A New Computerized Data Acquisition and Analysis System for KES-FB Instruments

Abstract

The Kawabata evaluation system for fabrics (KES-FB) has been commonly used to measure fabric mechanical behaviors related to hand. However, the data acquisition and analysis technique for this system is obsolete and time-consuming. The purpose of this study is to develop a new data acquisition and analysis system for the KES-FB instruments using LabVIEWTM software and corresponding hardware (National Instruments). Windows-interface programs for each KES test method are created with the LabVIEW system. In order to validate this data acquisition system, twenty apparel fabrics are tested using both the original KES-FB data recording method and the new computerized data processing method. Linear regression and variance analysis are used to compare tested results and evaluate repeatability and variability within the two data acquisition methods. The R2 values of most linear regression models are close to 1.00, indicating that the KES data system has been successfully updated.

Tactile comfort characterization of knitted fabrics based on the ring-shaped style tester

“…Then, the Euler's distance D it between the sample vector Z i and the updated cluster center v t is recalculated by Equation (6). The minimum Euler's distance between Z i and the updated cluster center can be found by Equation (7). Then the updated matrixes A and M are obtained by Equations ( 8) and ( 9), which is similar to the first round of the clustering.…”

“…On the one hand, testing the physical and mechanical properties of fabrics requires multiple samples to be tested on different instruments, so the testing time is longer and the cost is higher in practical application; 6 on the other hand, the dependence of tactile touch value and the collinearity between test parameters have attracted the attention of scholars to the stability of the multivariate linear prediction model. [7][8][9] The CHES-FY (comprehensive hand evaluation system for fabrics and yarns) can measure the weight, bending, friction and tensile properties and basic styles of fabrics and yarns in situ. [10][11][12] In addition to measuring the physical and mechanical properties of fabrics directly under low stress to predict the feel of the fabrics, the other method is an indirect method that cleverly simulates human contact with fabrics.…”

Instrumental evaluation of orthogonal tactile sensory dimensions for fine lightweight knitted fabrics

“…Nevertheless, the dependence between the tactile sensory attributes and the collinearity between the measured fabric parameters have drawn much concern about the stability of the prediction models (Chen & Zhao, 2001;Pan, 2006). In the prediction models, sixteen fabric parameters measured by the KESF instruments are used to predict primary hand values such as stiffness, smoothness and fullness for men's suiting (Kawabata, 1980).…”

“…Furthermore, there exists collinearity amongst the sixteen instrumentally measured fabric parameters (Chen & Zhao, 2001). Thus, the stability of the prediction models based on linear regression is adversely affected by the nature of collinearity between the measured fabric parameters (Naes & Mevik, 2001).…”

Relationship between Friction and Tactile Properties for Woven and Knitted Fabrics

“…The objective evaluation of sensorial properties of fabrics is possible with instruments such as the Kawabata Evaluation System (KES) [17,18]. Several devices [19][20][21] can predict fabric stiffness, smoothness, or softness, and simulate the touching feeling through friction measurement.…”