275
Views
7
CrossRef citations to date
0
Altmetric
Articles

Soft computing methods in the analysis of elastic wave signals and damage identification

Pages 945-956 | Received 02 Jan 2013, Accepted 04 Jan 2013, Published online: 01 Feb 2013

References

  • Giurgiutiu, V, 2005. Tuned lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring, J. Intell. Mater. Syst. Struct. 16 (2005), pp. 291–305.
  • Lee, BC, and Staszewski, W, 2007. Lamb wave propagation modeling for damage detection: II, Damage monitoring strategy. Smart Mater. Struct. 16 (2007), pp. 260–274.
  • Staszewski, W, Lee, BC, Mallet, L, and Scarpa, F, 2004. Structural health monitoring using laser vibrometry: I, Lamb wave sensing. Smart Mater. Struct. 13 (2004), pp. 251–260.
  • Nazarko, P, and Ziemiański, L, 2010. Towards application of soft computing in structural health monitoring, in artificial intelligence and soft computing, LNAI 6114. Berlin: Springer-Verlag; 2010. pp. 56–63.
  • Nazarko P. Comparative analysis of auto-associative NNs and SVMs applied to patterns classification in the damage detection system. In: 19th International Conference on Computer Methods in Mechanics. 2011 May 9–12; Warsaw (Poland). p. 379–380..
  • Waszczyszyn, Z, and Ziemiański, L, 2005. Parameter identification of materials and structures, CISM Courses and Lectures. 469 (2005), pp. 256–340.
  • Nazarko, P, and Ziemiański, L, 2009. "Novelty detection and damage evaluation in laboratory models". In: Cunha, A, and Rodrigues, J, eds. SMART’09 Smart Structures and Materials. FEUP The Faculty of Engineering of the University of Porto: Portugal; 2009. pp. 359–360.
  • Madzarov, G, Gjorgjevikj, D, and Chorbev, I, 2009. A multi-class SVM classifier utilizing binary decision tree, Informatica. 33 (2009), pp. 233–241.
  • Worden, K, and Dulieu-Barton, JM, 2004. An overview of intelligent fault detection in systems and structures, Struct. Health Monit. 3 (2004), pp. 85–98.
  • Hernandez-Garcia, MR, and Sanchez-Silva, M, 2007. "Learning machines for structural damage detection". In: Lagaros, ND, and Tsompanakis, Y, eds. Intelligent computational paradigms in earthquake engineering. Hershey, PA: Idea Group; 2007. pp. 158–187.
  • Kuźniar, K, and Waszczyszyn, Z, 2006. Neural networks and principal component analysis for identification of building natural periods, J. Comput. Civil Eng. 20 (2006), pp. 431–436.
  • Nazarko, P, and Ziemiański, L, 2011. Application of artificial neural networks in the damage identification of structural elements, Comput. Assist. Mech. Eng. Sci. 18 (2011), pp. 175–189.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.