Abstract:
Nondestructive testing (NDT) is a common and reliable method for the detection
of surface and subsurface defects. However, due to the increasing integration
and complexity of industrial components and systems, the problem of
mismatching of size and volume between the existing inspection unit and the
targeted object has limited the applicability of NDT techniques. Especially for
geometrically intricate systems, the deployment of NDT devices for in-situ
inspection has become a major challenge. Addressing the challenge of
inaccessibility and inapplicability, this research proposes a miniaturised active
thermography (MAT) system, featured with a small-size and low-cost thermal
sensor, and a portable optical heat excitation source. A novel spatial resolution
enhancement for a thermogram (SRE4T) system, which includes an infrared (IR)
sensor, an XY movement stage and a super-resolution image enhancement
method, is also proposed to address the low spatial resolution of the miniaturised
sensor without upgrading the sensor. Moreover, dedicated data analysis
approaches to evaluate defects are proposed considering the degraded signal
quality. Compared with existing non-miniaturised inspection systems, the
proposed system is evaluated quantitatively and qualitatively by testing samples
with different materials, structures, and a variety of defects. An accessibility test
is designed and conducted to evaluate the proposed system’s performance to
access geometrically intricate space.
The results show that the proposed system can work effectively for the
degradation assessment of composite laminates, and also has enhanced
accessibility and applicability of deployment for geometrically intricate systems
and narrow space targets. It is observed that the data quality for composite
materials seems to be more reliable and quantifiable than metal due to the
relatively low sample rate of the sensor and the high thermal conductivity of the
metal component. The SRE4T system can significantly improve the spatial
resolution of miniaturised sensors, although it has not been used for active
thermography at the present stage. The current miniaturised IR cameras feature
low spatial resolution and low Signal-to-Noise Ratio, which leads to the poor
performance of most of the current data analysis methods on these sensors. We
propose an effective analytics framework including data processing, image
processing and feature extraction to reduce the influence of noise and enhance
the detectability of damage.
