Modeling of weld penetration control system in GMAW-P using NARMAX methods

Abstract

Abstract This study introduces the nonlinear identification of a weld penetration control system in pulsed gas metal arc welding system (GMAW-P) characterized with the fused characteristic signal. It was found that both the change in arc voltage during the peak current period and the average arc voltage during the peak current period can be used for condition monitoring of weld pool surface and thus for the estimation of weld penetration depth in GMAW-P. By fusing these two signals through a Kalman filter, filtered fluctuation of arc voltage during peak current period, Δ U k f , is proposed to estimate weld penetration more reasonably. A second order NARMAX (nonlinear autoregressive moving average model with exogenous inputs) model is identified thorough forward regression orthogonal least squares (FROLS) algorithm and the error reduction ratio (ERR) criterion, and then validated in statistical validation. After simplification, the obtained model structure is a bilinear model, and is proved to be superior than linear models thorough model prediction tests. The proposed bilinear model is used to design a gain-scheduled model predictive controller, which shows the ability in weld penetration control in an experiment with a set point change.