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.…
Autor*innen: | Tim KleweORCiD, Christoph StrangfeldORCiD, Tobias Ritzer, Sabine KruschwitzORCiD |
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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: | Chemie und Prozesstechnik |
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: | 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 |