Study On Testing Ramie Fiber Fineness With Wira Airflow Meter

Fiber fineness is the key index for ramie rating, product quality and textile use value. At present, the main method of testing ramie fiber fineness is cut-middles method. This method has some shortcomings such as the small quantity of ramie sample, the deficiency of representative, the tedious operation and the results greatly influenced by subjective factors. As consumer market increased demand for ramie products and the fast development of ramie fiber, the corresponding detection technology is proposed new requirements.In this paper, a faster and more accurate test method for ramie fiber fineness is studied. Testing the metric count of ramie fiber with WIRA airflow meter is researched and the regression equation according airflow value to calculate the metric count is established. And the test method using airflow meter is extended to Y145A airflow meter which is more common.In this paper, the main research contents and conclusions are as follows:Firstly, the influence of parameters in Kozeny equation on WIRA flow value is studied.(1) The influence of sample weight on the flow value is studied. When the other parameters under certain conditions, with the sample weight increases, the flow value decreases. The variation is closer to linear, sample weight for each additional 0.1g, flow value reduced 10.3%～14.6%.(2) The influence of sample placement on the flow value is studied. Compared to the placement of parallel and folded, the random placement gets the minimum flow value and coefficient of variation.(3) The influence of sample carding on the flow value is studied. Compared to carding the sample with hands, the sample processed by carding machine gets smaller flow value and coefficient of variation.(4) the fiber length in the sample has no significant effect on flow value.(5) The influence of sample moisture regain on the flow value is studied. Along with the increase of fiber moisture regain, the flow value shows a trend of decrease. When the moisture regain increased from 1.14% to 27.28%, the flow r value decreases 18.10%. Secondly, the regression equation between WIRA airflow value and metric counts tested by cut-middles method is established and verified.(1)The regression equation is Y=-9.372X+3398.157(Y is metric count, unit:Nm; X is flow value, unit:mm). At the significant level a=0.05, there is no significant difference between the metric count calculated according to the equation and the metric count tested by cut-middles method. The relative deviation between calculated value and tested value is 3.92%.(2) When metric count of the sample is between 1400Nm～2400Nm, the regression equation is Y=-9.972X+3475.668 (Y is metric count, unit:Nm;X is flow value, unit:mm). At the significant level a=0.05, there is no significant difference between the metric count calculated according to the equation and the metric count tested by cut-middles method. The relative deviation between calculated value and tested value is 3.79%.(3) When metric count of the sample is between 1500Nm～2000Nm,the regression equation is Y=-7.280X+3000.306 (Y is metric count, unit:Nm; X is flow value, unit:mm). At the significant level a=0.05, there is no significant difference between the metric count calculated according to the equation and the metric count tested by cut-middles method. The relative deviation between calculated value and tested value is 3.26%.The differences among the three calculated value according to the three regression equations are not significant. Considering the conveniences of application, determine the regression equation Y=-9.372X+3398.157 to be the final regression model.Thirdly, the test method using airflow meter is extended to Y145A airflow meter which is more common. The regression equation is Y=-9.372X+3398.157(Y is metric count, unit:Nm; X is flow value, unit:L/min). At the significant level a=0.05, there is no significant difference between the metric count calculated according to the equation and the metric count tested by cut-middles method.