Optimized Operation Of Polyester Filament Yarn Based On Intelligent Algorithms

Fiber production, including natural fibers, polymer fibers and so on, is a large-scale production system with multiple processes and complex conditions. The implementation of monitoring and controlling the production process requires not only mastering the production equipments and technologies, but also learning to design and optimize production process. This paper, as a sub-topic of the polyester fiber spinning forming process simulation, process optimization and systems integration projects, undertakes a research on the optimized operation of the polyester filament's spinning process. The main research is as follows:Firstly we propose the identified method of the target set of process parameters to be optimized, construct the evaluation model based on entropy-fuzzy comprehensive algorithm, and analyze the data collected with K-means algorithm and multi-valued association rule mining algorithm, which provides the basis for the optimized operation.Then based on expert knowledge, we propose the methods of polyester filament spinning process optimization, mainly including the representation of knowledge and the implementation of inference engine. Through the production rules inferred by the fuzzy causality diagram theory, this paper finds out the main reason of the deviation of product quality. And then it forecasts the optimized performance parameters through reverse reasoning with the immune optimization neural network (IRBF) This can improve the current status of manual measurement, which depends highly on the human experience and so as to lay a foundation for the optimized production of the large value, large-scale spinning.At last we propose the implementation of the polyester filament spinning process optimization expert system software based on the C/S structure, and show the overall design framework of the system, the practical function of modules and the form designs of the system database, which provide a good reference for the practical application for the intelligent optimization of the individual fibers in the future.