A new criterion for quality monitoring of pulsed laser spot welding using an infrared sensor - Part 2: quality estimation using an artificial neural network

Abstract

This paper suggests a method for estimating weld quality using a radiation feature. In one experiment the dimensions of the weld joint were examined using the radiation feature. Results show that the feature can be used to estimate weld dimensions. In another experiment, weld strength was estimated using the feature. Since it would be laborious to examine a large number of radiation features and find the explicit relationship, an artificial neural network (ANN) was employed. In experiments, the significant welding parameters were varied within a controllable range and 640 laser spot welds were used for ANN learning. The correlation coefficient between the estimated and the measured strength was as high as 0.98 for learned parts. The other 180 welds were used to appraise the learned ANN. The correlation coefficient between the estimated and the measured strength was as high as 0.95 for the unstudied parts and the mean square error of estimation was as low as 0.78 kgf.