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Acoustic emission tomography - A new imaging technique for structural health monitoring

: Schubert, F.

Mazal, P. ; Czech Society for Nondestructive Testing; Deutsche Gesellschaft für Zerstörungsfreie Prüfung e.V. -DGZfP-, Berlin; European Federation for Non-Destructive Testing -EFNDT-:
NDT in progress : IIIrd International Workshop of NDT Experts, October 10 - 12, 2005, Prague, Czech Republic
Brno: University of Technology, 2005
ISBN: 80-2142996-8
International Meeting of NDT Experts <3, 2005, Praha>
Conference Paper
Fraunhofer IZFP, Institutsteil Dresden ( IKTS-MD) ()
structural health monitoring; localization; acoustic emission tomography

The general acceptance of structural health monitoring (SHM) techniques strongly depend on the way how the measured data are presented to the owner or operator of a structure and if a complex post-processing of the data by a scientific expert is necessary or not. Thus, a worthwhile goal is to combine SHM with traditional tomographic imaging techniques as known from other fields of NDE like x-ray or ultrasonic tomography. The acoustic emission (AE) technique is a qualified candidate for a passive SHM approach in which AE events caused by crack formation and growth in a structure under external or internal load are used to monitor its structural integrity. Besides pure counting, localization as well as moment tensor inversion are well known variants of AE analysis. In this paper a new imaging technique is presented in which AE events are used as sources for acoustic travel time tomography. For that purpose the usual iterative localization algorithm is combined with an iterative tomography algorithm. This is equivalent to the solution of the generalized inverse localization problem in locally isotropic heterogeneous media. The procedure leads to a new imaging technique where in addition to the source positions the volume of the specimen is visualized in terms of a locally varying wave speed distribution. It is shown by numerically obtained data sets at a steel-reinforced concrete model that the algorithm leads to a more accurate localization of AE events and offers totally new perspectives for acoustic emission imaging in the framework of structural health monitoring.