Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/11957
Authors: Fais, Silvana* 
Casula, Giuseppe* 
Cuccuru, Francesco* 
Ligas, Paola* 
Bianchi, Maria Giovanna* 
Title: An innovative methodology for the non-destructive diagnosis of architectural elements of ancient historical buildings
Issue Date: 12-Mar-2018
Series/Report no.: /8 (2018)
DOI: 10.1038/s41598-018-22601-5
URI: http://hdl.handle.net/2122/11957
Keywords: Non-invasive methodology
Stone building materials
Diagnosis
3D Terrestrial Laser Scanner
Non-invasive multi-techniques acoustic data
Microscopy
Subject ClassificationMethodology for the non-destructive diagnosis of architectural elements
Cultural Heritage
Abstract: In the following we present a new non-invasive methodology aimed at the diagnosis of stone building materials used in historical buildings and architectural elements. This methodology consists of the integrated sequential application of in situ proximal sensing methodologies such as the 3D Terrestrial Laser Scanner for the 3D modelling of investigated objects together with laboratory and in situ non-invasive multi-techniques acoustic data, preceded by an accurate petrographical study of the investigated stone materials by optical and scanning electron microscopy. The increasing necessity to integrate different types of techniques in the safeguard of the Cultural Heritage is the result of the following two interdependent factors: 1) The diagnostic process on the building stone materials of monuments is increasingly focused on difficult targets in critical situations. In these cases, the diagnosis using only one type of non-invasive technique may not be sufficient to investigate the conservation status of the stone materials of the superficial and inner parts of the studied structures 2) Recent technological and scientific developments in the field of non-invasive diagnostic techniques for different types of materials favors and supports the acquisition, processing and interpretation of huge multidisciplinary datasets.
Appears in Collections:Papers Published / Papers in press

Files in This Item:
File Description SizeFormat 
s41598-018-22601-5.pdfArticle pdf reprint2.18 MBAdobe PDFView/Open
Show full item record

Page view(s)

12
checked on Oct 20, 2018

Download(s)

3
checked on Oct 20, 2018

Google ScholarTM

Check

Altmetric