essential to getting the appropriate fabric weight and desired quality. Usually, no rules or assumptions exist to get the desired stitch density in the finished fabric stage. Fifteen types of blended knit fabrics were prepared to conduct the study. The varying percentages of cotton, polyester, and elastane are incorporated in the blends. Regression analysis and regression ANOVA tests were done to predict the stitch density of finished fabrics. A suitable regression equation is established to get the desired results. The study also found that the stitch density value in the finished stage fabric decreases by approximately 15% compared to the stitch density in the grey fabric stage. This study will help the fabric manufacturers get the finished fabric stitch density in advance by utilizing the grey fabric stitch density data set. The author expects this research to benefit the knitting and dyeing industry, new researchers, and advanced researchers.
文摘In the knitting industry the measurements of the stitch density and the stitch length are usually done manually, which may lead to lower efficiency and less definition and also bring subjective ideas into the test results. In order to improve the effect we can measure with Digital Image Processing Techniques. A piece of sample is scanned into computer and changed into a digital image, which is processed with media filtering. To acquire the power spectrum, the image in the spatial domain is converted into the frequency domain. Picking up the characteristic points describing the stitch density and the stitch length separately in the power spectra and reconstructing them, the values of the stitch density and the stitch length could be calculated. When measuring the stitch length, we should establish a geometric model of the stitch based en the digital image processing, which provides a method to transform the stitch length in the two-dimensien space into the three-dimensien space and to measure the value of the stitch length more accurately. This method also provides a new way to measure the stitch length without damaging the fabric.
