Quality Control of a Real-Time Flight Experiment Using Neural Networks

Abstract

The paper presents some investigations on automatic processing of flight information. The aim of this investigation is to reduce the cost and timing required for aviation equipment testing. The algorithms are developed for recognizing various test modes as well as evaluating the correctness of their implementation. While developing the algorithms a multilayer perceptron and a Kohonen network were used as basics. The results of experiments are presented when applying these algorithms for real testing process.