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Proactive condition assessment in civil engineering using automated multi-sensor systems

: Stoppel, M.; Kurz, Jochen Horst; Taffe, A.; Boller, Christian

Chang, Fu-Kuo:
Structural Health Monitoring 2011. Condition-based Maintenance and Intelligent Structures. Vol.2 : Proceedings of the Eighth International Workshop on Structural Health Monitoring; 13.-15.09.2011, Stanford University
Lancaster, Pa.: DEStech Publications, 2011
ISBN: 978-1-60595-053-2
8 S.
International Workshop on Structural Health Monitoring <8, 2011, Stanford>
Fraunhofer IZFP ()

Infrastructure is subject to continuous ageing. This has given life cycle management of infrastructure an increasing role. Reliable inspection and monitoring tools are therefore an increasing demand. A combination of different non-destructive test methods is often necessary to receive reliable results for material characterization, flaw detection and the determination of component specific geometry parameters. Regarding concrete structures thickness measurements are combined with flaw detection and additional information about reinforcement and tendon ducts is required. Therefore, a multi-sensor measurement approach is necessary with a high degree of automation. Otherwise a time consuming succession of manual measurements has to be performed which would prevent practical applications. A modular control and data acquisition approach is described and the application of two different automated measurement devices is shown. The BetoScan system consists of a self-navigating mobile robot. The system is especially designed for the investigation of reinforced concrete floors exposed to de-icing salts. The data acquisition of the OSSCAR system a multi-sensor scanner is similar to the robot approach. These different applications are based on a similar kernel allowing the modular use of different contact and noncontact sensors. The described general concept of multi-sensor data acquisition and data analysis presented here is not limited to the field of civil engineering applications.