DC05 - BAM
PhD: Joint processing and inversion of active and passive ultrasonic data
Work Package
WP1 - Innovative sensor technologies | |
X | WP2 - Advanced imaging using mechanical waves |
WP3 - Smart and robust structures and materials |
Objectives
The main objective is to overcome inherent limitations of active ultrasonic monitoring (such as Full Waveform Inversion FWI, Coda Wave Interferometry CWI) and passive Acoustic Emission (AE) techniques by combining these innovative, full wave-equation-based technologies for the first time within a single framework to allow for the acoustic imaging of the interior of engineered objects for quality assurance, inspection and monitoring. A joint simulation framework for active and passive measurement data will be set up; also, an integrated, iterative imaging procedure for active and passive ultrasonic data will be developed with: (1) an imaging method for active data, e.g. based on FWI, resulting in an optimised velocity model; (2) Reverse Time Migration (RTM) for imaging the structural interior; (3) a CWI imaging method for temporal changes in the medium, based on a sensitivity kernel from full waveform simulations using information from (1) and (4); and (4) an inverse imaging for AE data based on simulated wave propagation (Time Reversal, TR), using information from (1) and (3). All these methods use simulations of the wave propagation inside the object; they will generate the best possible input models to derive the most reliable output models. The combination of these techniques (1)-(4) will provide comprehensive assessments of ongoing processes, such as degradation in a structure, by providing beneficial updates and interconnections among the techniques, thus allowing detailed 3D images, and at best in near real time. All these procedures will be adapted to the sensors/instrumentation developed within the project as well as tested and validated on case studies provided by by other doctoral students in USES2.
Planned intersectoral, interdisciplinary and international secondments
- IZFP, Florian Römer, 2 months, M11-M12: Algorithms for data compression, integration to sensors.
- UPM, Antonio Fernandez-Lopez, 2 months, M18-M19: Training on optical fibre and embedded sensors in other industries.
- Zensor, Yves Van Ingelgem, 2 months, M27-M28: Training in actual SHM installations.