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 universal phenomenon which affects almost all the metals, resulting in their degradation. Timely and accurate detection and monitoring of corrosion is essential for maintaining the structural integrity and preventing catastrophic failure of the structures. In the aircraft industry, the selection of specific metallic materials is mainly based on the properties of the metals like weight, heat resistance, stiffness, strength, electrical properties, etc., rather than their resistance to corrosion. The cost of corrosion in aircraft is huge not only from the economic point of view, but also in terms of human life and safety. Detecting corrosion at the right time is of utmost importance in the battle against corrosion. There are many non-intrusive and indirect testing methods to identify corrosion in the aircraft structure. Herein, we discuss various techniques currently being used for detection of corrosion in aircraft, including the conventional and non-conventional non-destructive inspection (NDI) methods. These NDI techniques are based on visual and other field detection approaches but are less effective in inspecting corrosion in hidden areas. A new trend in this regard is the development of real-time corrosion sensors that support non-destructive testing and signal the onset of the corrosion in aircraft structures. Artificial Intelligence (AI) techniques are gaining attention in corrosion detection nowadays. This review discusses various types of offline NDI methods, real-time corrosion sensors and AI techniques with their associated challenges in corrosion detection. We have also deliberated on the possibility of integration of these methods to develop a digital twin of the physical condition of the aircraft to improve accuracy and effectiveness of corrosion detection.