基于免疫神经网络的纺丝过程双向智能优化模型

In this paper, an immune neural network-based bi-directional intelligent optimizing model for the spinning process is proposed, along with the expert system in which the proposed model is embedded. The bi-directional optimizing mechanism is formed by analyzing large numbers of data in production. With such a mechanism, the reasonable plans for the parameter configuration of the spinning production line can be acquired, and the performance of the fibers can also be predicted and evaluated. Simulation results show that the proposed model has the ability to establish the bi-directional model between the production configuration and the fiber quality indices, which outperforms the conventional neural network-based model. The proposed model can not only reveal the internal connections between the manufacturing process of fiber and its corresponding quality indices, but also provide a useful tool for the manufacturing personnel on the development and design of fiber products.