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Villanueva Roldán, Pedro

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https://academica-e.unavarra.es/handle/2454/50166

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Villanueva Roldán

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Pedro

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Ingeniería

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0000-0003-0865-3789

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2772

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2023 - 20242
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Subject: Thick joints × Author: Aldalur, Eider ×

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Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationOpen Access
    Advanced welding automation: Intelligent systems for multipass welding in Butt Double V-Groove and Tee Double Bevel configurations
    (Elsevier, 2024-12-01) Curiel Braco, David; Suárez, Alfredo; Veiga Suárez, Fernando; Aldalur, Eider; Villanueva Roldán, Pedro; Ingeniería; Ingeniaritza
    The paper addresses the imperative shift towards automation in welding processes, leveraging advanced technologies such as industrial robotic systems. Focusing on the reconstruction and classification of weld joints, it introduces a methodology for automatic trajectory determination. Utilizing a laser profilometer mounted on the robot, weld joints are reconstructed in three di- mensions, and spurious data is filtered out through signal processing. A classification algorithm, integrating signal processing and artificial intelligence, accurately categorizes joint profiles, in- cluding V-joints and single bevel T-joints. The proposed intelligent and adaptive system enhances welding automation by analyzing point cloud data from laser scanning to optimize welding tra- jectories. This study establishes a foundational framework for further refinement and broader application in welding automation. Key Points - Introduction of a methodology for automated trajectory determination in welding processes. - Utilization of laser scanning and signal processing for reconstruction and classification of weld joints. - Implementation of an intelligent and adaptive system to optimize welding trajectories
  • Thumbnail Image
    PublicationOpen Access
    Intelligent and adaptive system for welding process automation in T-shaped joints
    (MDPI, 2023) Aldalur, Eider; Suárez, Alfredo; Curiel Braco, David; Veiga Suárez, Fernando; Villanueva Roldán, Pedro; Ingeniería; Ingeniaritza
    The automation of welding processes requires the use of automated systems and equipment, in many cases industrial robotic systems, to carry out welding processes that previously required human intervention. Automation in the industry offers numerous advantages, such as increased efficiency and productivity, cost reduction, improved product quality, increased flexibility and safety, and greater adaptability of companies to market changes. The field of welding automation is currently undergoing a period of profound change due to a combination of technological, regulatory, and economic factors worldwide. Nowadays, the most relevant aspect of the welding industry is meeting customer requirements by satisfying their needs. To achieve this, the automation of the welding process through sensors and control algorithms ensures the quality of the parts and prevents errors, such as porosity, unfused areas, deformations, and excessive heat. This paper proposes an intelligent and adaptive system based on the measurement of welding joints using laser scanning and the subsequent analysis of the obtained point cloud to adapt welding trajectories. This study focuses on the optimization of T-joints under specific welding conditions and is intended as an initial implementation of the algorithm, thus establishing a basis to be worked on further for a broader welding application.