A Soft Computing Approach for Sensory Analysis with Thermographic Techniques for Structural Monitoring of Bronze Statues

The proposed research work is based on the fundamental principle of ensuring the protection of the World Heritage so that it can be passed on to future generations. The contribution provided is responsible for non-destructive monitoring and the implementation of an algorithm able to classify and locate a possible defect present on the investigated object. The monitoring is carried out using infrared thermography, which is an important non-destructive technique often used in the analysis of cultural heritage. Because of its ability to show underground characteristics in artefacts, this technique has been used to investigate various types of artefacts consisting of different structures and materials. After the thermographic examination, an algorithm is implemented that better classifies and identifies the defects present on a bronze sculpture exposed to both atmospheric phenomena and its proximity to the sea. The results obtained certified the importance for non-destructive techniques on cultural heritage. Validating the use of thermography and associated analysis algorithms. The paper proposes a new method of non-destructive surveillance and investigation. In fact, the combination of the thermographic technique with the implementation of a Convolutional Neural Network (CNN) algorithm more easily identifies the presence of imperfections. The results obtained validated the study methodology and confirmed the symbiosis between Non-Destructive Testing (NDT) techniques, Artificial Intelligence (AI), and the importance of monitoring cultural and artistic heritage.