Low Thermal Conductivity Materials and Very Low Heat Power: A Demanding Challenge in the Detection of Flaws in Multi-Layer Wooden Cultural Heritage Objects Solved by Pulse-Compression Thermography Technique

IR Reflectography, Pulse-Compression Thermography, MA-XRF, and Radiography: A Full-Thickness Study of a 16th-Century Panel Painting Copy of Raphael

The potential of any multi-analytical and non-invasive approach to the study of cultural heritage, both for conservation and scientific investigation purposes, is gaining increasing interest, and it was tested in this paper, focusing on the panel painting Madonna della Tenda (Musei Reali, Turin), identified as a 16th-century copy of the painting by Raffaello Sanzio. As a part of a broader diagnostic campaign carried out at the Centro Conservazione e Restauro, La Venaria Reale in Turin, Italy, the potential of the combination of X-ray radiography, pulse-compression thermography, macro X-ray fluorescence, and IR reflectography was tested to investigate the wooden support and all the preparatory phases for the realization of the painting. The results of the optical microscopy and SEM/EDS analyses on a multi-layered micro-sample were used for a precise comparison, integration, and/or confirmation of what was suggested by the non-invasive techniques. Particularly, the radiographic and thermographic techniques allowed for an in-depth study of a hole, interestingly present on the panel’s back surface, detecting the trajectory of the wood grain and confirming the presence of an old wood knot, as well as of a tau-shaped element—potentially a cracked and unfilled area of the wooden support—near the hollow. The combination of radiography, macro X-ray fluorescence, Near Infrared (NIR), and Short Wave Infrared (SWIR) reflectography allowed for an inspection of the ground layer, imprimitura, engravings, and underdrawing, not only revealing interesting technical-executive aspects of the artwork realization, but also highlighting the advantages of an integrated reading of data obtained from the different analytical techniques.

Detection and Identification of Defects in 3D-Printed Dielectric Structures via Thermographic Inspection and Deep Neural Networks

In this paper, we propose a new method based on active infrared thermography (IRT) applied to assess the state of 3D-printed structures. The technique utilized here-active IRT-assumes the use of an external energy source to heat the tested material and to create a temperature difference between undamaged and defective areas, and this temperature difference is possible to observe with a thermal imaging camera. In the case of materials with a low value of thermal conductivity, such as the acrylonitrile butadiene styrene (ABS) plastic printout tested in the presented work, the obtained temperature differences are hardly measurable. Hence, the proposed novel IRT method is complemented by a dedicated algorithm for signal analysis and a multi-label classifier based on a deep convolutional neural network (DCNN). For the initial testing of the presented methodology, a 3D printout made in the shape of a cuboid was prepared. One type of defect was tested-surface breaking holes of various depths and diameters that were produced artificially by inclusion in the printout. As a result of examining the sample via the IRT method, a sequence of thermograms was obtained, which enabled the examination of the temporal representation of temperature variation over the examined region of the material. First, the obtained signals were analysed using a new algorithm to enhance the contrast between the background and the defect areas in the 3D print. In the second step, the DCNN was utilised to identify the chosen defect parameters. The experimental results show the high effectiveness of the proposed hybrid signal analysis method to visualise the inner structure of the sample and to determine the defect and size, including the depth and diameter.

Surface and Interface Investigation of a 15th Century Wall Painting Using Multispectral Imaging and Pulse-Compression Infrared Thermography

Before starting the restoration of an artwork, good practice involves the evaluation of the item healthiness possibly carried out through non-invasive techniques. In the specific case of painting inspection, hyper- and multi- spectral techniques are commonly used to analyze the outer layers (varnish, pictorial, and drawing), while X-ray, tomography, and many others can be employed to investigate its inner structure. Although highly desirable, a single technique providing all the information about a painting is still not available. Thus, it is of great interest to define the analysis’ protocols that could optimally exploit the complementarities of a minimal set of techniques. To this aim, the present paper shows the combined use of the hypercolorimetric multispectral imaging and pulse-compression thermography on a 15th century wall painting attributed to the Italian artist Antonio del Massaro, also known as Pastura, representing the Madonna with the Child and the Saints Jerome and Francis. The capabilities and the complementarities of the two techniques, whose information can also be fused through post-processing, are illustrated in detail in this paper. In addition, a false-colour imaging approach is proposed to improve the readability and analysis of the thermography results.