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Shock and Vibration
Volume 2015, Article ID 648097, 15 pages
http://dx.doi.org/10.1155/2015/648097
Research Article

A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring

1CoDAlab, Department of Applied Mathematics III, Universitat Politècnica de Catalunya (UPC), 08036 Barcelona, Spain
2Faculty of Electronic Engineering, Universidad Santo Tomás, Bogotá, Colombia
3CoDAlab, Department of Applied Mathematics III, Escola Universitària d’Enginyeria Tècnica Industrial de Barcelona (EUETIB), Universitat Politècnica de Catalunya (UPC), Comte d’Urgell 187, 08036 Barcelona, Spain

Received 27 February 2015; Revised 5 May 2015; Accepted 14 May 2015

Academic Editor: Haifeng Gao

Copyright © 2015 Maribel Anaya 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.

Citations to this Article [10 citations]

The following is the list of published articles that have cited the current article.

  • M. Anaya, D.A. Tibaduiza, E. Forero, R. Castro, and F. Pozo, “An acousto-ultrasonics pattern recognition approach for damage detection in wind turbine structures,” 2015 20th Symposium on Signal Processing, Images and Computer Vision (STSIVA), pp. 1–5, . View at Publisher · View at Google Scholar
  • Francesc Pozo, and Yolanda Vidal, “Wind Turbine Fault Detection through Principal Component Analysis and Statistical Hypothesis Testing,” Energies, vol. 9, no. 1, pp. 3, 2015. View at Publisher · View at Google Scholar
  • Julián Navarro-García, Luis Roberto Mercado-Díaz, and Jorge Alberto Jaramillo-Garzón, “A comparison of class-balance strategies for SVM in the problem of protein function prediction,” 2015 20th Symposium on Signal Processing, Images and Computer Vision, STSIVA 2015 - Conference Proceedings, 2015. View at Publisher · View at Google Scholar
  • E Forero, D Tibaduiza, M Anaya, and R Castro, “Detection and characterization of defects in moving parts of wind turbines,” IOP Conference Series: Materials Science and Engineering, vol. 138, pp. 012015, 2016. View at Publisher · View at Google Scholar
  • D Tibaduiza, M Anaya, E Forero, R Castro, and F Pozo, “A Sensor Fault Detection Methodology applied to Piezoelectric Active Systems in Structural Health Monitoring Applications,” IOP Conference Series: Materials Science and Engineering, vol. 138, pp. 012016, 2016. View at Publisher · View at Google Scholar
  • Jaime Vitola, Francesc Pozo, Diego Tibaduiza, and Maribel Anaya, “Distributed Piezoelectric Sensor System for Damage Identification in Structures Subjected to Temperature Changes,” Sensors, vol. 17, no. 6, pp. 1252, 2017. View at Publisher · View at Google Scholar
  • Jaime Vitola, Francesc Pozo, Diego Tibaduiza, and Maribel Anaya, “A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications,” Sensors, vol. 17, no. 2, pp. 417, 2017. View at Publisher · View at Google Scholar
  • Francesc Pozo, and Yolanda Vidal, “Damage and Fault Detection of Structures Using Principal Component Analysis and Hypothesis Testing,” Advances in Principal Component Analysis, pp. 137–191, 2017. View at Publisher · View at Google Scholar
  • Maria-Giovanna Masciotta, Alberto Barontini, Luís F. Ramos, Paulo Amado-Mendes, and Paulo B. Lourenço, “A Bio-inspired Framework for Highly Efficient Structural Health Monitoring and Vibration Analysis,” Experimental Vibration Analysis for Civil Structures, vol. 5, pp. 455–468, 2017. View at Publisher · View at Google Scholar
  • Francesc Pozo, Yolanda Vidal, and Óscar Salgado, “Wind Turbine Condition Monitoring Strategy through Multiway PCA and Multivariate Inference,” Energies, vol. 11, no. 4, pp. 749, 2018. View at Publisher · View at Google Scholar