ISBN number 978-1-925627-66-4
An Innovative High-Fidelity Approach to Structural
Health Monitoring
Oleg Levinski
1
, Wim Verhagen
2
, Haytham Fayek
2
, Michael J. Scott
2
, Pier Marzocca
2
1
Defence Science and Technology Group, 506 Lorimer St, Fishermans Bend, VIC 3207,
Australia
2
RMIT University, GPO Box 2476, Melbourne, Victoria, 3001, Australia
Email: Oleg.Levinski@defence.gov.au
ABSTRACT
Structural health management for Defence air platforms is traditionally driven by scheduled
inspection intervals and pre-emptive maintenance based on interpretation of structural
certification test results or reactive based on unique or unexpected fleet in-service incidents.
However, in the current environment of budget constraints and shrinking resources, a major
shift towards actionable and proactive condition-based maintenance is required to improve
aircraft availability and reduce fleet management and sustainment costs.
Significant improvements in structural life prediction and management can be achieved by
implementing an integrated approach to aircraft operation and sustainment. Numerous
uncertainty factors and safety margins used in the fatigue life calculation can be minimised
or even eliminated by integrating a high-fidelity numerical model of the aircraft with a
‘smart’ health monitoring system and a comprehensive historical database for each
individual aircraft covering its operation, maintenance, upgrades and repairs. Detecting and
tracking the global airframe health as well as local structural anomalies caused by fatigue
and wear is a crucial component towards the development of a smart structural diagnostics
capability to support the sustainment of the current and future aerospace platforms.
This paper describes the progress of a collaborative effort between DSTG and RMIT
University in developing a high-fidelity approach to structural health monitoring and
individual aircraft tracking inspired by the Aircraft Digital Twin concept. Operational Load
Analysis and Asset Diagnostics (aka OPERAND) is a multi-physics analysis suite for
structural health monitoring based on integrating current state-of-the-art software
techniques, data-driven methods, and model-based approaches. This innovative structural
diagnostics and prognostics framework has the potential to considerably improve aircraft
fleet airworthiness management, provide substantial savings to aircraft operators and
optimise aircraft availability for enhanced operational effectiveness. It aims to enable
proactive condition-based aircraft maintenance through high-fidelity airframe fatigue
tracking by significantly improving airframe load and stress predictions.
Keywords: data analytics, digital twin, individual aircraft tracking, OPERAND, structural
dynamics.
