Abstract
Fabric comfort comprises fabric sound which is the sound generated by fabric during wear by users. In this work sound generated by samples of polyester and cotton-polyester woven fabric was investigated. The sample specifications in warp wise direction were identical. In order to stimulate sound generated by the samples, an apparatus capable of sound induction was designed and developed. The recorded sound signals were analyzed, using Discrete Fourier Transform, together with Discrete Wavelet Transform. Sub-bands energy of FFT and energy coefficients of wavelet transform were calculated. The effect of Physical and mechanical properties on sound features of samples was predicted using Multilayer Feed forward network with back propagation learning algorithm. The network generated results showed that, fabric surface roughness and drape coefficient are the most and the least effective parameters affecting sound volume respectively.
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