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Predicting the Corrosion of Aircraft Using In-field Environmental Sensor Data

Paper Number: 83
Author/s: A Sudholz1, S Jacob2, J Talevski1, C Loader1
Organisation: Defence Science and Technology Group1, Melbourne, Australia, BAE Systems Australia2, Melbourne, Australia


The Defence Science and Technology Group (DST) and BAE Systems Australia (BAE) are developing corrosion prediction models to assist maintainers of military aircraft. These models are embodied in an engineering tool known as a Corrosion Prognostic Health Management (CPHM) system. The aim of a CPHM system is to enable condition-based maintenance (CBM) where maintainers can perform targeted inspections, thereby limiting unnecessary and time-consuming maintenance. Key to building maintainer confidence in CPHM systems is the validation of modelling outputs with in-field environmental data.

The current programme has established a series of ground-based stations (GBS) to record local environmental data and monitor corrosion of typical aircraft aluminium alloys. Each GBS comprises environmental sensors and witness plates of a selection of typical aircraft aluminium alloys, and are installed at six sites around Australia representing a broad range of environmental conditions relevant to the Royal Australian Air Force. Corrosion modelling predictions using these environmental inputs can therefore be compared to the corrosion experienced by each aluminium alloy. Such in-field data will assist in validating the predictive capability of current corrosion models and building end-user confidence for use in CBM practices. This paper will detail results from the first 12 months of the GBS programme and discuss the application of in-field data to CPHM systems.