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Neural Network Classification of the Unknotted Joints of Yarn Ends

Research and development

Author:

• Lewandowski Stanisław
  Institute of Textile Engineering and Polymer Materials, University of Bielsko-Biala, Bielsko-Biała, Poland

Full text

Abstract: The artificial neural network elaborated in this research enabled to recognise and multicriterially classify the unknotted joints of yarn ends. Worsted weaving woollen yarn with a linear mass of 15 tex was used as an example. A 10-step quality scale was applied in order to increase the accuracy of recognition and classification of joints. Such a neural network design can be applied for the quality classification of such joints, as well as in other fields of the textile industry.

Tags: neural network, classification scale, unknotted joints, spliced yarn ends, wool yarn.

Citation: Lewandowski S.; Neural Network Classification of the Unknotted Joints of Yarn Ends. FIBRES & TEXTILES in Eastern Europe 2011, Vol. 19, No. 3 (86) pp. 37-43.

Published in issue no 3 (86) / 2011, pages 37–43.