JOURNAL OF TEXTILE RESEARCH ›› 2016, Vol. 37 ›› Issue (07): 142-148.
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Abstruct: In order to make a primary research in the relationship between the quality of drawing sliver and the quality of vortex spinning yarn. Support vector regression machine prediction model optimized by GA is built up. 19.7tex and 11.8tex vortex spinning blended yarn of polyester and viscose(the blending ratio is 67:33)is selected as the experiment object. Yarn strength and CV of yarn unevenness are predicted while four quality parameters of drawing sliver (CV of yarn unevenness, moisture regain, quantification of sliver and unevenness of quantification) are used as the input parameters of prediction model. BP neural network model is also built to make a comparison with the aforementioned model. After a comparison between these two models, the result shows that the model of the optimized support vector regression machine performed a more powerful reliability and accuracy and it can describe the non-linear relationship between the quality of sliver and the quality of vortex spinning yarn more appropriately than BP model.
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