Nondestructive determination of moisture damage in layered building floors

  • In this ongoing research project, we study the influence of moisture damage on Ground Penetrating Radar (GPR) in different floor constructions. For this purpose, a measurement setup with interchangeable layers is developed to vary the screed material (cement or anhydrite) and insulation material (glass wool, perlite, expanded and extruded polystyrene), as well as the respective layer thickness. The evaluation of the 2 GHz common-offset radar measurements is focused on the extraction of distinctive signal features that can be used to classify the underlying case of damage without any further information about the hidden materials or layer thicknesses. In the collected dataset, we analyze the horizontal distribution of A-scan features in corresponding B-scans to detect water in the insulation layer. Furthermore, possible combinations of these features are investigated with the use of multivariate data analysis and machine learning (logistic regression) in order to evaluate the mutualIn this ongoing research project, we study the influence of moisture damage on Ground Penetrating Radar (GPR) in different floor constructions. For this purpose, a measurement setup with interchangeable layers is developed to vary the screed material (cement or anhydrite) and insulation material (glass wool, perlite, expanded and extruded polystyrene), as well as the respective layer thickness. The evaluation of the 2 GHz common-offset radar measurements is focused on the extraction of distinctive signal features that can be used to classify the underlying case of damage without any further information about the hidden materials or layer thicknesses. In the collected dataset, we analyze the horizontal distribution of A-scan features in corresponding B-scans to detect water in the insulation layer. Furthermore, possible combinations of these features are investigated with the use of multivariate data analysis and machine learning (logistic regression) in order to evaluate the mutual dependencies. In this study, the combination of an amplitude- and frequency-based feature achieved an accuracy of 93.2 % and performed best to detect a damage in floor insulations.zeige mehrzeige weniger

Volltext Dateien herunterladen

  • gpr2020-045.1.pdf
    eng

Metadaten exportieren

Weitere Dienste

Teilen auf Twitter Suche bei Google Scholar
Metadaten
Autoren/innen:Tim Klewe, Christoph Strangfeld, Tobias Ritzer, Sabine Kruschwitz
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):18th International Conference on Ground Penetrating Radar
Jahr der Erstveröffentlichung:2020
Organisationseinheit der BAM:8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.0 Abteilungsleitung und andere
Herausgeber (Institution):Society of Exploration Geophysicists
Erste Seite:164
Letzte Seite:167
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Feuchte; Radar
Building floors; Moisture
Themenfelder/Aktivitätsfelder der BAM:Analytical Sciences
Analytical Sciences / Zerstörungsfreie Prüfung und Spektroskopie
Veranstaltung:18th International Conference on Ground Penetrating Radar
Veranstaltungsort:Meeting was canceled
Beginndatum der Veranstaltung:14.07.2020
Enddatum der Veranstaltung:19.07.2020
DOI:https://doi.org/10.1190/gpr2020-045.1
ISSN:2159-6832
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:18.11.2020
Referierte Publikation:Nein