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Journal of Sensors
Volume 2012 (2012), Article ID 318038, 11 pages
Research Article

Welding Diagnostics by Means of Particle Swarm Optimization and Feature Selection

1Photonics Engineering Group, University of Cantabria, 39005 Santander, Spain
2Hamlyn Centre for Robotic Surgery, Institute of Global Health Innovation, and Department of Surgery and Cancer, Imperial College London, London SW7 2AZ, UK

Received 1 February 2012; Accepted 10 April 2012

Academic Editor: Francesco Baldini

Copyright © 2012 J. Mirapeix et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In a previous contribution, a welding diagnostics approach based on plasma optical spectroscopy was presented. It consisted of the employment of optimization algorithms and synthetic spectra to obtain the participation profiles of the species participating in the plasma. A modification of the model is discussed here: on the one hand the controlled random search algorithm has been substituted by a particle swarm optimization implementation. On the other hand a feature selection stage has been included to determine those spectral windows where the optimization process will take place. Both experimental and field tests will be shown to illustrate the performance of the solution that improves the results of the previous work.