A sensor enabled robotic strategy for automated Defect-Free Multi-Pass High-Integrity welding. (December 2022)

• Record Type: Journal Article
• Authors: Charalampos Loukas, Names:; Warner, Veronica; Jones, Richard; MacLeod, Charles N.; Vasilev, Momchil; Mohseni, Ehsan; Dobie, Gordon; Sibson, Jim; Pierce, Stephen G.; Gachagan, Anthony
• Is Part Of: Materials & design. Volume 224(2022)
• Publication Date: 2022-12
• Subjects: Robotic Arc Welding -- Path Planning -- Defects -- Multi-Pass -- V-groove -- Non-Destructive Testing; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2022.111424
• Languages: English
• ISSNs: 0264-1275

Abstract

Graphical abstract: Highlights: An adaptive robotic welding approach is presented for fully automated defect free multi-pass robotic arc welding. A user-initiated, workpiece localization method without any prior component knowledge is introduced utilizing Hand-Eye calibration. An algorithmic process compensates for human-vision error by adapting the welding process to the pre-welded specimen for on-the-fly welding path generation. Robotically experimental verification on welded joints of single sided butt joints is demonstrated. Non-Destructive Testing in the form of Ultrasound Testing validates the high integrity and repeatable quality of the proposed work. Abstract: High-integrity welds found in safety–critical industries require flaw-free joints, but automation is challenging due to low-volume, often-unique nature of the work, alongside high-uncertainty part-localisation. As such, robotic welding still requires tedious manually taught paths or offline approaches based on nominal Computer-Aided-Design (CAD). Optical and laser sensors are commonly deployed to provide online adjustment of pre-defined paths within controlled environments. This paper presents a sensor-driven approach for defect-free welding, based on the as-built joint geometry alongside the requirement for no-accurate part localisation or CAD knowledge. The approach a) autonomously localises the specimen in the scene without CAD requirement, b) adapts and generates accurate welding paths unique to the as-built workpiece and c) generates robot kinematics based on an external-control strategy. The proposed approach is validated through experiments of unconstrained placed joints, where the increased accuracy of the generated welding paths, with no common seam tracking, is validated with an average error of 0.12 mm, 0.4°. Coupling with a multi-pass welding framework, the deployment of fully automated robotic arc welding takes place for different configurations. Non-Destructive-Testing (NDT) in the form of Ultrasound-Testing (UT) inspection validates the repeatable and flaw-free nature of the sensory-driven approach, exploiting direct benefits in quality alongside reduced re-work.