Papers by Keyword: Yarn Evenness

Abstract: In this paper, a new yarn appearance measurement system based on machine vision is introduced. The yarn images are continuously captured by image acquisition system. To extract the main body of the yarn accurately, the yarn images are processed sequentially with threshold segmentation and morphological opening operation. Then the coefficient of variation (CV value) of diameter is calculated to characterize the yarn evenness. The measurement process achieves result (CV value) which can be compared with USTER evenness tester by image processing techniques. By comparing different methods which use different algorithms, a suitable method is chosen to be used in this new measurement system. Then a more accurate, more efficient and faster measurement system will meet requirements in the future.

Abstract: In melt spinning process, evenness of polypropylene melt spun yarns affects the appearance, hairiness, strength and productivity of yarns, as well as product production and profits, causing rejection due to nonconformity. The research is to find optimal manufacturing parameters of melt spun yarns. Firstly, to proceed the parameter design by Taguchi method, then to select a manufacturing parameter which will affect the quality of melt spun yarns as controllable factors. Also to choose a suitable orthogonal arrays. Meanwhile, according to variation of analysis, to decide optimal manufacturing parameters of melt spun yarns and its remarkable factor. Finally, using 95% confidence interval to proof the experiment’s reliability and repeatability.

Abstract: Yarn unevenness is one of the important indexes which presents the evenness of polyester POY filament and affects the performances of the filament. The principle of capacitive evenness tester Uster and the measurement method are described in this paper. The influences of operating environment and the measuring conditions on determining the unevenness of polyester POY filament are discussed. The reasonable conditions are also pointed out, which will have the directive function for the evenness test work with Uster.

Abstract: The artificial neural network and multiple regression models have been developed to predict the evenness of cotton ring yarn with process parameters such as front roller speed, spindle speed, nip gauge, back draft zone time and roving twist. The efficiencies of prediction of the two models have been experimentally verified, and the predicted evennesses of cotton ring yarns from both the models have been compared statistically. An attempt has been made to study the effect of process parameters on yarn evenness. The MSE and mean absolute error of ANN modelare lower than that of multiple regression model. The results show that the performances of prediction of ANN models are more accurate than those of multiple regression models.

Abstract: Pre-tension of filament is critical to the characteristics of solo-sirofil composite yarn. In this paper, solo-sirofil yarns under filament pre-tension of 5-25cN were produced by modified EJM-128K ring spinning frame. The hairiness, breaking strength, breaking work and yarn evenness were tested under standard test conditions. It’s explored that when the pre-tension of filament is 15cN, perform of solo-sirofil achieve the best level with lower hairiness, higher breaking strength and breaking work, and better yarn evenness.

Abstract: This paper systematically analysied and measured the main properties of the pure cashmere siro-spun yarn and pure rabbit hair ring-spun yarn, including the yarn evenness, thin and thick , neps, raw material nature, yarn strength, yarn hairiness, twist level, wearing resistance and etc. And the market price of yarn was also investigated. The model of the cost performance ratio was established to analyse the yarn properties scientifically. The results indicated that the pure rabbit hair yarn is better than the pure cashmere yarn. It provided the guidance suggestions and scientific basis for the manufacturers to improve the performance and reduce the cost price of the yarn.

Abstract: This paper compares capacitive and photoelectric method for measuring yarn evenness, and presents a new yarn unevenness on-line measurement system to detecting accurately yarn appearance diameter. By means of researching coefficient of diameter variation and mass variation, the relation model of variation coefficient is established, and the experimental data shows excellent correlation between coefficient of diameter variation and coefficient of mass variation and approximate linear relationship. The laser on-line measurement system of yarn evenness can accurately measure yarn diameter and calculate the coefficient of variation, which is suitable for the production field measurement.

Abstract: This paper introduces application of the intelligent sensor in the yarn quality online detection. Using computer control techniques,Adopting the high accuracy intelligent laser sensor to detect the yarn diameter, display and print out the real-time evenness of the yarn by analyzing the yarn sampled datas. The device is more portable, forward-looking, intelligent and low cost, It is the development direction of the yarn quality testing in cotton factory.