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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.
Ziel des WelDX Forschungsvorhabens ist es, den Austausch wissenschaftlicher Forschungsdaten aus dem Bereich der Schweißtechnik auf Basis eines einheitlichen Open Source Dateiformates zu ermöglichen und damit die Einhaltung und Dokumentation geeigneter Qualitätsstandards zu fördern. Im Zuge der Projektarbeit wird die Zusammenarbeit und der Wissenstransfer schweißtechnischer Institute zunächst auf nationaler Ebene gefördert und die Bildung eines von der Fachcommunity getragenen Kuratoriums zur Betreuung und Weiterentwicklung des Dateiformates und der Ausarbeitung zugehöriger Qualitätsstandards angestrebt.
Der Vortrag gibt eine Übersicht zur Motivation, der technischen Umsetzung des Dateiformates sowie möglicher Anwendungsfälle.
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.
An experimental setup to integrate laser sensor into conventional GMAW setups via a unified control architecture is described. The setup is used to automate and monitor narrow-gap GMAW and control the electrode weaving motion as well as the resulting height of each weld layer. A way to develop GMAW arc-sensors using artificial neural networks using the setup is shown.
The control system is connected to a relational database to store various process measurements. The database can be accessed to filter previous weldments by numerous criteria which allows modelling of process parameter correlation among vast datasets. Such models can be used for process monitoring and control in future applications.
The talk gives an introduction into gas metal arc welding and its relation to plasma science as well as current challenges in welding research concerning research data management and the application of the FAIR principles.
The WelDX project is introduced and the main goals are discussed and contrasted with the current features of the weldx API.
Different internal and public facing use cases focusing on research data management and their implementation using weldx are presented.
The interactive part of the presentation displays some advanced multi layer use cases and data analysis using the weldx API as well as the integration of materials properties into weldx.
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.
The presentation shows the current development status of the Welding Data Exchange (weldx) format based on the Advanced Scientific Data Format (ASDF).
The use of a complete single pass arc welding experiment example stored in a single weldx file and validated against a predefined schema definition is presented.
The example includes generic experimental metadata, the workpiece geometry and materials definition following associated standards, the weld process spatial movement description, the welding process parameter descriptions and welding process measurements. The inclusion of 3D scan data of the workpiece description is also included.
The full code and data is available on GitHub: https://github.com/BAMWelDX/IIW2021_joint_intermediate_CXII
Scientific welding data covers a wide range of physical domains and timescales and are measured using various different sensors. Complex and highly specialized experimental setups at different welding institutes complicate the exchange of welding research data further. The WelDX research project aims to foster the exchange of scientific data inside the welding community by developing and establishing a new open source file format suitable for the documentation of experimental welding data and upholding associated quality standards. In addition to fostering scientific collaboration inside the national and international welding community an associated advisory committee will be established to oversee the future development of the file format. The proposed file format will be developed with regard to current needs of the community regarding interoperability, data quality and performance and will be published under an appropriate open source license. By using the file format objectivity, comparability and reproducibility across different experimental setups can be improved.
The talk motivates and introduces the WelDX project and the proposed solutions for current challenges in the field of research data management and Open Science practices in welding research.
Using an exemplary welding dataset based on the joint and welding process design of offshore structures, advanced data fusion and analysis capabilities are demonstrated.
The dataset shown consists of a complex welding sequence covering multiple weld layers with varying process parameters and adaptive weaving motions to cover manufacturing tolerances. In the presentation, an interactive exploration of the dataset contents in the spatial domain is presented. Furthermore, transformation between spatial and time domain of the data is demonstrated.
In addition to data gathered during the welding process, the integration of downstream testing data and results is also explained. For demonstration, integration of weld seam cross section images and Vickers hardness mapping test results into the dataset are explained an demonstrated. The testing data is set into context with the welding process information.
Finally, implications for advancements in research data management for WAAM and AI applications are discussed.
Die Anwendung von Leichtbauprinzipien im Stahlbau, wie z.B. die Verwendung von aufgelösten Tragstrukturen, sog. Jackets-Fundamenten, bietet ein großes Potential zur Reduzierung des Ressourcenverbrauchs, insbesondere im Hinblick auf die benötigte Stahlmenge.
In diesem Vortrag zeigen wir die Potenziale einer vollständigen Digitalisierung der schweißtechnischen Fertigungs- und Prüfkette auf, um eine vollautomatische Fertigung sowie Qualitätsprüfung von Rohrknoten als Schlüsselelement von Jackets-Fundamenten zu ermöglichen. Darüber hinaus wird der Zusammenhang zwischen der Geometrie der Nahtform und der resultierenden Ermüdungsfestigkeit durch numerische Methoden unter Einbeziehung bionischer Prinzipien bewertet. Es wird gezeigt, dass Hohlprofilknoten vollautomatisch unter Berücksichtigung von Geometrietoleranzen geschweißt werden können. Darüber hinaus konnte die Nahtform gemäß den numerischen Modellen hergestellt werden, was ein großes Potenzial für eine verlängerte Lebensdauer bietet. Anschließend werden die Verbesserungen bei der Ressourceneffizienz und die Reduzierung der Kohlendioxidemissionen durch eine Lebenszyklusanalyse bewertet.