Intelligent control model for yarn quality based on multi-process knowledge association
SHAO Jing-feng
MA Chuang-tao
Abstract：To solve the problem of yarn quality was difficult to control accurately by using quality control model based on single process, an intelligent control model for yarn quality based on multi-process knowledge association was built. Firstly, the yarn fracture strength was selected as the main control indexes, and the knowledge association among multi-process was achieved based on the quality control point and quality loss function. Furthermore, the quality loss function was selected as the objective function to built quality control model, and the automatic process control technology was adopted to achieve the quality control based on data feedback. And then, the penalty function was introduced to solve the model by using multi-object firework algorithm. Finally, as verified by the experiment, the results was shown that fracture strength was improved by 1.27%and 3.40%, and the nonconforming rate of the yarn production was decreased by 23.48%and 50.00%after comparing the results of the model we proposed with the control model ignoring multi-process knowledge association and the results before the control. Meanwhile, the comparison and analysis of the results indicate that the model we proposed was conducive to solve the problem of yarn quality was difficult to control by single process quality control model.
Keywords：quality controlmulti-process knowledge associationquality loss functionpareto optimality
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 840-849 )