Relationship Between Fiber Properties and Rotor Spun Yarn Strength.pdf

1、The relationship between fiber properties-and yarn properties has been the focusof research, and considerable success has been achieved. Many mathematical modelshave been used to understand and predict the complex relati

2、onships between fiberparameters and yam characteristics, and substantial research has been done todetermine methods of predicting yarn properties. But the regression approach hasbeen used more intensively for prediction

3、of the yarn strength with an assumption oflinearity. Recently, some studies have showed that relationship between yarn strengthand fiber properties is nonlinear. In this study we present a comparison study of three m

4、odels for predicting thestrength of rotor spun cotton yarns from fiber properties. The adaptive neuro-fuzzyinference system (ANFIS) and Support Vector Machines (SVM)，generally calledArtificial Intelligent Techniques, tha

5、t are capable of mapping non linear relations andMultiple Linear Regression models are used to predict the rotor spun yarn strength.HVI (high volume instrument) and Uster AFIS (advanced fiber information system)fiber tes

6、t results are used to train and test the three models. Three important stageshave been involved in this study. In the fast stage, we used the ANFIS method to predict rotor spun yarn strengthform fiber properties; tha

7、t is, we identify the relationship between yarn strength andfiber properties. The impact of each fiber property on the rotor spun yarn strength hasbeen analysed. The graphs illustrating the relationship between yam stren

8、gth and oneof the fiber properties, with all the other properties held constant have been plotted.An examination of each graph revealed the nonlinear relationship between rotor spunyarn strength and all fiber properties

9、.The direction of each fiber property influence onyarn strength has been also expected. Increasing fiber strength, upper half meanlength, length uniformity and yarn count has a positive impact whereas increasingmicronair

10、e, yellowness and short fiber content has a negative impact on rotor spunyarn strength. impacts of fiber properties are non-linear. The study showed also how to control the yam quality using the knowledge on fiber proper

11、ties through the yarnstrength leaned surfaces on fiber properties. In the second stage, we used Support Vector Nfachine (SVM) model to predictthe rotor spun yam strength. Using the SVM results, we have demonstrated t

12、hereiative importance of each fiber property on rotor spun yam strength. It wasconfirmed that all fiber properties ptay a role in performance of rotor spun yarnstrength. The results show that the rotor spun yarn strength

13、 is influenced to a greateror lesser degree by the fiber properties. Finally, the predictive performances of the two models are estimated andcompared to those from classical linear regression method. The comparison s

14、howedthat the results provided by ANFIS are better than those provided by both regressionand SVMs methods. The comparison between ANFiS and SVM with conventionalmethods indicated that these new approaches worked better i