Quality Control of Resistance Spot Welding of High Strength Steels

Abstract

A reliable multi-sensor measuring technique was developed for inline quality control of resistance spot welding consisting of a combination of sensory components in conjunction with multivariate analysis methods for monitoring the welding process. To achieve the best possible discrimination of the classes, a Fast Independent Component Analysis Algorithm (Fast-ICA) was applied. For the actual classification of the process data a multi-layer perceptron was used.The evaluation of the process and its quality was done on the basis of the process variables like welding current, voltage, time, resistance and forces. By the simultaneous evaluation of resistance and force profile during welding the probability of failure detection was increased to over 95%. In addition, it was verified that the 3MA method can be used successfully for non-destructive testing of resistance spot welds. A probability of detection of 85% to 90% has been achieved, respectively.The paper presents the mathematical and technical procedures in detail, explains the experimental conditions and shows the obtained classification results of in-process control as well as the results of post-process inspection using 3MA technique in comparison.