This paper studies rotor spinning blended yam produced of spun silk and cashmere. Nine samples were spun, from three different opening rollers and different navels. According to the Uster test results of yam quality p...This paper studies rotor spinning blended yam produced of spun silk and cashmere. Nine samples were spun, from three different opening rollers and different navels. According to the Uster test results of yam quality properties, optimum selection is done by using analysis method of combining fuzzy decision-making and fuzzy pattern classification. Experimental plan is designed based on universal rotated experimental design, and the method of confined optimization is used to optimize the speed of opening roller, the speed of rotor and twist factor, according to the results of yam quality test by Uster.展开更多
The neural network spinning prediction model (BP and RBF Networks) trained by data from the mill can predict yarn qualities and spinning performance. The input parameters of die model are as follows: yarn count, diame...The neural network spinning prediction model (BP and RBF Networks) trained by data from the mill can predict yarn qualities and spinning performance. The input parameters of die model are as follows: yarn count, diameter, hauteur, bundle strength, spinning draft, spinning speed, traveler number and twist. And the output parameters are: yarn evenness, thin places, tenacity and elongation, ends-down. Predicting results match the testing data well.展开更多
文摘This paper studies rotor spinning blended yam produced of spun silk and cashmere. Nine samples were spun, from three different opening rollers and different navels. According to the Uster test results of yam quality properties, optimum selection is done by using analysis method of combining fuzzy decision-making and fuzzy pattern classification. Experimental plan is designed based on universal rotated experimental design, and the method of confined optimization is used to optimize the speed of opening roller, the speed of rotor and twist factor, according to the results of yam quality test by Uster.
文摘The neural network spinning prediction model (BP and RBF Networks) trained by data from the mill can predict yarn qualities and spinning performance. The input parameters of die model are as follows: yarn count, diameter, hauteur, bundle strength, spinning draft, spinning speed, traveler number and twist. And the output parameters are: yarn evenness, thin places, tenacity and elongation, ends-down. Predicting results match the testing data well.
