The Use of Artificial Neural Networks in Nondestructive Testing of Aircraft Parts

A methodology for nondestructive testing of aircraft parts based on the use of artificial intelligence methods has been proposed. A special feature of the developed methodology is the use of machine learning when analyzing the inspection results. The factors influencing the effectiveness of using the artificial intelligence methods in the inspection of aircraft parts are analyzed. A practical example shows the use of artificial neural networks in solving problems of processing the results of measurements of contact potential differences on the surface of metals and alloys.