직물의 보온성에 관한 통계학적연구

A Statistical Study on the Warmth Retaining Properties of Fabrics

In order to investigate the warmth retaining properties of fabrics some characteristics such as thickness. porosity, packing density, thermal conductivity, moisture regain and air permeability were measured and experimental results were analysed statistically to relate the warmth retaining properties with those characteristics. From the analysis, the following results were obtained. 1. When the warmth retaining properties of fabrics (Y) are dependent variable and thickness ($x_1$), porosity ($x_2$), packing density ($x_3$), thermal conductivity ($x_4$), moisture regain ($x_5$) and air permeability ($x_6$) are independent variables, the regression equation of warmth retaining properties can be represented as follows. 1) Y= 1.6005+46.817$x_1$, (R=0.9487) 2)Y=-1.4187+26.5072$x_1$+0.2055$x_2$(R=0.9704) 3) Y= -3.6908+17.4482$x_1$+0.1782$x_2$+28.3243$x_3$ (R=0.9756) 4) Y=0.9202+16.9553$x_1$+0. 1167$x_2$+30.3577$x_3$+1.8884$x_4$ (R=0.9792) 5) Y=0.9353+17.2266$x_1$+0.1177$x_2$+28.9821$x_3$-1.8302$x_4$+0.0151$x_5$ (R=0.9792) 6) Y=0.7583+17.2343$x_1$+0.1196$x_2$+28.8830$x_3$-1.8336$x_4$+0.0187$x_5$0.0004$x_5$ (R=0.9792) 2. The warmth retaining properties of fabrics are merely affected by adding thermal conductivity, moisture regain and multiple regression equation which contains thickness, porosity and packing density as variables. Therefore the multiple regression which contains thickness, porosity and packing density as variables Y=-3.6908+17.4482$x_1$+0.1782$x_2$+28.3243$x_3$ is highly practical.