Applying and validating neural network technology for nondestructive evaluation of materials

The application of neural network technology to nondestructive evaluation (NDE) of materials is considered. Based on a limited ultrasonic NDE study using neural networks, it is demonstrated that the neural network technology is feasible for classifying well-defined defects in NDE. In other NDE problems in which image data can be used, neural networks also are likely to perform very well. At this stage of development, however, the conventional pattern recognition techniques cannot be completely replaced by the neural network technology