Stepwise Regression Analysis on PLA / Tencel Knitted Fabric Structure and Performance of Moisture Absorption and Quick Dry

Abstract

Based on the analysis of the PLA/Tencel knitted fabric structure parameters, this paper, with the double screening stepwise regression analysis method, analyzes the influential PLA/ Tencel knitting fabric moisture absorption of quick dry, eliminates the insignificant factors and keep the distinctive factors. In terms of the quick dry effect of moisture absorption in different time, this thesis set up four optimal regression models. The analysis shows that the knitted fabric properties of moisture absorption and quick dry can be forecasted with the regression models, which use the correlation index of fabric specification structure parameter as input parameter: the wet transmission of PLA/tencel knitted fabric was corelated with the PLA content, weft density, warp density, yarn diameter, but the relationship with the fabric thickness is not obvious. The drying rate of 30 min and 60 min are related with the tencel content and weft density, the 30 min drying rate is bound up with the thickness of the fabric and the 60 min drying rate was related with square meters grams and linear modulus of stitch. Meanwhile, the correlation coefficient of predicting model after the adjustment is high and the maximum fitting error of predicted values and measured values of the maximum fitting error is small.