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Self-sensing Curved composite panel under Operational load: methodology Platform for prediction of damage Event

Project

SCOPE - Self-sensing Curved composite panel under Operational load: methodology Platform for prediction of damage Event


Funding origin:
European
European Union
STRIA Roadmaps:
Vehicle design and manufacturing (VDM)
Vehicle design and manufacturing
Transport mode:
Airborne
Airbone
Transport sectors:
Passenger transport
Passenger transport
Freight transport
Freight transport
Duration:
Start date: 01/05/2013,
End date: 01/05/2015

Status: Finished
Funding details:
Total cost:
€400 000
EU Contribution:
€300 000

Overview

Objectives:

This proposal developed SHM methodology platform, as outlined in JTI call JTI-CS-2012-3-GRA-01-051, for impact and damage detection in curved fuselage panels under real load conditions. The platform was able to detect BIVID and VID on sensorised fuselage panels. Different SHM methodologies were established based on piezoelectric transducers and Fibre Optic sensors. To allow for numerical simulation of impact events and wave propagation, non-linear Finite Element models were developed using SMART Elements to run in parallel on High Performance Computing units. Moreover, advanced Message Passing Interfaces were utilised to cope with large size of data handling.

The SCOPE platform had the following features:

  • SMART computational methodologies to accurately simulate sensing and actuating in real-time under real dynamic load conditions;
  • Passive sensing methodologies by generating meta-models based on sensor signals to detect and identify various impact events which are likely to occur during service life of aircraft;
  • Active sensing techniques based on Lamb wave and Electromechanical Impedance to detect and characterise damage;
  • An optimisation algorithm resulting in optimum sensor layout (i.e. number and location) using sensor data from SMART FE simulations;
  • A robust and reliable sensor system by utilising “SMART sensor” models with self-diagnostic properties to reduce the Probability of False Alarm;
  • Full non-linear impact analysis incorporating damage models for advanced composite to identify damage development and propagation;
  • Statistical analysis of the developed methodologies to result in a robust and reliable SHM platform;
  • To set test procedures for collecting SHM data;
  • Multiple impact data for impact identification;
  • Validation and calibration of the developed methodologies.

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