by Alberto D'AMORE and Luigi GRASSIA*
Structural Health Monitoring (SHM) is a technology aimed at monitoring the soundness of structures. Applications for aircraft structure are largely investigated. The goal oh SHM is to utilize the information acquired during the monitoring to save maintenance costs, improve flight safety, and design lighter structures.
There are different issues investigated by SHM research, like load monitoring and impact detection. Damage detection is the most largely investigated issue, i.e. developing a system that utilizes sensors to detect the structure's damages. The damage detection can be performed utilizing dynamic sensors generating waves through the structures. Defects deviate and reflect the waves so that damage can be identified. On the other hand, damage detection based on static sensors utilizes sensors measuring the strain under loads, like strain gages or fiber optics. In this case, damage is detected by the strain modification concerning the pristine structure.
The University of Campania cooperates with Leonardo Aircraft in the CERVIA National research program on developing and validating software aimed to diagnose flaws (e.g. damages, debonding, delaminations) based on measurement of the strain field.
First, the strain fields under load in pristine and damaged condition are compared; damages are identified by evaluating the change in the strain field. This work has investigated two different algorithms for damage detection, patented by Leonardo Aircraft; one is based on a reverse finite element model (f.e.m.) and the other on neural network.
The algorithm concepts are described in the following...
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*University of Campania “Luigi Vanvitelli”, Department of Engineering
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02 August 2022
