Open Access
Mechanics & Industry
Volume 19, Number 4, 2018
Article Number 407
Number of page(s) 12
Published online 16 November 2018
  1. N.T. Khiem, H.T. Tran, A procedure for multiple crack identification in beam-like structures from natural vibration mode, J. Vib. Control 20 (2014) 1417–1427 [CrossRef] [Google Scholar]
  2. S. Zheng, X. Liang, H. Wang, D. Fan, Detecting multiple cracks in beams using hierarchical genetic algorithms, J. Vibroeng. 16 (2014) 1153 [Google Scholar]
  3. A.R. Daneshmehr, A. Nateghi, D.J. Inman, Free vibration analysis of cracked composite beams subjected to coupled bending-torsion loads based on a first order shear deformation theory, Appl. Math. Model. 37 (2013) 10074–10091 [CrossRef] [Google Scholar]
  4. R.S. Pawar, S.H. Sawant, An overview of vibration analysis of cracked cantilever beam with non-linear parameters and harmonic excitations, Int. J. Innov. Technol. Exploring Eng. 8 (2014) 53–55 [Google Scholar]
  5. M.A. Musmar, M.I. Rjoub, M.A. Hadi, Nonlinear finite element analysis of shallow reinforced concrete beams using SOLID65 element, Elastic, 25743 (2006) 0–3 [Google Scholar]
  6. P. Parandaman, M. Jayaraman, Finite element analysis of reinforced concrete beam retrofitted with different fiber composites, Middle East J. Sci. Res. 22 (2014) 948–953 [Google Scholar]
  7. J.K. Sinha, M.I. Friswell, S. Edwards, Simplified models for the location of cracks in beam structures using measured vibration data, J. Sound Vib. 251 (2002) 13–38 [CrossRef] [Google Scholar]
  8. S. Caddemi, A. Morassi, Multi-cracked Euler-Bernoulli beams: mathematical modeling and exact solutions, Int. J. Solids Struct. 50 (2013) 944–956 [CrossRef] [Google Scholar]
  9. W.L. Chiang, D.J. Chiou, C.W. Chen, J.P. Tang, W.K. Hsu, T.Y. Liu, Detecting the sensitivity of structural damage based on the Hilbert-Huang transform approach, Eng. Comput. 27 (2010) 799–818 [CrossRef] [Google Scholar]
  10. H.P. Chen, N. Bicanic, Identification of structural damage in buildings using iterative procedure and regularisation method, Eng. Comput. 27 (2010) 930–950 [CrossRef] [Google Scholar]
  11. S. Parsazad, E. Saboori, A. Allahyar, Data selection for semi-supervised learning. arXiv preprint, arXiv:1208.1315 (2012) [Google Scholar]
  12. B. Chen, C. Zang, Artificial immune pattern recognition for structure damage classification, Comput. Struct. 87 (2009) 1394–1407 [CrossRef] [Google Scholar]
  13. J. Strackeljan, K. Leiviskä, Artificial immune system approach for the fault detection in rotating machinery, Proc. CM (2008) 1365–1375 [Google Scholar]
  14. S. Tamandani, M. Hosseina, M., Rostami, A. Khanjanzadeh, Using clonal selection algorithm to optimal placement with varying number of distributed generation units and multi objective function, World J. Control Sci. Eng. 2 (2014) 12–17 [Google Scholar]
  15. M. Vairamuthu, S. Porselvi, A.N. Balaji, J. Rajesh Babu, Artificial immune system algorithm for multi objective flow shop scheduling problem, Int. J. Innov. Res. Sci. Eng. Technol. 3 (2014) 1391–1395 [Google Scholar]
  16. H. Yang, T. Li, X. Hu, F. Wang, Y. Zou, A survey of artificial immune system based intrusion detection, Sci. World J. (2014) 1–11 [Google Scholar]
  17. N. Khaji, M. Mehrjoo, Crack detection in a beam with an arbitrary number of transverse cracks using genetic algorithms, J. Mech. Sci. Technol. 28 (2014) 823 [CrossRef] [Google Scholar]
  18. M.T. Vakil-Baghmisheh, M. Peimani, M.H. Sadeghi, M.M. Ettefagh, Crack detection in beam-like structures using genetic algorithms, Appl. Soft Comput. 8 (2008) 1150–1160 [CrossRef] [Google Scholar]
  19. Y.G. Xu, G.R. Li, Z.P. Wu, A novel hybrid genetic algorithm using local optimizer based on heuristic pattern move, Appl. Artif. Intell. 15 (2001) 601–631 [CrossRef] [Google Scholar]
  20. H. Guan, Y. Chen, P. Du, Study of an improved clonal selection algorithm and its application, Int. J. Digit. Content Technol. Appl. 6 (2012) 323 [Google Scholar]
  21. H. Tada, P.C. Paris, G.R. Irwin, The stress analysis of cracks, Handbook, Del Research Corporation, 1973 [Google Scholar]

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