Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
|
EL
| URI: | http://purl.tuc.gr/dl/dias/2F9C95EE-527C-4D31-B2AD-853E53B79F2F | ||
| Έτος | 1998 | ||
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | ||
| Άδεια Χρήσης |
|
||
| Βιβλιογραφική Αναφορά | G.E. Stavroulakis, H. Antes ," Neural crack identification in steady state elastodynamics," Com. Methods in Ap. Mechanics and Eng. vol. 165, no. 1–4, pp.129–146, November 1998. doi: h10.1016/S0045-7825(98)00035-8 https://doi.org/10.1016/S0045-7825(98)00035-8 | ||
| Εμφανίζεται στις Συλλογές |
An inverse crack identification problem with harmonic excitation in linear elastodynamics is treated here by means of back-propagation neural network methods and boundary element techniques. The problem concerns the determination of the existence and the characteristics of a hidden crack within an elastic structure by means of measurements of the structural response on the accessible boundary for given external time-periodic loadings. The direct problem is solved by a boundary element formulation in the frequency domain which leads to a system of linear equations with frequency-dependent matrices. Thus, for a given frequency, certain similarities with linear elastostatics exist. Feed-forward multilayer neural networks trained by back-propagation are used to learn the (inverse) input-output relation of the structural system. Then, the inverse problem is solved by a simple application of the neural network recalling (production) ability.
Copyright © DIAS 2013
