2-D defect reconstruction from MFL signals based on genetic optimization algorithm

Proceedings of the IEEE International Conference on Industrial Technology

Volumn 2005, Issue , 2005, Pages 508-513

  Wenhua, Han ^a   Peiwen, Que ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

DEFECTS; GENETIC ALGORITHMS; INVERSE PROBLEMS; MAGNETIC FLUX; OPTIMIZATION; PROBLEM SOLVING; RADIAL BASIS FUNCTION NETWORKS;

GENETIC OPTIMIZATION ALGORITHMS; MAGNETIC FLUX LEAKAGE (MFL);

IMAGE RECONSTRUCTION;

EID: 33847292342     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIT.2005.1600691     Document Type: Conference Paper

References (8)

1. P. Ramuhalli, L. Udpa, S.S. Udpa, "Electromagnetic NDE signal inversion by function-approximation neural networks", IEEE Transactions on Magnetics, vol. 38, no. 6, pp. 3633-3642, November, 2002.
2. J. Lim, Data Fusion for NDE Signal Characterization, Iowa State University, Michigan, 2001
3. K. Hwang, S. Mandayam, S. S. Udpa, L. Udpa, W. Lord and M. Atzal, "Characterization of gas pipeline inspection signals using wavelet basis function neural networks", NDT & E International, vol. 33, no. 8, pp. 531-545, December, 2000
4. P. Ramuhalli, L. Udpa, S.S. Udpa, "Neural network-based inversion algorithms in magnetic flux leakage nondestructive evaluation", Journal of Applied Physics, vol. 93, no. 103, pp. 8274-8276, May, 2003
5. D. E. Goldberg, Genetic Algorithms in Search, Optimzation & Machine Learning, Addison-Wesley, 1989
6. M. Srinivas, L.M. Patnaik, "Genetic algorithms: a survey", Computer, vol. 27, no. 6, pp. 17-26, June, 1994
7. S. Haykin, Neural networks: A comprehensive Foundation. Englewood Cliffs, NJ: Prentice-hall, 1994.
8. S. Chen, C. F. N. Cowan, P. M. Grant, "Orthogonal Least Squares Learning Algorithm for Radial Basis Function Networks", IEEE Transactions on Neural Networks, vol. 2, no. 2, pp. 302-309, March, 1991