TY - JOUR A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Kruschwitz, Sabine T1 - Review of moisture measurements in civil engineering with ground penetrating radar – Applied methods and signal features JF - Construction and Building Materials N2 - 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. KW - Ground Penetrating Radar KW - Moisture KW - Civil engineering KW - Signal features PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-520684 DO - https://doi.org/10.1016/j.conbuildmat.2021.122250 VL - 278 SP - 122250 PB - Elsevier Ltd. AN - OPUS4-52068 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - Nondestructive determination of moisture damage in layered building floors T2 - 18th International Conference on Ground Penetrating Radar N2 - 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 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. T2 - 18th International Conference on Ground Penetrating Radar CY - Meeting was canceled DA - 14.07.2020 KW - Radar KW - Feuchte KW - Moisture KW - Building floors PY - 2020 DO - https://doi.org/10.1190/gpr2020-045.1 SN - 2159-6832 SP - 164 EP - 167 AN - OPUS4-51575 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - GPR Dataset of Moisture Measurements on Building Floors in Laboratory and On-Site N2 - Related work Laboratory Study: Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors https://doi.org/10.3390/app11198820 On-Site Study: TBA Doctoral Thesis: Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar https://doi.org/10.14279/depositonce-19306 Measurement Parameters The GPR measurements were carried out with the SIR 20 from GSSI and a 2 GHz antenna pair (bandwidth 1 GHz to 3 GHz) in common-offset configuration. Each B-Scan consists of N A-Scans, each including 512 samples of a 11 ns time window. Survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan No Gains were applied. Folder Description: Lab_dry, Lab_insulDamage, Lab_screedDamage - each contain 168 Measurements (B-Scans) in .csv on 84 dry floors, floors with insulation damage and screed damage. - each floor setup was measured twice on two orthogonal survey lines, indicated by _Line1_ and _Line2_ in the file name. - the file names encode the building floor setup e.g. CT50XP100 describes a 50 mm cement screed with 100 mm extruded polystyrene below - the material codes are CT: cement screed, CA: anhydrite screed, EP: expanded polystyrene, XP: extruded polystyrene, GW: glass wool, PS: perlites further information can be found in the publication https://doi.org/10.3390/app11198820 OnSite_ - 5 folders containing B-Scans on 5 different practical moisture damages - the building floor setup is encoded according to the lab with an additional measurement point numbering at the start and a damage case annotation at the end of the file name with _dry, _insulationDamage and_screedDamage File Description: B-Scans, Measurement files - no header - dimension: 512 x N data point with N beeing the number of A-Scans including 512 samples of a 11 ns time window. - survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan Moisture References - Moist_Reference of On-Site Locations include the columns MeasPoint: Measurement point, wt%Screed: moisture content of screed layer in mass percent; wt%Insul: moisture content of insulation layer in mass percent. References were obtained by drilling cores with 68 mm diameter in the center of each survey line. - Moist_Reference_Screed of Lab data include the columns Screed: Screed material and thickness in mm, wt%Screed moisture content of screed layer in mass percent - Moist Reference_Insul of Lab data include the columns Insulation: Insulation material and thickness in mm, water addition in l: water added to the insulation layer in liters, V%Insulation: water added to the insulation layer in volume percent, RH%: resulting relative humidy in the insulation layer during measurement. These References are only avaible for Lab measurements on insulation damages. KW - GPR KW - Material Moisture KW - Building Floors KW - Laboratory KW - On-Site PY - 2024 DO - https://doi.org/10.5281/zenodo.10776684 PB - Zenodo CY - Geneva AN - OPUS4-59609 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors JF - Applied Sciences N2 - 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. KW - Radar KW - Material Moisture KW - Non-destructive testing KW - Signal Features KW - Civil Engineering KW - Machine Learning PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-533606 DO - https://doi.org/10.3390/app11198820 VL - 11 IS - 19 SP - 8820 PB - MDPI AN - OPUS4-53360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -