Automated geometry measurement and deep rolling of butt welds

Heide, Klaas Maximilian; Heikebrügge, Steffen; Dänekas, Christian; Breidenstein, Bernd; Schaumann, Peter

doi:10.1007/s40194-022-01346-w

Cited by 3 publications

(4 citation statements)

References 29 publications

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“…In general, small notch radii and large flank angles have a stress-increasing effect [9]. To determine the local weld toe parameters, various methods exist in the literature [10,11]. In general, the determination of the parameters is based on two-dimensional geometry data sets perpendicular to the weld seam.…”

Section: Determination Of Notch Radius and Flank Anglementioning

confidence: 99%

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Development of an automated quality assurance approach for welded joints

Dänekas,

Schaumann,

Ghafoori

et al. 2023

ce papers

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A more economical and resource‐saving construction of offshore wind energy converters is necessary in order to achieve climate policy objectives. Automated quality assurance of welded joints offers a great potential to enable less conservative manufacturing of the support structures. The main objective of this study is to find a correlation between the parameters that describe the weld geometry and the fatigue life. Butt welded specimens were scanned with a laser line sensor. The weld seam parameters including notch radius and flank angle were evaluated and the stress concentration factors in the notch were determined considering the microstructural support effect. A series of constant amplitude fatigue tests was conducted in order to evaluate S‐N‐curves according to nominal stress approach and notch stress approach. The fatigue results show a good correlation between notch stresses and fatigue life, demonstrating the great potential of the quality assurance approach for evaluating the weld seam geometries.

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Section: Determination Of Notch Radius and Flank Anglementioning

confidence: 99%

“…For each combination the distances between the data points and the circle are evaluated and the combination with the best rating is chosen as the decisive circle approximation. The algorithm is described in detail in [11].…”

Section: Determination Of Notch Radius and Flank Anglementioning

confidence: 99%

Development of an automated quality assurance approach for welded joints

Dänekas,

Schaumann,

Ghafoori

et al. 2023

ce papers

Self Cite

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“…Finally, the corresponding weld path is determined by utilizing the height and width of the weld seam and the distribution information of feature points within the filling layer. This approach achieves ML-MC welding dynamic routing of the weld groove [29][30]. The specific process of dynamic routing for ML-MC is Figure 7.…”

Section: Visual Dynamic Row Planning Of Multi-layer and Multichannel ...mentioning

confidence: 99%

Multi-Layer and Multi-Channel Dynamic Routing Planning and Initial Point Positioning of Weld Seam Based on Machine Vision

Li,

Zheng

2023

IEEE Access

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The welding process for medium and thick plates typically involves multi-layering and multichanneling, but its quality and reliability require further improvement. Therefore, this study introduces the convolution neural network algorithm to establish a deep learning model for weld seam recognition. Additionally, the structured light imaging method is used to accurately position the V-shaped weld groove. Meanwhile, a machine vision based multi-layer and multi-pass dynamic routing planning algorithm was also studied and designed, and a contour feature point recognition algorithm for the filling layer was developed. Thus, dynamic routing planning is achieved. It is demonstrated that the difference between the coordinates acquired by the deep learning model and the ideal region decreases steadily and reaches a minimum of (200,80). The confidence level of weld seam detection gradually increases with the adjustment of the welding robot, reaching a maximum of 98%. The confidence level of the detected feature points reaches 100%. In the meantime, the remaining height of the fusion after welding is 2.5mm. There are no negative phenomena present on the surface of the weld seam, meeting the necessary process requirements. Such discrepancies as undercut, incomplete penetration, slag inclusion, and porosity are absent. It shows that the welding technology based on machine vision has strong feasibility, effectively improves the automation level and efficiency of welding technology, and provides reliable technical support for the development of modern machine vision welding technology.

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“…Für eine voll automatisierte Bestimmung der Nahtparameter wurde der Algorithmus erweitert und wird im Folgenden kurz beschrieben. Detaillierte Informationen zur Auswertemethode sind in [31] zu finden.…”

Section: Analyse Der Gescannten Schweißnahtgeometrieunclassified

Automatisierte Schweißnahtnachbehandlung für Offshore‐Windenergieanlagen

et al. 2022

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Für die Umsetzung der klimapolitischen Ziele ist eine wirtschaftliche und ressourcenschonende Bauweise von Offshore‐Windenergieanlagen (OWEA) dringend erforderlich. Die Erhöhung der anzusetzenden Ermüdungsfestigkeit durch den Einsatz hochfester Stähle und durch die Anwendung von Schweißnahtnachbehandlungsmethoden bietet großes Potenzial zur Senkung des Materialeinsatzes und der Kosten bei Monopiles. Speziell in der automatisierten Fertigungskette der OWEA bieten sich automatisierte Prozesse wie das Festwalzen an. Festwalzen ist ein im Maschinenbau etabliertes mechanisches Bearbeitungsverfahren zur Erhöhung der Verschleiß‐ und Ermüdungsfestigkeit von metallischen Komponenten. Der vorliegende Aufsatz stellt Ergebnisse des Festwalzens als neuartige Nachbehandlungsmethode zur Erhöhung der Ermüdungsfestigkeit von Schweißnähten dar. Es werden die Oberflächen‐ und Randzoneneigenschaften UP‐geschweißter Stumpfnahtstöße aus einem Baustahl der Güte S355MLO vor und nach dem Festwalzen gezeigt. Um den Einfluss des Festwalzens auf die Nahtgeometrie zu quantifizieren, werden zusätzlich Ergebnisse von Messungen mit einem Laserliniensensor dargestellt. Abschließend werden die Ergebnisse der Ermüdungsversuche diskutiert, die das große Potenzial des Festwalzprozesses als Schweißnahtnachbehandlungsmethode aufzeigen.

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Automated geometry measurement and deep rolling of butt welds

Cited by 3 publications

References 29 publications

Development of an automated quality assurance approach for welded joints

Development of an automated quality assurance approach for welded joints

Multi-Layer and Multi-Channel Dynamic Routing Planning and Initial Point Positioning of Weld Seam Based on Machine Vision

Automatisierte Schweißnahtnachbehandlung für Offshore‐Windenergieanlagen

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