Flaw Detection by SHM with Static Sensors Approach: State of the Art and Perspectives

Abstract

AbstractStructural health monitoring (SHM) is a technology aimed to monitor the soundness of the structures. Applications for aircraft structures are largely investigated. The goal is to utilize the information acquired during the monitoring to save maintenance costs, improve flight safety, and design lighter structures. Different issues, like load monitoring and impact detection, are investigated by SHM research. The most largely investigated issue is damage detection, i.e., developing a system that utilizes sensors to detect the damage in the structure. Damage detection can be performed with two sensors: dynamic and static. Dynamic sensors work by transmission of waves through the structures. Defects are identified by deviation and reflection of the waves by damages. The SHM approach described in this work is based on static sensors, like strain gages or fiber optics. The strain fields under load in pristine and damaged conditions are compared; the evaluation of the change in the strain field identifies damages. Two different algorithms for damage detection have been developed and patented in Leonardo Aircraft and are described in this work; they are based on the reverse finite element model (FEM) and neural network. The issues related to the strain field measurement are also briefly described.