Understanding the influence of the fabrics microstructure on frictional noise was investigated in terms of surface roughness for three multi-fibre apparel fabrics (denim, cotton and silk) and single-fibre polyester model fabrics. Surface roughness (R\(_a\)) correlated strongly with total noise emitted (R\(^2\) = 0.97) and was attributed to the ‘hairy’ nature of multi-fibre fabrics. In terms of specific frequencies emitted within a fabric’s sound spectrum, the microstructure of the model fabrics was strongly correlated (R\(^2\) = 1.00) with the fundamental harmonic predicted, enabling a ‘fingerprint’ theory to be proposed. Friction coefficients, measured using tribology, of apparel and model fabrics were established, and showed that the major impact on friction was R\(_a\) and fibre type. Furthermore, friction was reduced via the lubrication of hydrocolloid fluid gel particulates, by means of reducing the surface roughness by filling in asperities and reducing the hairy nature of the fibres. Consumer perceptions of fabrics and fabric sounds were established with one-to-one interviews, and the influence of sound on sensory perception and liking was established by manipulating real-time fabric sounds, showing that by altering high and low frequencies, and overall noise, a significant difference in sensory attribute 'textured' can be observed.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:607236 |
Date | January 2014 |
Creators | Cooper, Cerise Jemma |
Publisher | University of Birmingham |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://etheses.bham.ac.uk//id/eprint/5087/ |
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