多工序递阶的棉纺过程质量智能控制模型

针对纺纱质量特征值之间因存在非线性关系而难以精准控制的问题，对影响纱线质量波动的关键指标进行了辨识，并提取断裂强度为关键指标；设计了基于纱线断裂强度的质量控制点及质量损失函数，提出了纺纱过程多工序质量控制点间知识关联方法；以质量损失函数为目标函数构建了基于多工序递阶的棉纺过程质量控制模型，并利用多目标烟花算法求解。结果表明，提出的质量控制模型实现了纱线断裂强度的多工序控制，有利于解决质量特征值之间“输入-输出”关系的非线性化问题。该模型控制结果与未考虑多工序间知识关联以及控制前的结果相比，其纱线断裂强度提高了1.27%和3.40%，因纱线断裂强度不达标导致的纱线不合格品率降低了23.48%和50.00%。

Intelligent control model for spinning quality based on multi-process hierarchy

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.Theverification results show thattheproposed control model realizes accurate control on yarn quality, and it is suitable for solving the nonlinear problem of the input-output relationship in spinningquality 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 isfound 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%.