Dynamic Optimization of Carbonization Process Parameters Based on Genetic Programming

The properties of carbon fiber are closely related to the carbonization process, in which high temperature is key factor affecting its strength, modulus and other properties. In order solve problem that it difficult adapt complex industrial production environment dynamic factors existing taking furnace heating rate as decision variables, energy consumption yield optimization objectives, element factors, model process parameters established validity verified. Aiming at parameter uncertain environment, a multi-objective algorithm based on genetic programming knowledge transfer proposed. And compare with latest algorithms prove efficiency advantages.