TY - GEN A1 - Chaudhuri, Somsubhro A1 - Stamm, Michael T1 - Infrared thermography of turbulence patterns of operational wind turbine rotor blades supported with high-resolution photography: KI-VISIR Dataset N2 - With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading-edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI-VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie – Artificial Intelligence-Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so-called thermal turbulence patterns (TTP) that result from such surface contamination or damage. To compliment the thermographic inspections, high-resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise the turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills. KW - Reference Data KW - Infrared Thermography KW - Wind energy KW - Dataset PY - 2024 DO - https://doi.org/10.5281/zenodo.13771899 PB - Zenodo CY - Geneva AN - OPUS4-61102 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Friedrich, Alexander T1 - Simulation data for eddy current rail testing - simulation accuracy and evaluation uncertainty quantification N2 - This dataset serve to quantify the simulation error and the evaluation uncertainties in the context of eddy current rail testing. It was obtained during the AIFRI project (Artificial Intelligence for Rail Inspection) with the Faraday software by INTEGRATED Engineering Software, using its BEM Solver. KW - Non-destructive testing KW - Eddy current testing KW - Eddy current simulstion PY - 2024 DO - https://doi.org/10.5281/zenodo.13970374 PB - Zenodo CY - Geneva AN - OPUS4-61470 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Han, Ying T1 - Segmented primary phases of Al-alloy EN AW-2618A in the T61 state using synchrotron computed tomography N2 - The video file contains data from a synchrotron computed tomography measurement of the primary phases of the Al-alloy EN AW-2618A in the T61 state. The volume fraction of the primary phases was determined. KW - Aluminum alloy KW - EN AW-2618A KW - Computed tomography KW - Primary phases PY - 2024 DO - https://doi.org/10.5281/zenodo.12730717 PB - Zenodo CY - Geneva AN - OPUS4-60657 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 - GEN A1 - Völker, Tobias A1 - Mensing, Friedrich A1 - Kruschwitz, Sabine T1 - Estimation of cement content in concrete by spatially resolved laser induced breakdown spectroscopy – Dataset N2 - This dataset includes both simulated and raw measurement data as detailed in the journal paper [1]. File names follow the format SampleNo_Type, where SampleNo corresponds to the sample identifier listed in Table 1, and Type specifies the data type: either syn (synthetic) or exp (experimental). For experimental data, a slice index is appended to the file name in the format SampleNo_Type_Slice, identifying the specific subsample. [1] https://doi.org/10.1016/j.cemconres.2024.107714 KW - LIBS KW - Spectroscopy KW - Cement content KW - Elemental mapping PY - 2024 DO - https://doi.org/10.5281/zenodo.14246581 PB - Zenodo CY - Geneva AN - OPUS4-62394 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -