Title :
Genetic algorithms for nondestructive testing in crack identification
Author :
Arkadan, A.A. ; Sareen, T. ; Subramaniam, S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
fDate :
11/1/1994 12:00:00 AM
Abstract :
A method to identify the nature of a crack on the surface of a region using nondestructive testing (NDT) and inverse problem methodology is presented. A genetic algorithm (GA) based approach, which involves a global search to avoid local minima, is presented and applied to solve the inverse problem of identifying the position, shape and the orientation of a surface crack. A fine tuning algorithm is combined with the GA to reach the optimum solution
Keywords :
crack detection; genetic algorithms; inverse problems; nondestructive testing; crack identification; fine tuning algorithm; genetic algorithms; global search; inverse problem methodology; local minima; nondestructive testing; optimum solution; surface crack; Artificial neural networks; Electronic switching systems; Genetic algorithms; Genetic mutations; Inverse problems; Nondestructive testing; Shape; Simulated annealing; Stochastic processes; Surface cracks;
Journal_Title :
Magnetics, IEEE Transactions on
