Neural network system for identification of non-destructive testing signals

Abstract

In this article the technique of using neural network algorithms in non-destructive control systems is considered. The block diagram of the neural network system for identification of the safe state of fixed objects is presented. The topology of the radial basis and the recurrent Elman network for the initialization of neural structures is determined. Methods and criteria for training the neural network in the process of non-destructive testing of the object are presented.