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Study on Blended Yarn and Its Products of Casein Protein Modification of PAN

Author: ZhaoJunFeng
Tutor: WuXiangJi
School:
Course: Fashion Design and Engineering
Keywords: casein protein modified fiber of PAN blended yarn and its products artificial neural networks regression forecasting factor analysis comprehensiveevaluation
CLC: TS154
Type: Master's thesis
Year: 2011
Downloads: 80
Quote: 0
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Abstract


Casein Protein modified fiber of PAN was a new generation regenerated protein fiber.In the21st century, concerned about the application of new fibers, the researches anddevelopments of eco-friendly recycled fiber had become one of the key elements in textileindustry. In this paper, casein protein modified yarn of PAN and its woven products werestudied, following two parts as below.First, the key skills in spinning process about two-component blended yarn of caseinprotein fiber on ring spinning and the predicted performance of blended yarn were studied.Based on the factors of the theoretical analysis on blended yarn performance,14.7texcasein/cotton blended yarn, for example, its spinning technology parameters and keytechnologies were described in detail such as by adjusting the equipment, drafting Gauge,the speed ratio and other parameters, the evenness CV. Good performance of the blendedyarn of two components was achieved.On this basis,147lots of different proportions and counts of casein/cotton blendedyarn of the finished product within six months were collected. Using of BP artificial neuralnetwork to predicte two important properties-tensile strength and Evenness CV value ofcasein/cotton blended yarn. BP neural network had the innate superiority in nonlinearregression function. Select samples of112learning and training network, the remaining35samples as validation. After several times adjustment and optimization, artificial neuralnetwork took a very good forecast on breaking strength and evenness. The predictionaccuracy of neural network was more than98%, and the determine constant of linearregression of prediction R~2was more than0.85, achieve the purpose of prediction. At thesame time, multiple linear regression analysis method was exercised to predict the samevalue of blended yarn. The predicted values of breaking strength and evenness were got inlinear regression model; the accuracy of prediction can be seen from the chart that the linear regression model’s was much less than the neural network’s.Second, eight kinds of casein protein fiber woven fabrics were selected to test itsperformance. Taking the performance of shirt fabric, thermal comfort, appearanceretention and fabric style were considered. The results of tests for a more detailed analysisbetween performance indicators were discussed.Then fuzzy comprehensive evaluation and factor analysis were applied to evaluate theoriginal datas of eight fabrics performance in last chapter. First with fuzzy comprehensiveevaluation, the eight fabric performance sort classification. At the same time in SPSSsoftware, the establishment of the correlation coefficient matrix of selected variables andprovide common factor were achieved, common factor scores obtained to calculate thecomposite score. Obtained by comparing the two results of comprehensive evaluationmethods are not exactly same, but on the whole, it is consistent. However, factor analysisof the comprehensive evaluation method was more suitable for multivariate analysis;which help to identify the correlation between various factors and datas could becondensed to make data analysis easier than before.

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CLC: > Industrial Technology > Light industry,handicrafts > Textile industry,dyeing and finishing industry > Chemical fiber textile > Pure chemical fiber spinning process
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