Using Artificial Neural Networks (ANNs) in Detection Methodologies. First Detection Results Concerning a DMDP Antenna Structure

Abstract The objective of this paper is to present detection results, produced from experiments in a Dual Mode Dual Polarity (DMDP) antenna structure, using a general detection methodology based on Statistics and Artificial Neural Networks (ANNs), in order to detect possible abnormalities within the structure. The antenna is supposed in three states (healthy, minus2bolts, minus1mass). Several experiments, both on healthy and damaged DMDP antenna structure, were carried out in a free configuration space i.e. the structure is suspended with elastic strings, so that it has rigid body suspension frequencies. Frequency Response Functions (FRFs) were recorded and used to detect the abnormalities. A simple identifier for all frequencies is proposed and statistically studied. This identifier is then used by the proposed methodology to compute the diagnosis. The diagnosis performance is 100% for all the treated experiments (in laboratory).