MFL signals and artificial neural networks applied to detection and classification of pipe weld defects
暂无分享,去创建一个
Luis Volnei Sudati Sagrilo | João M.A. Rebello | A. A. Carvalho | C. S. Camerini | I.V.J. Miranda | J. Rebello | L. Sagrilo | C. Camerini | A. A. Carvalho | I.V.J. Miranda
[1] David Jiles,et al. Review of magnetic methods for nondestructive evaluation (Part 2) , 1990 .
[2] G. P. Srivastava,et al. Characterisation of metal loss defects from magnetic flux leakage signals with discrete wavelet transform , 2000 .
[3] B. P. Lathi,et al. Communication Systems , 1968 .
[4] Satish Udpa,et al. Advanced signal processing of magnetic flux leakage data obtained from seamless gas pipeline , 2002 .
[5] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .
[6] Amara Lynn Graps,et al. An introduction to wavelets , 1995 .
[7] Alan V. Oppenheim,et al. Discrete-Time Signal Pro-cessing , 1989 .
[8] David A. Bradley,et al. The use of neural networks in ultrasonic flaw detection , 1999 .
[9] R. C. Mcmaster. Nondestructive testing handbook , 1959 .
[10] Mohammad S. Obaidat,et al. An intelligent simulation methodology to characterize defects in materials , 2001, Inf. Sci..
[11] A. Masnata,et al. Neural network classification of flaws detected by ultrasonic means , 1996 .
[12] David Jiles,et al. Review of magnetic methods for nondestructive evaluation , 1988 .
[13] Yong Bai. Pipelines and risers , 2001 .
[14] Jaime B. Santos,et al. Automatic defects classification — a contribution , 2001 .
[15] J. N. H. Tiratsoo. Pipeline pigging technology , 1988 .
[16] Sophocles J. Orfanidis,et al. Introduction to signal processing , 1995 .