The restoration of Cultural Heritage wouldn't be possible without the financial resources to meet Cultural Heritage needs. A smart procedure to reduce in time and funds spent for restoration is linked to a planning of the diagnostic interventions acting to predict incipient defects undetectable to the naked eye. One of the main methods to fulfil this task is infrared thermography (IRT). The aim of this study is to examine the efficiency of various mathematical techniques in thermographic data processing, with respect to the thermal excitation procedure and the type of artificial defect in a panel painting sample. One of the thermographic analyses performed was based on the pixelwise algorithm for time-derivative of temperature (PATDT). With this algorithm, Newton's cooling law was applied pixel per pixel, resulting in the computation of the cooling rate of each pixel. In addition, the capabilities of the multivariate statistical analysis methods, independent component thermography (ICT) and sparse principal component thermography (SPCT) were also investigated. In the present case study, the authors inspected possible pathologies resembling splitting areas (i.e., detachments) in real panel paintings, with the consequent change in the heat transfer coefficient and the heat capacity. The feasibility of the different analysis methods was illustrated with the application results.

Active thermography testing and data analysis for the state of conservation of panel paintings

Stefano Sfarra
;
Dario Ambrosini
2018

Abstract

The restoration of Cultural Heritage wouldn't be possible without the financial resources to meet Cultural Heritage needs. A smart procedure to reduce in time and funds spent for restoration is linked to a planning of the diagnostic interventions acting to predict incipient defects undetectable to the naked eye. One of the main methods to fulfil this task is infrared thermography (IRT). The aim of this study is to examine the efficiency of various mathematical techniques in thermographic data processing, with respect to the thermal excitation procedure and the type of artificial defect in a panel painting sample. One of the thermographic analyses performed was based on the pixelwise algorithm for time-derivative of temperature (PATDT). With this algorithm, Newton's cooling law was applied pixel per pixel, resulting in the computation of the cooling rate of each pixel. In addition, the capabilities of the multivariate statistical analysis methods, independent component thermography (ICT) and sparse principal component thermography (SPCT) were also investigated. In the present case study, the authors inspected possible pathologies resembling splitting areas (i.e., detachments) in real panel paintings, with the consequent change in the heat transfer coefficient and the heat capacity. The feasibility of the different analysis methods was illustrated with the application results.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/122461
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