Numerical Simulation of Intelligent Fuzzy Closed-Loop Control Method for Radial-Axial Ring Rolling Process of Super-Large Rings

During the radial-axial ring rolling (RARR) process of super-large rings, abnormal deformation states such as instability and out of circularity often lead to rolling termination and quality fluctuation of ring products. In this work, an intelligent fuzzy closed-loop control method for RARR process of super-large rings is proposed, i.e., the ring's offset adaptive fuzzy control (ROAFC) based on the regulation of the axial roll's rotational speed and the ring's circularity fuzzy control (RCFC) based on the regulation of the mandrel's feed speed. In addition, a recursive average filtering algorithm is added to smooth the axial roll's rotational speed and the mandrel's feed speed according to the actual situation. Using the ABAQUS/Explicit software and its subroutine VUAMP, the intelligent fuzzy controller of the ring's offset and circularity in the RARR process is designed, and the finite element (FE) model for RARR process of a Φ10 m super-large ring with an integrated intelligent fuzzy control algorithm is established. The variation laws of the ring's offset and circularity error in the RARR process are studied with regard to different control methods such as conventional planning control (CPC), ROAFC, RCFC, and comprehensive control of ROAFC combined with RCFC (ROAFC + RCFC). The results obtained show that, compared with the CPC, the ring's offset is reduced by 84.6% and the circularity error is decreased by 51.9% in the RARR process utilizing comprehensive control of ROAFC + RCFC. The research results provide methodological guidance for realizing the intelligent forming of super-large rings.