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SHM using guided waves - Recent activities and advances in Germany

: Mueller, Inka; Moll, Jochen; Tschöke, Kilian; Prager, Jens; Kexel, Christian; Schubert, Lars; Lugovtsova, Yevgeniya; Bach, Martin; Vogt, Thomas

Chang, F.-K. (Ed.):
Structural Health Monitoring 2019. Vol.1 : Enabling Intelligent Life-Cycle Health Management for Industry Internet of Things (IIOT), Proceedings of the Twelfth International Workshop on Structural Health Monitoring, September 10-12, 2019, Stanford University
Lancaster, Pa.: DEStech Publications, 2019
ISBN: 978-1-60595-601-5
International Workshop on Structural Health Monitoring (IWSHM) <12, 2019, Stanford>
Fraunhofer IKTS ()
guided electromagnetic wave propagation; Life Cycle; monitoring; nondestructive examination; reliability; signal processing; survey; efficient simulation; engineering structures; environmental influence; non-destructive testing; probability of detection; scientific community; simulation algorithm; structural health monitoring (SHM)

Not all issues that prevent Structural Health Monitoring (SHM) based on Guided Waves (GW) from being a part of today's monitoring solutions in industry are obvious to the scientific community. To uncover and overcome these issues, scientists working on SHM and GW problems joined in an expert committee under the patronage of the German Society for Non-Destructive Testing. An online survey among more than 700 experts and users reveals the hurdles hindering the practical application of GW-based SHM. Firstly, methods for proof of reliability of SHM " approaches are missing. Secondly, detailed understanding of phenomenological described wave-damage interactions is needed. Additionally, there are significant unsolved implementation issues and un-solved problems of signal processing including handling of environmental influences. To enable substantial proof of reliability without unaffordable experimental effort also efficient simulation tools including realistic damage interaction are needed, enabling the joint use of experimental and simulated data to predict the capabilities of the monitoring system. Considering these issues, the committee focusses on simulation, signal processing, as well as probability of detection and standardization. In the presented work, recent activities of the expert committee starting with survey results are summarized. An open access data basis of life-like measurements is presented to allow testing and comparison of signal processing and simulation algorithms. Finally, a strategy for efficient proof of reliability increasing the acceptance of SHM in industry and for successful integration of SHM into real-world engineering structures is proposed.