Αναγνώριση ρωγμών σε κατασκευές με βέλτιστη τοποθέτηση αισθητήρων
Crack identification in structures using optimal sensor locations
Προβολή/ Άνοιγμα
Συγγραφέας
Γαϊτανάρος, ΣταύροςΌνομα Επιβλέποντος
Παπαδημητρίου, Κωνσταντίνος
Ημερομηνία
2007Γλώσσα
en
Πρόσβαση
ελεύθερη
Επιτομή
A Bayesian system identification methodology is presented for estimating the crack
location, size and orientation using strain measurements. The Bayesian statistical
approach combines information from measured data and analytical or computational
models of structural behavior to predict estimates of the crack characteristics along with
the associated uncertainties, taking into account modeling and measurement errors. An
optimal sensor location methodology is proposed to maximize the information that is
contained in the measured data for crack identification problems. For this, the most
informative, about the condition of the structure, data are obtained by minimizing the
information entropy measure of the uncertainty in the model parameter estimates
provided by the above statistical system identification method. Both crack identification
and optimal sensor location formulations lead to highly non-convex optimization
problems in which multiple local and global optima may exist. A hybrid optimization
method based on evolutionary strategies and gradient based techniques is used to
determine the global minimum. The effectiveness of the proposed methodologies is
illustrated using simulated data from a single crack in a thin plate subjected to known and
unknown static loading. The effects of modeling and measurement error on the
effectiveness of the crack detection method, as well as the methodology’s limitations are
investigated.
Ακαδημαϊκός Εκδότης
Πανεπιστήμιο Θεσσαλίας. Πολυτεχνική Σχολή. Τμήμα Μηχανολόγων Μηχανικών Βιομηχανίας.