Statistical Based Features Vector for Skin-stringer Debonding Detection

Abstract

In composite aeronautical structures at the stiffener terminations, the carried loads are transferred to the skin, making vital the design of the run-out region. Hence, improved structural health monitoring methods are required. The observations showed that failure initiates in the flange close to the tip in many operational cases, causing an almost full disconnection from the skin. This paper presents a simple methodology for skin-stringer de-bonding detection by using distributed fibre optic sensors and first order statistics. The proposed technique is based on the deviation comparison between a baseline set of measurements (irrespectively of the healthy state) and the current structural response. The assessed datasets are then processed in order to provide normalbased statistical features, an appropriate threshold limit and a damage index for each sensor. The algorithm points then out the positions where the possibility of the existence of a damage is maximum.