A Comprehensive Review on Corrosion Detection Methods for Aircraft: Moving from Offline Methodologies to Real-Time Monitoring Combined with Digital Twin Technology

Abstract

Corrosion is a pervasive issue that limits the service life of an aircraft and leads to their degradation. Timely and accurate detection and monitoring of corrosion are crucial for maintaining structural integrity and preventing catastrophic failures. This review explores various techniques for corrosion detection, including conventional and innovative Non-Destructive Inspection (NDI) methods. Another promising trend is the development of real-time corrosion sensors that enhance non-destructive testing by providing early warnings of corrosion in aircraft structures. Additionally, advancements in Artificial Intelligence (AI), Machine Learning (ML), and the concept of digital twins represent cutting-edge technologies in the realm of corrosion monitoring. This review offers a comprehensive and up-to-date overview of these approaches, highlighting the challenges and prospects of these methods. We also propose the innovative potential of integrating diverse approaches to construct a digital twin, which aims to characterize the behaviour of physical entities by leveraging a virtual replica in real time.