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Description
Visual inspection is traditionally used for the detection of surface cracks in aircraft structures, but its reliability strongly depends on inspector expertise and remains time-consuming. To overcome these limitations, alternative non-destructive testing (NDT) methods are required to ensure reliable crack detection during production and maintenance operations. Among infrared thermography techniques, laser-based flying spot thermography has demonstrated strong potential for detecting open surface cracks in metallic structures. This method consists of scanning a specimen with a localized laser heat source while monitoring the thermal response using an infrared camera. When the heat source approaches a crack, a local thermal discontinuity appears due to the disturbance of heat diffusion, revealing the presence of an open crack.
At ONERA, a multispectral inspection bench has been developed to detect and characterize surface cracks on metallic specimens by combining visible and infrared imaging. Visible (RGB) images are first used to identify potential crack-like features, while flying spot thermography is then applied to discriminate actual cracks from surface-related artefacts such as machining marks or surface stripes. In this context, improving crack detectability while minimizing inspection time remains a key challenge.
This work proposes an optimized flying spot thermographic inspection strategy based on a single-pass, parallel laser scan along the crack direction, which is more compatible with operational maintenance constraints than conventional back-and-forth scanning approaches. While this strategy significantly reduces inspection time, it is more sensitive to surface conditions, particularly surface roughness. To address this limitation, a three-dimensional finite element thermal model based on heat conduction and advection–diffusion equations is developed to simulate laser thermography inspections under varying surface roughness conditions. This numerical model enables the analysis of thermal artefacts induced by surface roughness, which can attenuate or mask the thermal signature of cracks.
Based on the numerical results, a dedicated signal processing strategy is developed to mitigate roughness-induced structural noise, particularly when high-pass filtering is applied, which tends to amplify surface-related artefacts alongside crack signatures. The proposed processing approach is first validated on simulated data and subsequently applied to experimental measurements.
Following the numerical study, a multispectral experimental campaign is conducted on metallic tensile specimens exhibiting different surface roughness levels. Two optical configurations are used: a standard 25 mm objective and a high-magnification optical microscope providing a spatial resolution down to 15 µm. While the highest spatial resolution enables the detection of very narrow cracks with widths below 10 µm, it also significantly amplifies surface-structure noise. The combined numerical and experimental results demonstrate the relevance of the proposed multi-scale inspection and processing strategy for reliable crack detection and provide practical guidelines for optimizing flying spot thermographic inspection parameters in aerospace maintenance applications.
