Abstract
The relationship between fabric drape, low stress mechanical properties and finishing processes is relatively complex. This paper demonstrates the possibility of using artificial neural networks to identify the fabric drape of woollen fabrics treated with different dry finishing processes (stenter, decatising, superfinish, formula, KADE strong/weak - autoclave decatizing). The mechanical and surface properties of woollen fabrics were measured by both the KES-FB and FAST systems, and then the results obtained were applied to artificial neural network (ANN) modelling. ANN models were compared by verifying the Mean Square Error (MSE) and Correlation coefficient (R-value). The results indicated that each model is capable of making quantitatively accurate drape behaviour predictions for wool fabrics (Rmin = 0.92, MSEmin = 0).
Original language | English |
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Pages (from-to) | 90-99 |
Number of pages | 10 |
Journal | Fibres and Textiles in Eastern Europe |
Volume | 23 |
Issue number | 2 |
Publication status | Published - 2015 |
Bibliographical note
Publisher Copyright:© 2015, Institute of Biopolymers and Chemical Fibres. All rights reserved.
Keywords
- Artificial neural network
- FAST
- Fabric drape
- Finishing processes
- KES
- Wool fabrics