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. (C) 2022 Elsevier B.V. All rights reserved.
Non-destructive techniques (NDT) for the diagnosis of heritage buildings: Traditional procedures and futures perspectives
Lucchi, Elena;
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. (C) 2022 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.