Abstract:

An innovative Frictional Sound Automatic Measuring System (FSAMS) was designed to collect and enable analysis of the frictional sound spectra of four natural fibre woven fabrics which included cotton, linen, silk, and wool. The Fast Fourier Transform (FFT) method was used to convert time-domain signals into frequency-domain signals to enable the maximum sound amplitude (MSA) and the level pressure of the total sound (LPTS) of the cotton, linen, silk, and wool fabrics to be calculated and analysed. Subsequently auto-regression formulae were used to calculate the fabric auto-regressive coefficients (ARC, ARF, and ARE); the correlations between fabric frictional sound in terms of LPTS and AR coefficients, and mechanical properties as measured by KES-FB were also evaluated. Stepwise regression was then used to identify the key frictional sound parameters for the four types of fabric. The results show that LPTS values for cotton, linen, silk, and wool fabrics increase with their ARC values. It was revealed that the key mechanical parameters affecting fabric frictional sound for the four natural fibre woven fabrics were not the same for each fabric type: the parameters that influenced LPTS values were the fabric weight and bending hysteresis for the cotton fabric,tensile energy for the linen, tensile resilience for the silk and shear hysteresis at a 5° shearangle for the wool fabric.