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Nach Auftreten eines Feuchteschadens in Fußbodenaufbauten sind sowohl die zeitnahe Feststellung als auch Eingrenzung betroffener Bereiche von besonderer Bedeutung. So können erforderliche Renovierungsmaßnahmen effizient geplant und mögliche Folgeschäden vermieden werden. Zur messtechnischen Beantwortung dieser Fragestellungen werden bereits seit vielen Jahren Neutronensonden eingesetzt, welche allerdings keine Tiefenzuordnung des schadensträchtigen Flüssigwassers zulassen. Hierzu müssen mit hohem zeitlichem und finanziellem Aufwand zerstörende Sondierungsbohrungen vorgenommen werden, welche zukünftig durch den parallelen Einsatz des Radarverfahrens vermieden werden könnten. In systematischen Laborstudien wurden gängige Feuchteschäden an häufig anzutreffenden Fußbodenaufbauten simuliert und deren Einfluss auf das Messsignal untersucht. Hierbei kamen Zementund Anhydritestriche, sowie die Dämmmaterialen Styropor, Styrodur, Glaswolle und Perlite-Schüttung mit variierenden Schichtdicken zum Einsatz, um die vielfältigen Konfigurationen der Praxis abzubilden. Für den gewonnenen Datensatz konnten geeignete Signalmerkmale extrahiert werden, welche mithilfe multivariater Datenauswertung eine Klassifizierung des vorliegenden Schadenfalls zulassen. Zum Ende des Forschungsvorhabens steht besonders die Anwendbarkeit der entwickelten Methoden für die Praxis im Fokus. Hierzu wurden Messungen an realen Schadensfällen durchgeführt und deren Ergebnisse mit den Laboruntersuchungen verglichen. Hierbei stellten sich variierende Schichtdicken, sowie vorkommende Fußbodenheizungen und Armierungsgitter als mögliche Fehlerquellen für eine vollständig automatisierte Auswertung heraus.
In 2019, 3.1 billion Euro of damage was caused by piped water, accounting for the largest share (53%) of building insurance claims in Germany. In the event of damage, the accurate determination and localization of water ingress is essential to plan for and perform efficient renovations. Neutron probes are already applied successfully on building floors to localize the source of damage and other affected areas. However, additional information about the depth of moisture penetration can only be obtained by the destructive extraction of drilling cores, which is a time- and cost-intensive procedure. With its high sensitivity to water and fast measurement procedure, Ground Penetrating Radar (GPR) can serve as a suitable extension to the neutron probe, enabling more precise characterization of common forms of moisture damage.
In this research project, we study the influence of common types of moisture damage in differing floor constructions using GPR and a neutron probe. A measurement setup with interchangeable layers is used to vary the screed material (cement or anhydrite) and insulation material (Styrofoam, Styrodur, glass wool, perlite), as well as the respective layer thickness. Every configuration is measured for the following main cases: 1) dry state; 2) with a damaged insulation layer and 3) a damaged screed layer.
The evaluation is focused on the extraction of distinctive signal features for GPR, which can be used to classify the underlying case of damage. Furthermore, possible combinations of these features are investigated using multivariate data analysis and machine learning in order to evaluate the influence of different floor constructions.
To validate the developed methods, practical measurements on real damage cases in Germany are carried out and compared to reference data obtained from drilling cores.
To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and costintensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases.
When applying Ground Penetrating Radar (GPR) to assess the moisture content of building materials, different medium properties, dimensions, interfaces and other unknown influences may require specific strategies to achieve useful results. Hence, we present an overview of the various approaches to carry out moisture measurements with GPR in civil engineering (CE). We especially focus on the applied Signal features such as time, amplitude and frequency features and discuss their limitations. Since the majority of publications rely on one single feature when applying moisture measurements, we also hope to encourage the consideration of approaches that combine different signal features for further developments.
Subfloors are layered structures, consisting largely of porous building materials, such as screed. They are often suffering damage from tap water leakage, which is a typical problem in buildings, and which has largely contributed to repair costs of almost 3 billion Euro in 2018 alone in Germany. In this context, especially mould plays a role, which is both destroying the structure and posing severe health risks.
To determine the damaging effects of moisture, it is necessary to know the respective processes occurring in building materials, especially to quantify the amount of moisture and its progress in the material. In this study, humidity sensors are used to derive the material moisture experimentally.
Capacitive sensors recording the relative humidity are embedded into the screed and in the insulation materials such as expanded polystyrene, extruded polystyrene, perlite and glass wool. For the application in screed, the sensors need to be shielded against the aggressive alkaline materials. To ensure an appropriate exchange with the environment, a permeable membrane is requested. Different membrane materials have been investigated regarding their robustness and their permeability.
In the first experimental setup, two humidity sensor arrays with seven individual sensors are embedded in homogeneous screed samples. The measured corresponding relative humidity of the screed is converted to the material moisture based on the approach of Hillerborg. In a second experimental setup, a layered structure of a complete subfloor is built in a box of 0.8 m times 0.8 m. The humidity sensors are positioned in the different insulation materials of various thicknesses. By adding water, leakage damage is simulated and its progress and effect is investigated experimentally.
The investigations point at the question if the observed moisture is able to generate damage such as mould. The moisture and corresponding humidity values are discussed. It will be shown that this low-cost hygrometric approach can be used easily for moisture monitoring of screed and insulation materials as well