Spatial spiral tube multi-roller bending: Accurate axial prediction utilizing AWPSO-FECAM-LSTM framework

Abstract

The multi-roller bending (MRB) process, characterized by its high stability and flexible mold adaptability, is widely employed in the bending forming of spatial metal tubes (such as spatial spiral tubes (SSTs)). However, due to the fewer mold constraints of the already bent-formed section, the bent tube exhibits irregular axial springback, resulting in uncontrollable axial deviations. To improve forming accuracy, this study proposes a novel AWPSO-FECAM-LSTM framework that predicts the axis coordinates of the SSTs formed with MRB. The framework incorporates two prediction modes: the Angle-Regulation-Based (ARB) model, which predicts points based on the same angle, and the Segment-Regulation-Based (SRB) model, which predicts points based on the same segment. The FECAM module extracts frequency-domain features, thereby enhancing the model’s ability to capture both temporal and frequency characteristics. Meanwhile, AWPSO optimizes hyperparameters using time-decay inertia weights and adaptive acceleration coefficients. Validated through bending experiments and finite element (FE) simulations, the model achieves a mean absolute percentage error (MAPE) of 0.98% and a mean squared error (MSE) of 0.000042, outperforming baseline models such as PSO-LSTM and vanilla LSTM. The ARB and SRB models collectively enable precise prediction of tube axis coordinates, with progressive prediction modes effectively reducing error accumulation. This framework demonstrates significant potential for real-time compensation in digital twin applications, advancing high-precision manufacturing of spatial metal tubes.