2026-09-24T17:30:53Zhttps://bura.brunel.ac.uk/oai/request

oai:bura.brunel.ac.uk:2438/55502014-11-01T12:15:55Zcom_2438_58col_2438_3672

Ralf, B Bevis, MJ Siores, E 2011-07-12T14:36:06Z 2011-07-12T14:36:06Z 1988 http://bura.brunel.ac.uk/handle/2438/5550 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University. The implementation of robotic technology into welding processes is made difficult by the inherent process variables of part location, fit up, orientation and repeatability. Considering these aspects, to ensure weld reproducibility consistency and quality, advanced adaptive control techniques are essential. These involve not only the development of adequate sensors for seam tracking and joint recognition but also developments of overall machines with a level of artificial intelligence sufficient for automated welding. The development of such a prototype system which utilizes a manipulator arm, ultrasonic sensors and a transistorised welding power source is outlined. This system incorporates three essential aspects. It locates and tracks the welding seam ensuring correct positioning of the welding head relatively to the joint preparation. Additionally, it monitors the joint profile of the molten weld pool and modifies the relevant heat input parameters ensuring consistent penetration, joint filling and acceptable weld bead shape. Finally, it makes use of both the above information to reconstruct three-dimensional images of the weld pool silhouettes providing in-process inspection capabilities of the welded joints. Welding process control strategies have been incorporated into the system based on quantitative relationships between input parameters and weld bead shape configuration allowing real-time decisions to be made during the process of welding, without the need for operation intervention. Submitted by Otue Ekong (lbsrooe@brunel.ac.uk) on 2011-07-12T14:35:53Z No. of bitstreams: 1 FulltextThesis.pdf: 50412709 bytes, checksum: 5b83b399f1cac3c412cccf62687279ae (MD5) Approved for entry into archive by Otue Ekong(lbsrooe@brunel.ac.uk) on 2011-07-12T14:36:06Z (GMT) No. of bitstreams: 1 FulltextThesis.pdf: 50412709 bytes, checksum: 5b83b399f1cac3c412cccf62687279ae (MD5) Made available in DSpace on 2011-07-12T14:36:06Z (GMT). No. of bitstreams: 1 FulltextThesis.pdf: 50412709 bytes, checksum: 5b83b399f1cac3c412cccf62687279ae (MD5) British Technology Group (BTG) en Brunel University School of Engineering and Design PhD Theses http://bura.brunel.ac.uk/bitstream/2438/5550/1/FulltextThesis.pdf Robotic technology Welding processes Seam tracking Joint recognition Artificial intelligence Development of a real-time ultrasonic sensing system for automated and robotic welding Thesis