Process control based on double-side image sensing of the keyhole in VPPA welding

Abstract

The double-side image sensing of the keyhole puddle in the variable polarity plasma arc welding (VPPAW) of aluminum alloys has been investigated in this paper to extract the characteristic geometrical size of the keyhole and to realize feedback controlling for weld formation in the welding process. Some geometrical sizes of the visible keyhole in the front and back image such as the width, height, area, etc., can be used to monitor both the keyhole puddle and the welding formation in the welding process. Under the conditions of varied heat sink, varied gap and misalignment, the trend from normal welding to cutting can be reflected from the variations of geometrical sizes of the keyhole puddle. The keyhole area, the keyhole height and the shape parameters of the keyhole puddle are the key parameters which reflect the trend from normal welding to cutting when meeting the conditions of the varied heat sink, varied gap and misalignment. The algorithm for the image process of the keyhole puddle and the periphery extracting of the visible keyhole developed in the paper can be used to determine real-time, the geometrical sizes of the visible keyhole when the welding process is conducted. An artificial neural network is applied to establish the steady model for predicting the geometrical sizes of the back keyhole puddle. The inputs of the model are the geometrical sizes of the front keyhole puddle and the weld parameters, and the outputs of the model are the geometrical sizes of the back keyhole puddle. The model can be used to control the stability of the keyhole and the weld formation.