caa a22 4500 606173005 CHVBK 20210128100731.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s10921-015-0307-7 doi (NATIONALLICENCE)springer-10.1007/s10921-015-0307-7 Clustering Based Multi Sensor Data Fusion for Honeycomb Detection in Concrete [Elektronische Daten] [Christoph Völker, Parisa Shokouhi] We use three clustering algorithms to aggregate a three-modal non-destructive testing data set into defect and not-defect groups. Our data set consist of impact-echo, ultrasound (US) and ground penetrating radar data collected on a large concrete slab with embedded simulated honeycombing defects. US performs best in defect discriminating and sizing, however the false positive rate is still high. We fuse the data set using K-Means, Fuzzy C-Means and DBSCAN clustering at feature-level. We discern that DBSCAN improves the detectability up to 10%. A discussion of its advantages over commonly used K-Means and Fuzzy C-Means clustering are provided. Springer Science+Business Media New York, 2015 Data fusion nationallicence Concrete evaluation nationallicence Honeycombing nationallicence Machine learning nationallicence Clustering nationallicence Völker Christoph BAM Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205, Berlin, Germany aut Shokouhi Parisa Department of Civil and Environmental Engineering, The Pennsylvania State University, 215 Sackett Bldg., 16802, University Park, PA, USA aut Journal of Nondestructive Evaluation Springer US; http://www.springer-ny.com 34/4(2015-12-01), 1-10 0195-9298 34:4<1 2015 34 10921 https://doi.org/10.1007/s10921-015-0307-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10921-015-0307-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Völker Christoph BAM Federal Institute for Materials Research and Testing, Unter den Eichen 87, 12205, Berlin, Germany aut NATIONALLICENCE 700 1- Shokouhi Parisa Department of Civil and Environmental Engineering, The Pennsylvania State University, 215 Sackett Bldg., 16802, University Park, PA, USA aut NATIONALLICENCE 773 0- Journal of Nondestructive Evaluation Springer US; http://www.springer-ny.com 34/4(2015-12-01), 1-10 0195-9298 34:4<1 2015 34 10921