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Signal Processing for NDE
Nowadays, testing and evaluating of industrial equipment using nondestructive tests, is a
fundamental step in the manufacturing process. The complexity and high costs of manufacturing
industrial components, require examinations in some way about the quality and reliability of the
specimens. However, it should be noted, that in order to accurately perform the nondestructive
test, in addition to theoretical knowledge, it is also essential to have the experience and carefulness,
which requires special courses and experience with theoretical education. Therefore, in the
traditional methods, which are based on manual testing techniques and the test results depend on
the operator, there is the possibility of an invalid inference from the test data. In other words, the
accuracy of conclusion from the obtained data is dependent on the skill and experience of the
operator. Thus, using the signal processing techniques for nondestructive evaluation (NDE), it is
possible to optimize the methods of nondestructive inspection, and in other words, to improve the
overall system performance, in terms of reliability and system implementation costs.
In recent years, intelligent signal processing techniques have had a significant impact on the
progress of nondestructive assessment. In other words, by automating the processing of
nondestructive data and signals, and using the artificial intelligence methods, it is possible to
optimize nondestructive inspection methods. Hence, improve overall system performance in terms
of reliability and Implementation costs of the system. This chapter reviews the issues of intelligent
processing of nondestructive testing (NDT) signals