It is estimated that EU cultural heritage (CH) buildings represent 30% of the total existing stock. Nevertheless, all actions in terms of refurbishment need a deep knowledge based on the diagnosis of the built quality. For this reason, the paper aims to provide a comprehensive review about the applicability of non-destructive techniques (NDT) and advanced modelling technologies for the diagnosis of heritage buildings. Considering a time span of two decades (2001-2021), a bibliometric analysis was performed, using data statistics and science mapping. Subsequently, the most relevant studies on this topic were evaluated for each technique. The main findings revealed that: (i) most of studies were conducted on Southern European countries; (ii) 36% of publications were journal papers and only 2% corresponded to reviews; (iii) “photogrammetry” and “laser applications” were identified as consolidated techniques for historic preservation, but they are only linked with HBIM and deep learning; (iv) a significant gap on quantitative NDT was detected and consequently, future researches should be performed to propose a common diagnosis protocol; (v) artificial neural networks have several barriers (i.e. data privacy, network security and quality of datasets). Hence, a holistic approach should be adopted by the European countries.

Non-Destructive Techniques (NDT) for the diagnosis of heritage buildings: traditional procedures and futures perspectives

Nardi, Iole
2022-01-01

Abstract

It is estimated that EU cultural heritage (CH) buildings represent 30% of the total existing stock. Nevertheless, all actions in terms of refurbishment need a deep knowledge based on the diagnosis of the built quality. For this reason, the paper aims to provide a comprehensive review about the applicability of non-destructive techniques (NDT) and advanced modelling technologies for the diagnosis of heritage buildings. Considering a time span of two decades (2001-2021), a bibliometric analysis was performed, using data statistics and science mapping. Subsequently, the most relevant studies on this topic were evaluated for each technique. The main findings revealed that: (i) most of studies were conducted on Southern European countries; (ii) 36% of publications were journal papers and only 2% corresponded to reviews; (iii) “photogrammetry” and “laser applications” were identified as consolidated techniques for historic preservation, but they are only linked with HBIM and deep learning; (iv) a significant gap on quantitative NDT was detected and consequently, future researches should be performed to propose a common diagnosis protocol; (v) artificial neural networks have several barriers (i.e. data privacy, network security and quality of datasets). Hence, a holistic approach should be adopted by the European countries.
2022
Photogrammetry
Laser Scanning
Infrared thermography (IRT)
Heat flux meter (HFM)
Heritage Building Information Modelling (HBIM)
Non-destructive techniques (NDT)
Heritage buildings
Airtightness measurements
Artificial Neural Networks (ANN)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/62301
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