Abstract
This work aims to address the effectiveness and challenges of non-destructive testing (NDT) by active infrared thermography (IRT) for the inspection of aerospace-grade composite samples and seeks to compare uncooled and cooled thermal cameras using the signal-to-noise ratio (SNR) as a performance parameter. It focuses on locating impact damages and optimising the results using several signal processing techniques. The work successfully compares both types of cameras using seven different SNR definitions, to understand if a lower-resolution uncooled IR camera can achieve an acceptable NDT standard. Due to most uncooled cameras being small, lightweight, and cheap, they are more accessible to use on an unmanned aerial vehicle (UAV). The concept of using a UAV for NDT on a composite wing is explored, and the UAV is also tracked using a localisation system to observe the exact movement in millimetres and how it affects the thermal data. It was observed that an NDT UAV can access difficult areas and, therefore, can be suggested for significant reduction of time and cost.
Highlights
Active infrared thermography (IRT) is an infrared-based non-destructive testing (NDT) technique, which is used for a quick analysis of materials, structures, and components
The carbon fibre-reinforced polymer (CFRP) sample 2.2 was subjected to 24 J of impact, whilst sample 3.2 was subjected to 8 J of
The CFRP sample 2.2 was subjected to 24 J of impact, whilst sample 3.2 was subjected to 8 J of impact
Summary
Active infrared thermography (IRT) is an infrared-based non-destructive testing (NDT) technique, which is used for a quick analysis of materials, structures, and components. The method is reliable due to its non-contact, qualitative, and quantitative inspection, regardless of the size and shape of the specimen of interest [1]. IRT evaluates materials without subsequently affecting the mechanical, physical, or chemical properties. The method is subject to interference when the environment is not controlled, or the experiment set-up is not optimal. Challenges such as non-uniform heating, low spatial resolution, and environmental noise cause some difficulties for defect detection and characterisation [2]. Inspections are being used for many applications, but the experimental set-ups differ greatly. The equipment is mounted on robot arms, and unmanned aerial
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