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Eingeladener Vortrag
- nein (64)
Zur Effizienzsteigerung beim Einsatz von Lichtbogenverfahren für Fügeaufgaben im Dickblechbereich werden häufig angepasste Verfahren mit möglichst geringer Nahtquerschnittsfläche angewendet, beispielsweise das MSG-Engspaltschweißen für I-Nähte. Die Herausforderung für die Automatisierung des Verfahrens besteht neben der komplexen Prozessführung auch in der oftmals schlechten Zugänglichkeit der Prozesszone für optische Sensorik, weswegen verstärkt auf prozessorientierte Sensorik zurückgegriffen wird. Zur Steigerung des Prozessverständnisses und Entwicklung neuer Regelungskonzepte wurde ein Versuchsaufbau umgesetzt, der sowohl optische Messsysteme als auch prozessorientierte Sensorik in einer gemeinsamen Steuerungsumgebung vereint. Die umfassende prozessbegleitende Sensorik ermöglicht die sukzessive Erweiterung des Prozesswissens, welches direkt zur Umsetzung neuer Steuer- und Regelalgorithmen basierend auf Regressionsmodellen genutzt werden kann. Der gemeinsame Einsatz optischer und prozessorientierter Sensorik wurde zur Auslegung eines Lichtbogensensors zur Höhenführung genutzt. Die Versuchsdurchführung mit dem Ziel der Ableitung nichtlinearer Regressionsmodelle erfolgt automatisiert mit Hilfe eines optischen Sensors. Der Vorteil dieses Verfahrens liegt dabei neben der schnellen Umsetzbarkeit in der direkten Korrelation der Messwerte zu realen physikalischen Systemgrößen und der schnellen Adaption auf unterschiedliche Schweißparameter und -prozesse.
An approach to develop an arc sensor for gap-width estimation during automated NG-GMAW with a weaving electrode motion is introduced by combining arc sensor readings with optical measurement of the groove shape to allow precise analyses of the process. The two test specimen welded for this study were designed to feature a variable groove geometry in order to maximize efficiency of the conducted experimental efforts, resulting in 1696 individual weaving cycle records with associated arc sensor measurements, process parameters and groove shape information. Gap width was varied from 18 to 25 mm and wire feed rates in the range of 9 to 13 m/min were used in the course of this study. Artificial neural networks were used as a modelling tool to derive an arc sensor for estimation of gap width suitable for online process control that can adapt to changes in process parameters as well as changes in the weaving motion of the electrode. Wire feed rate, weaving current, sidewall dwell currents and angles were used as inputs to calculate the gap width. Evaluation the proposed arc sensor model show very good estimation capabilities for parameters sufficiently covered during experiments.
The increasing adoption of Open Science principles has been a prevalent topic in the welding science community over the last years. Providing access to welding knowledge in the form of complex and complete datasets in addition to peer-reviewed publications can be identified as an important step to promote knowledge exchange and cooperation. There exist previous efforts on building data models specifically for fusion welding applications; however, a common agreed upon implementation that is used by the community is still lacking. One proven approach in other domains has been the use of an openly accessible and agreed upon file and data format used for archiving and sharing domain knowledge in the form of experimental data. Going into a similar direction, the welding community faces particular practical, technical, and also ideological challenges that are discussed in this paper. Collaboratively building upon previous work with modern tools and platforms, the authors motivate, propose, and outline the use of a common file format specifically tailored to the needs of the welding research community as a complement to other already established Open Science practices. Successfully establishing a culture of openly accessible research data has the potential to significantly stimulate progress in welding research.
Der Beitrag stellt am Beispiel eines für adaptive MSG-Lichtbogen-Engspaltschweißungen im Dickblech-Bereich entwickelten Versuchsstandes ein Automatisierungskonzept für vernetzte kommerziell verfügbare Anlagenkomponenten über ein zentrales echtzeitfähiges Steuersystem auf Basis des EtherCAT-Protokolls vor. Der Fokus liegt hierbei auf der Eignung für Aufgaben im Bereich der Qualitätssicherung sowie Forschung und Entwicklung leistungsfähiger Algorithmen zur Prozessüberwachung und -regelung. Die sich daraus ergebende Vielzahl zu messender und steuernder Parameter stellen vor allem in Verbindung mit präzisen und hochfrequenten Messgeräten höchste Anforderungen an die Datenverarbeitung sowohl in Echtzeit als auch zur Auswertung nach dem Prozess. Die Einbindung etablierter Programmiertools wie MATLAB/Simulink in gängigen Automatisierungsstandards ermöglichen flexible und innovative Forschungsarbeit.
