Abstract
This article describes a novel approach for analyzing elastic wave signals to obtain a solution to simple inverse source problems. By using a simulated intelligent system that resembles the structure of a neural network and an acoustic source with its associated field of elastic waves in a plate, a set of pattern vectors is generated. The memory of the system is formed through a learning process in which a systematic series of experiments is presented to the system. In the experiments described here, the system was trained using simulated acoustic emission signals generated by a normal force acting on a thick plate to which information about the source related to its location and characteristics was appended. It is demonstrated, using such a trained system, that one can recover the characteristics of an unknown source from the acoustic signals emitted by it. It is also shown that one can synthesize from the memory the acoustic signals corresponding to an arbitrary source without using any elastodynamic theory.
Published Version
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