Infrared thermography analysis with a low-cost camera in plaster sculptures of museum collections

Infrared thermography (IRT) is a non-destructive and non-invasive technique that provides the possibility to investigate the surface of sculptures for the detection of subsurface features and anomalies such as delamination, layer structure, fillings, and defects. IRT has been widely used in buildings and large structures, as well as in works of art such as bronze sculptures and paintings. This article describes the application of active infrared thermography, using a portable low-cost IRT camera, in the examination of plaster sculptures, a material where it has not yet been applied to. In particular, it was used in two plaster sculptures by 19th-century Portuguese artist Soares dos Reis, within a wider project (GEO-SR) aimed at the study of his work. The results indicate that thermography is a suitable technique with a great potential to detect alterations under the surface of plaster, revealing a new look into its manufacturing and conservation.

A Method of Defect Depth Recognition in Active Infrared Thermography Based on GRU Networks

Active infrared thermography (AIRT) is a significant defect detection and evaluation method in the field of non-destructive testing, on account of the fact that it promptly provides visual information and that the results could be used for quantitative research of defects. At present, the quantitative evaluation of defects is an urgent problem to be solved in this field. In this work, a defect depth recognition method based on gated recurrent unit (GRU) networks is proposed to solve the problem of insufficient accuracy in defect depth recognition. AIRT is applied to obtain the raw thermal sequences of the surface temperature field distribution of the defect specimen. Before training the GRU model, principal component analysis (PCA) is used to reduce the dimension and to eliminate the correlation of the raw datasets. Then, the GRU model is employed to automatically recognize the depth of the defect. The defect depth recognition performance of the proposed method is evaluated through an experiment on polymethyl methacrylate (PMMA) with flat bottom holes. The results indicate that the PCA-processed datasets outperform the raw temperature datasets in model learning when assessing defect depth characteristics. A comparison with the BP network shows that the proposed method has better performance in defect depth recognition.

NDT of Composites Based on Active Infrared Thermography and Ultrasound Testing

Composite materials, such as glass and carbon reinforced ones, are characterized by inhomogeneous structure that requires non destructive testing based on uncommon evaluation methods. The presented approach is based on the active infrared thermography, supported by the A-scan ultrasound testing. The heat wave propagation induced by halogen or xenon bulbs, due to the differences in thermal conductivity, reveals material structure and anomalies. In our previous work we have developed several signal processing and depth evaluation methods, but the real engineering approach requires additional approval testing methods such as the A-scan ultrasound is. The A-scan ultrasound, based on the low frequency probe, enables approval of anomalies located by infrared thermography. The active infrared thermography, as a full field method, enables evaluation of the whole scanned area. The A-scan, as a point-wise method, does not provide the image of whole area of interest. By combining these two methods, robust and reliable approach to analysis of composite structure is enabled.

An investigation on the suitability of modern nondestructive testing methods for the inspection of specimens manufactured by laser powder bed fusion

Laser powder bed fusion (L-PBF) is increasingly used to fabricate functional parts used in safety-relevant applications. To ensure that the sophisticated part specifications are achieved, 100% quality inspections are performed subsequent to the buildup process. However, knowledge about the detectability of defects in L-PBF parts using NDT methods is limited. This paper analyzes the suitability of NDT techniques in an ex situ environment, in particular active infrared thermography, neutron grating interferometry (nGI), X-ray computed tomography, and ultrasonic testing for the examination of L-PBF parts made from Inconel 718. Based on a test specimen with artificially inserted defects with varying dimensions and depths, these NDT techniques were compared in terms of their attainable resolution and thus defect detection capability. The empirical studies revealed that nGI shows the highest resolution capability. It was possible to detect defects with a diameter of 100–200 m at a depth of 60–80 $${\upmu } \hbox {m}$$ μ m . The results are discussed with regard to their relevance for the examination of L-PBF parts and thus not only contribute to a better understanding of the potential of the NDT techniques in comparison but also assist stakeholders in additive manufacturing in evaluating the suitability of the NDT techniques investigated.

Evaluation and Selection of Video Stabilization Techniques for UAV-Based Active Infrared Thermography Application

Unmanned Aerial Vehicles (UAVs) that can fly around an aircraft carrying several sensors, e.g., thermal and optical cameras, to inspect the parts of interest without removing them can have significant impact in reducing inspection time and cost. One of the main challenges in the UAV based active InfraRed Thermography (IRT) inspection is the UAV’s unexpected motions. Since active thermography is mainly concerned with the analysis of thermal sequences, unexpected motions can disturb the thermal profiling and cause data misinterpretation especially for providing an automated process pipeline of such inspections. Additionally, in the scenarios where post-analysis is intended to be applied by an inspector, the UAV’s unexpected motions can increase the risk of human error, data misinterpretation, and incorrect characterization of possible defects. Therefore, post-processing is required to minimize/eliminate such undesired motions using digital video stabilization techniques. There are number of video stabilization algorithms that are readily available; however, selecting the best suited one is also challenging. Therefore, this paper evaluates video stabilization algorithms to minimize/mitigate undesired UAV motion and proposes a simple method to find the best suited stabilization algorithm as a fundamental first step towards a fully operational UAV-IRT inspection system.