3D SCANNING AND MODEL ERROR DISTRIBUTION-BASED CHARACTERISATION OF WELDING DEFECTS

The inspection of welded structures requires particular attention due to many aspects that define the quality of the product. Deciding on the suitability of welds is a complex process. This work aims to propose a method that can support this qualification. This paper presents a state-of-the-art data-driven evaluation method and its application in the quality assessment of welds. Image processing and CAD modelling software was applied to generate a reference using the Iterative Closest Point algorithm that can be used to generate datasets which represent the model errors. The results demonstrate that the distribution of these variables characterises the typical welding defects. Based on the automated analysis of these distributions, it is possible to reduce the turnaround time of testing, thereby improving the productivity of welding processes.