A fatigue monitoring system is being developed by EADS-CASA MTAD to be installed in two of its products: C-295 and A330-MRTT. The main requirements of the system are high reliability, high accuracy, minimum impact on the manufacturing schedule, minimum maintenance requirements and the capability to be easily extended in the future to other members of the family of products. Among the several possible configurations, a parametric concept (i.e, flight parameters are used to calculate strains) has been selected. While the version of the system installed in the C-295 remains as a full parametric system, another version -installed in the A330-MRTT- uses real data to generate the transfer functions between flight parameters and strains, with the aim of improving the accuracy of the parametric approach. The configuration of the latter system consists of a limited number of aircraft ('reference aircraft') of the fleet equipped with strain gauges, so the transfer functions between flight parameters and strains can be calculated -using Artificial Neural Networks (ANN)-, and applied to the other aircraft of the fleet ('standard aircraft'), which are equipped only with an onboard recorder to collect and store the flight parameters. The accuracy enabled by this design is similar to strain-based systems, retaining also the advantages of a parametric concept.
展开▼
