# WELDMAP: A Photogrammetric Suite Applied to the Inspection of Welds
## 4 Conclusions  
In this article, an unprecedented tool has been presented that integrates the possibility of providing smart photogrammetric models based on the quality control of welds. Under the name WELDMAP, the ability to reconstruct 3D welds, both geometrically and radiometrically, allow us to perform external quality control according to normalised standards. More specifically, this article proposes the use of RGB images acquired with reflex cameras as a non-destructive and low-cost technique for the digitisation of welded joints and the automation of their quality control by means of an in-house software, successfully tested \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Type of Defect**} & **Criterion for the Quality Assessment (mm/\({}^{c}\))** & \multirow{2}{*}{**No. Weld**} & **Positioning along Bead Axis \(x\) (mm)** & \multirow{2}{*}{**Results**} \\ \hline \multirow{3}{*}{Excess Weld Metal} & \multirow{3}{*}{\(H\geq 0.1T+1\)} & 1 & 28.2 & 2.59 \(\geq\) 1.98 & not pass \\  & & 4 & 150.8 & 3.01 \(\geq\) 1.75 & not pass \\  & & 6 & 161.0 & 4.23 \(\geq\) 3.98 & not pass \\ \hline \multirow{3}{*}{Linear misalignment} & \multirow{3}{*}{\(d\geq 0.1t\)} & 1 & 23.4 & 0.75 \(\geq\) 0.70 & not pass \\  & & 2 & 74.5 & 1.45 \(\geq\) 1.20 & not pass \\  & & 5 & 110.9 & 0.68 \(\geq\) 0.50 & not pass \\ \hline \multirow{3}{*}{Angular misalignment} & \multirow{3}{*}{\(\delta\left[\eta_{l}-n_{r}\right]\geq 2^{\circ}\)} & 3 & 15.3 & 2.5 & not pass \\  & & 3 & 90.6 & 2.7 & not pass \\  & & 3 & 115.4 & 3.0 & not pass \\ \hline \multirow{3}{*}{Notch or pore} & \multirow{3}{*}{\(dz\geq 2\) mm} & 1 & 12.3 & 2.3 & not pass \\  & & 4 & 60.6 & 2.8 & not pass \\  & & 5 & 116.3 & 3.2 & not pass \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Results of the four defects assessed in WELDMAP software. In red colour are highlighted those defects which did not pass the threshold established. Only those cross-sections which produced defects are reported in the table. \(T\) is the width of the bead, \(t\) is the width of the weld, \(n_{l}\) and \(n_{r}\) the normal vectors of the right and left plaques, respectively. Figure 8: Quality control of welds based on cross-sections and the four defects analysed. In red are highlighted the different parts of the interface: menu (1), toolbar (2), tree view of the different inputs and intermediate results of the projects (3), 3D model viewers (4), pop-up window with the defects analysis (5), property view (6), pop-up window with the cross-sections generated (7), console (8), and thumbnails (9). in different scenarios and with different types of welds. The results come to support its usefulness, since today these quality control tasks have been carried out visually supported by expeditious measures, and in most cases with an analogue record. Looking ahead, it is expected to be able to work with images from other wavelengths (e.g., thermography, X-rays) and new materials (e.g., composites, fibres, etc. ), so that multimodal registration techniques have to be incorporated together with the application of artificial intelligence techniques for quality inspection tasks. So, further developments will be carried out to include additional types of defects. Conceptualisation, E.R.d.O. and D.G.-A. ; methodology, E.R.d.O., M.R.-M., P.R.-G. and D.G.-A. ; software, R.M. ; validation, M.R.-M. and P.R.-G.; formal analysis, D.G.-A., R.M. and M.R.-M.; writing--original draft preparation, E.R.d.O. ; writing--review and editing, M.R.-M. and D.G.-A. All authors have read and agreed to the published version of the manuscript. This research was partially supported by Ministry of Science and Innovation, Government of Spain, through the research project titled _Fusion of non-destructive technologies and numerical simulation methods for the inspection and monitoring of joints in new materials and additive manufacturing processes (FatIMA)_ with code RTI2018-099850-B-I00. Not applicable.