Research And Analysis Correlation Between Hairiness Index And The Number Of Hairiness About Yarn

Yarn hairiness is an important index in evaluating the quality of yarn. It not only has aninfluence on the later procedure of weaving and sizing, but also affects the property of fabric. Atpresent, there are two methods which are the diffuse reflectance and projection counting methodsto measure the hairiness. UT5including the OH module and HL400were used in this test methodof yarn hairiness respectively by the Uster Technologies Co. UT5and HL400are the mostadvanced machines in the world, whose measuring results are the hairiness index (H) and thenumber of hairiness. They are both indexes of measuring numbers of yarn hairiness and thecontents of the study are just the correlation between the value H and the number of hairiness. Thepurpose of the study is to analyze the factors impact on the correlation between the value H andthe number of hairiness, and aim at exploring the reason why correlation exist differencesobtained by different researchers. Hope the study will help the factory to solve practical problemsin production and to reduce the cost.Firstly, in order to investigate the effects of test methods on the measurement results,evaluation model of uncertainty measurement respectively is established by two test methods ofyarn hairiness respectively. The combined standard uncertainty result is given through designingexperiment, analyzing resources of uncertainty and estimating distribution of uncertainty.However, the integrated result with expanded uncertainty are0.0112and0.256. It indicates thatthe projection counting method is not as accurate as the diffuse reflectance method.Secondly, the paper mainly analyzes the influence of correlation between the value H and thenumber of hairiness that caused by the property of yarn.337yarn samples were collected andgained the result from UT5and HL400.Itcan discover the regression equation and r2throughregression analysis, and depend on the results that the fitting of overall sample was showed. Thespinning methods, sample size, density, and raw materials are factors which can effect thecorrelation between the value H and the number of hairiness. The regression analysis is applied toevery factors, intending to research the mechanism of four factors and the optimal regressionmodel and the r2.It is stated that rotor spinning have lower r2when compared with other spinningtypes after spinning classified. Sort the r2for ring spun: viscose yarn> polyester and viscosemixed yarn> polyester yarn> cotton and polyester mixed yarn> cotton yarn. Viscose yarn is alsohigher than cotton in sirospinning. For ring spinning the yarn in9.8tex has lower r2whencompared with other yarn which has different linear density. It is applied to compact spinning; it isfound out that the sample size also is a factor can effect the correlation between the value H andthe number of hairiness during yarn classified. When the sample size decrease, the correlation willbe increase. To sum up, it is stated that the test system, spinning methods, sample size and linear densityare important factors that can effect correlation between the value H and the number of hairiness.