Durch die automatisierte Datenerfassung in einer übergelagerten Datenbank stehen die Messungen sämtlicher Schweißvorgänge jederzeit zur Entwicklung neuer Abläufe zur Prozessteuerung und -regelung oder zur Verbesserung der bestehenden Algorithmen zur Verfügung, was insbesondere den sukzessiven Aufbau komplexer Regressionsmodelle aus der Anwendung heraus ermöglicht.
Als Applikationsbeispiel wird die Entwicklung eines dynamischen Lichtbogensensors vorgestellt und diskutiert. Die Versuchsdurchführung mit dem Ziel der Ableitung nichtlinearer Regressionsmodelle erfolgt automatisiert mithilfe eines optischen Sensors. Der Vorteil dieses Verfahrens liegt dabei neben der schnellen Umsetzbarkeit in der direkten Korrelation der Messwerte zu realen physikalischen Systemgrößen und der schnellen Adaption auf unterschiedliche Schweißparameter und -prozesse.
An approach to develop an arc sensor for gap width estimation during automated NG-GMAW with a weaving electrode motion is introduced by combining arc sensor readings with optical measurements of the groove shape to allow precise analyses of the process. The two test specimen welded for this study were designed to feature a variable groove geometry in order to maximize efficiency of the conducted experimental efforts, resulting in 1696 individual weaving cycle records with associated arc sensor measurements, process parameters and groove shape information. Gap width was varied from 18 mm to 25 mm and wire feed rates in the range of 9 m/min to 13 m/min were used in the course of this study. Artificial neural networks were applied as a modelling tool to derive an arc sensor for estimation of gap width suitable for online process control that can adapt to changes in process parameters as well as changes in the weaving motion of the electrode. Wire feed rate, weaving current, sidewall dwell currents and angles were defined as inputs to calculate the gap width. The evaluation of the proposed arc sensor model shows very good estimation capabilities for parameters sufficiently covered during the experiments.
Offshore wind energy plays an important role for the desired transition towards a carbon dioxide free industry within the next decades. However, the grounding of the offshore wind plants governs the overall installation process besides bureaucratic bottlenecks.
The application of lightweight principles in steel construction, e.g. the usage dissolved load-bearing structures, so called Jackets foundations, offer great potential in reducing the resource consumption, especially with respect to the needed amount of steel.
In this context this paper focuses on a fully digitalization of the welding manufacturing and as well as testing chain to enable a fully automated manufacturing as well as quality assessment of tubular nodes as key element of Jackets foundation structures. Furthermore, the relationship between the seam shape geometry and resulting fatigue strength is evaluated by numerical methods incorporating bionic principles. It is shown that tubular nodes can be welded fully automatically taking geometry tolerances into account. Moreover, the seam shape could be manufactured as requested by the numerical models which offers great potential for an extended lifetime. Subsequently, the improvements in resource efficiency and reduction of carbon dioxide emissions are evaluated by a life-cycle-assessment.
Digital vernetzte Sensorik für Erfassung von Prozessgrößen
- Datenbankstruktur zur Integration sämtlicher Messgrößen
- In-situ Korrelation zwischen Prozessparametern und
Schweißergebnis auf Basis künstlicher Intelligenz
- Sukzessiver Aufbau an Prozesswissen selbstlernendes
System
- Prozessregelung MSG-Engspaltschweißen
-Adaptiver Pendelwinkelkeine Vorgabe durch Anwender notwendig gleichmäßiger Flankeneinbrand
-Füllgradregelung Vorgabe einer Zielaufbauhöhe durch Anwender autarke Regelung der Prozessgrößenfür gleichmäßige Füllhöhe bei Variation der Spaltbreite