Application of Signal Processing and Pattern Recognition Techniques to Inverse Problems in Nde

Udpa L. and Lord W. , A discussion of the inverse problem in electromagnetic NDT, in: Review of Progress in Quantitative Nondestructive Evaluation, Vol. 5A, Thompson D.O. and Chimenti D.E. , eds, Plenum, 1986, pp. 375–382

Lord W. , personal communication.

Wing G.M. , A primer on integral equations of the first kind, SIAM, Philadelphia, 1991.

Hwang J.H. and Lord W. , Defect characterization from magnetic leakage fields, Br. J. Non-Destr. Test. (1977), 14–18.

Beissner R.E. and Sablikm M.J. , Flaw characterization by the magnetic leakage field method, Final Report SWRI Project 15–9248.

Auld B.A. , ., Improved probe-flaw interaction modeling inversion processing and surface roughness clutter, in: Review of Progress in Quantitative NDE, Vol. 2, Thompson D.O. and Chimenti D.E. , eds, Plenum, New York, 1984.

Auld B.A. , Muennemann F.G. and Riaziat M. , Quantitative modeling of flaw and responses in eddy current testing, in: Research Techniques in Nondestructive Testing, Vol. 7, Sharpe R.S. , ed., Academic Press, New York, 1984.

Sabbagh H.J. and Sabbagh D.L. , Development of a system to invert eddy current data and reconstruct flaws, Final Report, Contract No. N60921-61-C-0302 with Naval Surface Weapons Center Code R34, White Oaks Labs, June 1982.

Dunbar W.S. , Applications of the volume integral technique to modeling impedance changes due to surface cracks, in: Review of Progress in NDE Quantitative, Vol. 6A, Thompson D.O. and Chimenti D.E. , eds, Plenum, New York, 1987.

Elshafiey I. , Udpa L. and Udpa S.S. , Solution of inverse problems in electromagnetics using Hopfield networks, IEEE Trans. Magn. 31(1) 1995.

Tank D.W. and Hopfield J.J. , Simple neural optimization networks: A/D convertor, signal decision circuit and a linear programming circuit, IEEE Trans. Circuits Syst. CAS-33 (5) 1986.

Udpa L. , Imaging of electromagnetic NDE phenomena, Ph Dissertation D, Colorado State University, Fort Collins, 1986.

Hoole S.R.H. , Saldanha R. , Coulomb J.-L. and Sabonnadiere J.-C. , Inverse problem methodology and finite elements in the identification of cracks, sources, materials, and their geometry in inaccessible locations, IEEE Trans. Magn. 27(3) (1991), 3433–3443.

Zorgati R. , Lesselier D. , Duchene B. and Pons F. , Eddy current testing of anomalies in conductive materials, Part II: Quantitative imaging via deterministic and stochastic inversion techniques, IEEE Trans. Magn. 28(3) (1992), 1850–1862.

Wismer M.G. and Ludwig R. , A hybrid finite element method of moment formulation for single frequency eddy current inversion, IEEE Trans. Magn. 28(3) (1992), 1843–1849,

Turin G.L. , An introduction to matched filters, IRE Trans. Inf. Theory, IT-6 (1960), 311–329.

Mucciardi A.N. and Shankar R. , Signal processing for ISI, EPRI NP-1421, Section 4, May 1980.

Doctor P.A. , ., Pattern recognition methods for classifying and sizing eddy current using eddy current data, in: Eddy Current Characterization of Materials and Structures, ASTM STP 722(ASNT), Birnbaum G. and Free G. , eds, Philadelphia, 1981.

Ivakhenko A.G. , The group method of data handling - A rival of the method of stochastic approximation, Sov. Autom. Control 13(3) (1968).

Persoon E. and Fu K.S. , Shape discrimination using Fourier descriptors, IEEE Trans. Syst. Man Cybern. SMC-7 (3) (1977).

Zahn C.T. and Roskies R.Z. , Fourier descriptors for plane closed curves, IEEE Trans. Comput. C-21 (1972), 269–281.

Udpa S.S. and Lord W. , A fourier descriptor classification scheme for differential probe signals, Mater. Eval. 42(9), (1984), 1136–1141.

Tou J.T. and Gonzales R.C. , Pattern Recognition Principles, Addison-Wesley MA , 1974.

Lippmann R.P. , An introduction to computing with neural nets, IEEE ASSP Magazine (April, 1987), 4–21.

Rumelhart D.E. , Hinton G.E. and Williams R.J. , Learning internal representations by error propagation, in: Parallel Distributed Processing: Exploration in the Microstructure of Cognition, Rumelhart D.E. and McClelland J.L. , eds, Press MIT, 1986.

Udpa L. and Udpa S.S. , Eddy current defect characterization using neural networks, Mater. Eval. 48(3) (1990), 342–347.

Chao J. , Udpa L. and Udpa S.S. , Ultrasonic signal analysis using wavelet transform, in: Review of Progress in Quantitative NDE, Vol. 12A, Thompson D.O. and Chimenti D.E. , eds, Plenum, New York, 1993, pp. 735–742

Xie G. , Defect characterization of gas pipelines using optimal radial basis function neural networks, Thesis M.S., Iowa State University, Ames IA, May 1996.

Broomhead D.S. and Lowe D. , Multivariate functional interpolation and adaptive networks, Complex Systems 2 (1988), 321–355.

Powell M.J.D. , Radial basis function approximations to polynomials, in: Numerical Analysis, 1987 Proceedings, Dundee, U.K.

Hwang K.T. , Mandayam S. , Udpa S.S. , Udpa L. and Lord W. , A multiresolution approach for characterizing MFL signatures from gas pipeline inspections", to be presented at the Sixth IEEE Midwest Circuits and Systems Symposium, Ames, August 1996.

Mandayam S. , , Magnetic flux leakage inspection of gas pipelines; Neural networks for signal compensation and identification, Topical Report GRI-96, Contract No. 5088-271-1696.