Abstract:

To meet the requirements and automated production needs of controllable weft density and variable diameter tubular fabric, a control model was established. The control algorithm was also analyzed and realized. Firstly, Aiming at non-equal radius properties of fabrics, a continuously adjusting mechanism was designed, based on which, the relationship between rotation angle and time was deduced. And then, the variation of weft density was analyzed, and the relation between traction speed and time was also established. Based on the general regerssinon neural network, the nonlinear shape curve of the fabric was approached. To verify the feasibility of the model and algorithm, Matlab was used for simulation analysis. The control model and algorithm have the advantages of fast operation, simple structure and high precision, which can meet the requirements of carbon fiber composites preform weaving.

Key words: tubular composite, non-equal radius, variable weft density, general regression neural network