Abstract:

To solve the problem of difficult control on yarn quality accurately because of the nonlinear input-output relationships among the spinning quality, key indexes injluencing spinning quality fluctuation were identified and the index fracture strength was abstracted. The quality control point and quality loss function based on fracture strength were designed, A knowledge correlation analysis method was proposed. Then, a spinning quality control model based on hierarchical multi-process was built, and it was solved by multi-object firework algorithm. The verification results show that the proposed control model realizes accurate control on yarn quality, and it is suitable for solving the nonlinear problem of the input-output relationship in spinning quality output characteristic value. Meanwhile, by comparing the control results with the model ignoring the knowledge relation among the multi-process and the results before the control, it is found that the fracture strength is improved by 1.27% and 3.40%, and the nonconforming rate of the yarn production result from the nonqualified fracture strength decerases by 23.48% and 50.00%.

Key words: spinning quality, control model, intelligent control, hierarchical multi-process, multi-object firework algorithm