Abstract
In this work parametric reduced order models (pROMs) for cracked shells are developed and applied to crack detection problems. Mesh morphing is employed to allow for parameterization of the models with respect to the crack location and size, while a clustering approach is adopted to partition the parameter space in sub-domains, for which efficient local reduced order models (ROMs) are constructed. Subsequently, the proposed ROMs are employed as forward simulators within an inverse problem setting, aiming to identify the location of the fault (crack). An output-only scheme is adopted, in the absence of information regarding the loading time history, based on transmissibility functions. The resulting scheme is tested through numerical examples involving realistic geometries, consisting of curved shells or multiple components.
Highlights
In the last decades, advances in sensing technologies have led to the development of an array of methods for condition monitoring, based on different types of measurements, and targeting different types of applications
One of the major challenges in the context of vibration-based Structural Health Monitoring (SHM) in general, and crack detection in particular, lies in the operational variations stemming from the loading conditions, which exert a strong influence on such features and on the accuracy of detection
Given a numerical model and a set of measurements obtained from the actual system, the crack detection problem can be posed as an inverse problem, mathematically expressed as follows: μc ≈ argminμ∈MF (μ) with M = μ ∈ RNp : μmi in⩽μi⩽μmi ax ∀i = 1, ..., Np where μc is the parameter vector corresponding to the actual crack location, μmi in and μmi ax are lower and upper bounds for parameter μi, and F is some metric of the difference between the measured and simulated response of the system
Summary
Advances in sensing technologies have led to the development of an array of methods for condition monitoring, based on different types of measurements, and targeting different types of applications. A common trait in most of the aforementioned works, and inverse problems in general, is the use of optimisation to minimise the discrepancy between some damage-sensitive feature extracted from the measured response and the corresponding quantity computed by the model Within this context, one of the major challenges in the context of vibration-based Structural Health Monitoring (SHM) in general, and crack detection in particular, lies in the operational variations stemming from the loading conditions, which exert a strong influence on such features and on the accuracy of detection.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
